Efficient Combination Research Articles

Definition and understanding of “efficiency” in healthcare provision research: a scoping review

BackgroundWith rising healthcare costs over the last decades, the concept of efficiency has gained popularity in healthcare provision research. As efficiency can be understood and measured in many different ways, it is often unclear what is meant by “efficient health systems” or “efficient healthcare providers”.ObjectivesThis study aims to analyze and categorize the different definitions and understandings of “efficiency” used in healthcare provision research over time.MethodsWe searched five databases (Medline, Embase, CINAHL, Business Source Premier, and EconLit) to conduct a scoping review. Sources were screened independently by two researchers, using the online software Rayyan. Results are reported using PRISMA-ScR.ResultsOf 1,441 individual sources identified, 389 were included in the review. Most papers (77.3%) using the term “efficiency” do not include explicit definitions or explanations of their understanding of it. Almost all papers (99.0%) are interested in productive efficiency (vs. allocative efficiency) and more specifically technical efficiency, therefore comparing the number of inputs used and outputs produced. While many papers (70.4%) include some elements of quality of care or health outcomes in their discussion, few (30.3%) include aspects of quality in their measurement of efficiency. Over the last decades, Data Envelopment Analysis has become the main method to measure efficiency. We propose a broad categorization of efficiency definitions that could be used by researchers to improve the comprehensibility and comparability of their research. Key features are the general type of efficiency, inclusion of quality or outcome information, and inclusion of cost information.DiscussionTo allow for better comparability and comprehensibility, researchers in healthcare provision should state explicitly which type of efficiency they are studying. To do this, we propose to use combinations of the terms productive efficiency, allocative efficiency, quality-inclusive efficiency, and cost efficiency.

Metabolic engineering of Streptomyces roseosporus for increased production of clinically important antibiotic daptomycin.

Daptomycin (DAP), a novel cyclic lipopeptide antibiotic produced by Streptomyces roseosporus, is clinically important for treatment of infections caused by multidrug-resistant Gram-positive pathogens, but the low yield hampers its large-scale industrial production. Here, we describe a combination metabolic engineering strategy for constructing a DAP high-yielding strain. Initially, we enhanced aspartate (Asp) precursor supply in S. roseosporus wild-type (WT) strain by separately inhibiting Asp degradation and competitive pathway genes using CRISPRi and overexpressing Asp synthetic pathway genes using strong promoter kasOp*. The resulting strains all showed increased DAP titre. Combined inhibition of acsA4, pta, pyrB, and pyrC increased DAP titre to 167.4 μg/mL (73.5% higher than WT value). Co-overexpression of aspC, gdhA, ppc, and ecaA led to DAP titre 168 μg/mL (75.7% higher than WT value). Concurrently, we constructed a chassis strain favourable for DAP production by abolishing by-product production (i.e., deleting a 21.1 kb region of the red pigment biosynthetic gene cluster (BGC)) and engineering the DAP BGC (i.e., replacing its native dptEp with kasOp*). Titre for the resulting chassis strain reached 185.8 μg/mL. Application of our Asp precursor supply strategies to the chassis strain further increased DAP titre to 302 μg/mL (2.1-fold higher than WT value). Subsequently, we cloned the engineered DAP BGC and duplicated it in the chassis strain, leading to DAP titre 274.6 μg/mL. The above strategies, in combination, resulted in maximal DAP titre 350.7 μg/mL (2.6-fold higher than WT value), representing the highest reported DAP titre in shake-flask fermentation. These findings provide an efficient combination strategy for increasing DAP production and can also be readily applied in the overproduction of other Asp-related antibiotics.

Classification of recovery states in U15, U17, and U19 sub-elite football players: a machine learning approach

IntroductionA promising approach to optimizing recovery in youth football has been the use of machine learning (ML) models to predict recovery states and prevent mental fatigue. This research investigates the application of ML models in classifying male young football players aged under (U)15, U17, and U19 according to their recovery state. Weekly training load data were systematically monitored across three age groups throughout the initial month of the 2019–2020 competitive season, covering 18 training sessions and 120 observation instances. Outfield players were tracked using portable 18-Hz global positioning system (GPS) devices, while heart rate (HR) was measured using 1 Hz telemetry HR bands. The rating of perceived exertion (RPE 6–20) and total quality recovery (TQR 6–20) scores were employed to evaluate perceived exertion, internal training load, and recovery state, respectively. Data preprocessing involved handling missing values, normalization, and feature selection using correlation coefficients and a random forest (RF) classifier. Five ML algorithms [K-nearest neighbors (KNN), extreme gradient boosting (XGBoost), support vector machine (SVM), RF, and decision tree (DT)] were assessed for classification performance. The K-fold method was employed to cross-validate the ML outputs.ResultsA high accuracy for this ML classification model (73–100%) was verified. The feature selection highlighted critical variables, and we implemented the ML algorithms considering a panel of 9 variables (U15, U19, body mass, accelerations, decelerations, training weeks, sprint distance, and RPE). These features were included according to their percentage of importance (3–18%). The results were cross-validated with good accuracy across 5-fold (79%).ConclusionThe five ML models, in combination with weekly data, demonstrated the efficacy of wearable device-collected features as an efficient combination in predicting football players’ recovery states.

Online Hydraulic Stiffness Modulation of a Soft Robotic Fish tail for Improved Thrust and Efficiency.

This paper explores online stiffness modulation within a single tail stroke for swimming soft robots. Despite advances in stiffening mechanisms, little attention has been given to dynamically adjusting stiffness in real-time, presenting a challenge in developing mechanisms with the requisite bandwidth to match tail actuation. Achieving an optimal balance between thrust and efficiency in swimming soft robots remains elusive, and the paper addresses this challenge by proposing a novel mechanism for independent stiffness control, leveraging fluid-driven stiffening within a patterned pouch. Inspired by fluidic-driven actuation, this approach exhibits high bandwidth and facilitates significant stiffness changes. We perform experiments to demonstrate how this mechanism enhances both thrust and swimming efficiency. The tail actuation and fluid-driven stiffening can be optimized for a specific combination of thrust and efficiency, tailored to the desired maneuver type. The paper further explores the complex interaction between the soft body and surrounding fluid and provides fluid dynamics insights gained from the vortices created during actuation. Through frequency modulation and online stiffening, the study extends the Pareto front of achievable thrust generation and swimming efficiency.

Robust self-healing capacity and high mechanical properties of castor oil-based waterborne polyurethane based on “kill two birds with one stone” strategy

Achieving ideal combination of high self-healing efficiency and good mechanical properties is of significance for the breakthrough in the application of self-healing materials. Herein, the functionalized castor oil-based waterborne polyurethane (DA-CWPU) was constructed based on “killing two birds with one stone” molecular design strategy with the addition of self-healing monomer D-A adduct. Firstly, D-A adduct containing flexible D-A bonds and rigid ring structure was prepared by D-A reaction with furfuryl alcohol (FA) and bismaleimide (BMI) as raw materials, which could not only effectively enhanced the self-healing ability of the material, but also ensured the strong mechanical properties. Then, DA-CWPU emulsion with favourable self-healing and mechanical properties was synthesized by the polymerization of castor oil (CO), isophorone diisocyanate (IPDI) and D-A adduct. The DA-CWPU film has preferable self-healing efficiency (93 % at 100 °C for 50 min), unique shape memory effect (rehabilitate after heating at 100 °C for 45 s), good toughness (485 MJ/m3), strong tensile strength (5.96 MPa) and sufficient elongation (115 %). At the same time, the self-healing DA-CWPU film can be recycled through solution casting. The sustainable castor oil-based waterborne polyurethane can be used as finishing agents for leather products, which realizes repeatedly self-healing in case of surface damage, greatly increasing the service life of the material and mechanical properties, providing a new approach for the development of mechanically robust self-healing materials.

Structural, elastic and gamma-ray attenuation properties of potassium borate glasses doped with BaO, Bi2O3, or Pb3O4: A comparative assessment

This study investigates the effect of substituting boron oxide (B2O3) with heavy metal oxides (HEMOs) on the structural, mechanical, and gamma-ray shielding properties of potassium borate (KB) glass systems. The glass compositions analyzed include 80B2O3–20K2O and 65B2O3–20K2O-15HEMO (where, HEMO = BaO, Bi2O3, or Pb3O4). All samples were prepared using the melt-quenching method, and their amorphous nature was confirmed through X-ray diffraction (XRD). Fourier-transform infrared spectroscopy (FTIR) had revealed BO3, BO4, and BiO6 groups beside the B–O–B linkages. The density increased with the addition of HEMOs, following the order: Pb3O4 (KB4) > Bi2O3 (KB3) > BaO (KB2) > and pure KB (KB1). This trend was also observed in the molar volume (Vₘ) and oxygen molar volume (Vₒ), while the oxygen packing density (Pρ) decreased. Mechanical properties assessed using the Makishima-Mackenzie model indicated that KB3 exhibited the highest elastic modulus (Yₘ) and Poisson's ratio (μ). The microhardness (Hₘ) followed the sequence KB2 > KB3 > KB4 > KB1, attributed to the higher bonding energy in KB2. Gamma-ray shielding parameters, including mass attenuation coefficients (MAC), were calculated using Phy-X and XCOM software for photon energies between 0.2835 MeV and 1.333 MeV. KB4 (Pb3O4) showed superior shielding performance with the highest linear attenuation coefficient (LAC) and the lowest half-value layer (HVL) and mean free path (MFP). Despite KB4's high density, KB3 (Bi2O3) is suggested as a more suitable candidate for radiation shielding applications due to its balanced combination of mechanical strength and γ-ray attenuation efficiency.

Serum extracellular vesicles 3'tRF-ThrCGTand 3'tRF-mtlleGAT combined with tumor markers can serve as minimally invasive diagnostic predictors for colorectal cancer.

Colorectal cancer (CRC) is a leading cause of morbidity and mortality, and timely diagnosis and intervention are crucial for cancer patients. Transfer RNA-derived fragments (tRFs) play a noncoding regulatory role in organisms. Serum EV(extracellular vesicles), as an integral mediator of intercellular transmission of genetic information vesicles in Transfer RNA-derived fragment (tRF RNA), are expected to be minimally invasive diagnostic and predictive biologic factors of CRC. Collect serum samples from 205 CRC patients, and then isolate extracellular vesicles from the serum. Captured the physical morphology of EV through transmission electron microscopy. The particle size was detected by particle size assay, and protein expression on the surface of EV was verified by Western blot. Gene microarrays were screened for differentially expressed tRF-RNA. TRF RNAs were verified by qPCR for differential expression in 205 CRC patients and 201 healthy donors, assessing the CRC diagnostic efficiency by area under the curve (AUC). Compared with 201 healthy donors, CRC patients experienced significantly down-regulated serum EV 3'tRF-ThrCGT while significantly up-regulated 3'tRF-mtlleGAT. Serum EV 3'tRF-ThrCGT and 3'tRF-mtlleGAT predictive diagnostic efficiency: 0.669 and 0.656, and the combination of CEA and CA724 predictive diagnostic efficiency was 0.938. The study data showed that 3'tRF-ThrCGT and 3'tRF-mtlelGAT can be minimally invasive diagnostic CRC indicators. The combination of tumor markers CEA and CA724 has important diagnostic significance.

YPR-SLAM: A SLAM System Combining Object Detection and Geometric Constraints for Dynamic Scenes

Traditional SLAM systems assume a static environment, but moving objects break this ideal assumption. In the real world, moving objects can greatly influence the precision of image matching and camera pose estimation. In order to solve these problems, the YPR-SLAM system is proposed. First of all, the system includes a lightweight YOLOv5 detection network for detecting both dynamic and static objects, which provides pre-dynamic object information to the SLAM system. Secondly, utilizing the prior information of dynamic targets and the depth image, a method of geometric constraint for removing motion feature points from the depth image is proposed. The Depth-PROSAC algorithm is used to differentiate the dynamic and static feature points so that dynamic feature points can be removed. At last, the dense cloud map is constructed by the static feature points. The YPR-SLAM system is an efficient combination of object detection and geometry constraint in a tightly coupled way, eliminating motion feature points and minimizing their adverse effects on SLAM systems. The performance of the YPR-SLAM was assessed on the public TUM RGB-D dataset, and it was found that YPR-SLAM was suitable for dynamic situations.

Spatial phase distortion compensation technology based on combinatorial optimization method in heterodyne detection

The spatial phase distortion caused by turbulent atmosphere, target speckle, or optical system aberration causes decoherence of heterodyne signals. The decoherence effect is the key problem that imposes restrictions on the application of laser heterodyne techniques. We propose an approach for spatial phase distortion correction based on a genetic algorithm by establishing a one-to-one correspondence between combination of spatial phase compensation amounts and heterodyne efficiency of the system. The spatial phase distortion compensation problem is converted into a combinatorial optimization problem. The experiment results show that the method achieves excellent compensation performance for the spatial phase distortion, significantly contributing to the applications of heterodyne techniques.

One‐Step Room Temperature Synthesis of Printable Carbon Quantum Dots Ink for Visual Encryption and High‐Performance Photodetector

AbstractCarbon quantum dots (CQDs) have emerged as promising materials for optoelectronic applications and have garnered much interest as potential competitors to conventional inorganic or hybrid semiconductor quantum dots because of carbon's intrinsic merits of high stability, low cost, and environment‐friendliness. The ability of easy formulation of functional ink of CQDs is necessary for the development of industrial‐scale, reliable, inexpensive printing/coating processes, for its full exploitation in the ever‐growing class of applications in sensors, optoelectronics, and energy storage and conversion. Here a facile one‐step room‐temperature synthesis of printable, fluorescent CQD ink is demonstrated. The as‐synthesized fluorescent CQD ink is used for invisible fingerprint stamps, printing of micro‐patterns, and soft lithographic patterning with a resolution down to 1.5 µm. This functional CQD ink is also used to fabricate a high‐performance CQD‐ZnO heterojunction ultraviolet (UV) photodetector with a photo‐responsivity of 3.85 A W−1, detectivity of 6.78 × 1010 Jones, and an external quantum efficiency (EQE) of 15.3%. The enhanced device performance can be attributed to CQD's high photocurrent generation efficiency and rational combination of the asymmetric electrode materials. This work enables a high‐temperature stable CQD fluorescent ink synthesis method to fulfill the processing requirements of printing and soft lithographic patterning for visual encryption and optoelectronics.

Combinatory Immunotherapy for Glioblastoma Treatment

AbstractDespite advancements in the treatment of glioblastoma, it faces challenges due to tumor heterogeneity, the blood‐brain barrier, recurrence, immune evasion, and conventional strategies, leading to low survival and a poor prognosis. Therefore, it is crucial to develop novel, useful treatment strategies for improving brain distribution to overcome blood‐brain barriers (BBB) and help the treatment of glioblastoma. Conventional immunotherapy like checkpoint inhibitors, CAR‐T cell therapy, monoclonal antibodies, cancer vaccines, and adoptive cell transfer often suffers from low therapeutic outcomes because the singular therapy generally has shortcomings, such as the cold immune microenvironment of brain tumors. In contrast, the emerging combinatory immunotherapy integrated with chemo‐immunotherapy, photothermal‐immunotherapy, and radio‐immunotherapy has shown great promise to modulate tumoral immune microenvironment and boost treatment outcomes. This review discusses the immune microenvironment of GBM, its impact on immunological effects, current immunotherapy methods, and advanced studies. It also introduces combinational GBM immunotherapy with traditional cancer therapies like chemo‐immunotherapy, surgery‐immunotherapy, photothermal‐immunotherapy, and radiotherapy‐immunotherapy. In the future, it is anticipated that this article will provide beneficial information and a path for the strategy of innovative, efficient combination immunotherapy in the treatment of glioblastoma.

Modeling hard rock breakage behavior influenced by the tipped hob cutter's tooth structure using the 2D discrete element (DE) model

A deep understanding of the mesoscopic damage evolution mechanism of tipped hob cutter in hard rock, as influenced by tooth structure parameters and working parameters, can assist in optimizing the tooth of tipped hob cutter and uncovering the failure conditions and mechanism of rock. In this paper, a series of numerical simulations of rock breaking by tipped hob cutter's tooth were modelled, calibrated, and analyzed to investigate the failure conditions and mechanism of rock by tipped hob cutter, as well as the effects of tooth profiles and working parameters on the fracture evolution of hard rock. The results show that the most efficient combination of tooth profile and Dp differs depending on the rock types. D-type teeth with a penetration depth of Dp = 3 mm are optimal for crushing granite, while A-type teeth with a penetration depth of Dp = 4 mm are suitable for crushing sandstone.

Novel hybrid treatment for canal water recycling by integrating coagulation, catalytic ozonation, and filtration for agricultural sustainability

This study employed a novel approach, utilizing recycled alumina flocs after coagulation/flocculation (C/F) as a catalyst in catalytic ozonation (CO), along with the auxiliary catalyst sodium zeolite (Na-Z), where alumina produces hydroxyl radicals, and zeolite enhances molecular ozone reactions. This synergistic strategy focuses on treating contaminated canal water, recognizing that the presence of various pollutants can reduce the efficacy of a singular catalyst type. In the current investigation, alum, Na-Z, and rice husk (RH) were applied as a coagulant, catalyst, and filter media in C/F, CO, and filtration processes respectively. Four treatment technologies (C/F, O3, O3/Na-Z, and RHF) were studied independently and in four different combinations (O3–C/F, C/F–O3, C/F–O3/Na-Z, and C/F–O3/Na-Z–RHF) for the first time and their efficacious performance was evaluated. It was revealed that the combination-IV (C/F–O3/Na-Z–RHF) was a more efficient and economical treatment than others. This novel integrated treatment C/F–O3/Na-Z–RHF has remarkable removal efficiency of 99 %, 99 %, 85 %, 93 %, 100 %, 89 %, and 93 % for TSS, turbidity, COD, BOD5, fecal coliforms, cadmium, and copper respectively, under optimized working conditions. Also, treated canal water complied with the studied irrigation water quality guidelines. Notably, this efficient treatment combination halved the treatment time compared to others, potentially reducing the electrical energy demand of 11.45 kWh.m−3 and the overall operational treatment cost of 1.62 USD.m−3. Hence, the application of this efficient hybrid treatment system contributed to recycling canal water for agricultural use, livestock, and pasture watering, playing a crucial role in mitigating the water crisis.

Financial sector development and microcredit to small firms

This article investigates the relationship between countries’ financial sector development and the loans extended to micro, small, and medium-sized enterprises (MSMEs or small firms) by microfinance institutions (MFIs). Using 4,801 MFI-year observations worldwide, we find a negative relationship between financial sector development and MSME lending by microfinance institutions. In other words, improvement in financial development, defined as a combination of depth, access, and efficiency, decreases micro-lending to small firms due essentially to intense competition from banks. Moreover, looking at the ownership status of microfinance institutions, we find that the intense competition between profit-oriented microfinance institutions and banks mainly drives the observed negative relationship. For nonprofit microfinance institutions, financial sector development is not significantly associated with their lending to small firms. In a less developed financial sector, microfinance institutions lend more to small firms, fulfilling their social mission.

Intelligent Dance Motion Evaluation: An Evaluation Method Based on Keyframe Acquisition According to Musical Beat Features.

Motion perception is crucial in competitive sports like dance, basketball, and diving. However, evaluations in these sports heavily rely on professionals, posing two main challenges: subjective assessments are uncertain and can be influenced by experience, making it hard to guarantee timeliness and accuracy, and increasing labor costs with multi-expert voting. While video analysis methods have alleviated some pressure, challenges remain in extracting key points/frames from videos and constructing a suitable, quantifiable evaluation method that aligns with the static-dynamic nature of movements for accurate assessment. Therefore, this study proposes an innovative intelligent evaluation method aimed at enhancing the accuracy and processing speed of complex video analysis tasks. Firstly, by constructing a keyframe extraction method based on musical beat detection, coupled with prior knowledge, the beat detection is optimized through a perceptually weighted window to accurately extract keyframes that are highly correlated with dance movement changes. Secondly, OpenPose is employed to detect human joint points in the keyframes, quantifying human movements into a series of numerically expressed nodes and their relationships (i.e., pose descriptions). Combined with the positions of keyframes in the time sequence, a standard pose description sequence is formed, serving as the foundational data for subsequent quantitative evaluations. Lastly, an Action Sequence Evaluation method (ASCS) is established based on all action features within a single action frame to precisely assess the overall performance of individual actions. Furthermore, drawing inspiration from the Rouge-L evaluation method in natural language processing, a Similarity Measure Approach based on Contextual Relationships (SMACR) is constructed, focusing on evaluating the coherence of actions. By integrating ASCS and SMACR, a comprehensive evaluation of dancers is conducted from both the static and dynamic dimensions. During the method validation phase, the research team judiciously selected 12 representative samples from the popular dance game Just Dance, meticulously classifying them according to the complexity of dance moves and physical exertion levels. The experimental results demonstrate the outstanding performance of the constructed automated evaluation method. Specifically, this method not only achieves the precise assessments of dance movements at the individual keyframe level but also significantly enhances the evaluation of action coherence and completeness through the innovative SMACR. Across all 12 test samples, the method accurately selects 2 to 5 keyframes per second from the videos, reducing the computational load to 4.1-10.3% compared to traditional full-frame matching methods, while the overall evaluation accuracy only slightly decreases by 3%, fully demonstrating the method's combination of efficiency and precision. Through precise musical beat alignment, efficient keyframe extraction, and the introduction of intelligent dance motion analysis technology, this study significantly improves upon the subjectivity and inefficiency of traditional manual evaluations, enhancing the scientificity and accuracy of assessments. It provides robust tool support for fields such as dance education and competition evaluations, showcasing broad application prospects.

A Novel Ce─Mn Heterojunction‐Based Multi‐Enzymatic Nanozyme with Cancer‐Specific Enzymatic Activity and Photothermal Capacity for Efficient Tumor Combination Therapy

AbstractCatalytic medicine, using enzymes or nanozymes, is an emerging method for cancer treatment. However, its applicability is limited by the low catalytic activity in the tumor microenvironment (TME). In this work, a versatile and synthesis‐friendly nanozyme, CeO2Mn1.08Ox nanoclusters, is prepared. This novel Ce─Mn heterojunction is formed by oxidation of CeO2 nanoparticles through H2SO4/KMnO4. CeO2Mn1.08Ox exhibits high multi‐enzymatic catalytic activities and acts as a catalase (CAT), peroxidase (POD), and oxidase (OXD) mimics under acidic conditions. It can regulate the TME by relieving hypoxia and consuming endogenous glutathione (GSH). Glucose oxidase (GOx) is then incorporated into CeO2Mn1.08Ox and linked with poly(ethylene glycol) (PEG) to obtain the cascade enzyme system (Ce─Mn)‐PEI/GOx‐PEG. CeO2Mn1.08Ox exhibits CAT‐like properties, which sensitize GOx‐based starvation therapy, and POD‐ and OXD‐like properties, which generate highly cytotoxic reactive oxygen species (ROS) in cancer cells. The glucose catabolic product, H2O2, is also used to generate O2 and ROS. In addition, the heterojunction structure provides CeO2Mn1.08Ox with near‐infrared (NIR) photothermal capability, making it suitable for photothermal therapy (PTT). Density functional theory (DFT) calculations provide possible reasons for the high catalytic activity and photothermal capability of CeO2Mn1.08Ox. When combining mild PTT with catalytic therapy, the cascade enzyme system (Ce─Mn)‐PEI/GOx‐PEG can efficiently ablate tumors.

Comparative study on productivity of double slope solar still using different wick and energy storage materials

The aim of the proposed study is to evaluate the efficiency of Double Slope Solar Still (DSS) using different wick and energy storage materials. In the study, wick materials such as jute, cotton and sponge were used in combination with energy storage materials such as mild steel, cast iron and copper. The experiments were conducted using DSS with different combinations of wick and energy storage materials to determine the efficient performance combination. The results show that sponge and copper have higher efficiency with wicks and energy storage materials. The results show that the maximum amount of water produced in a single day was 3147 ml when the DSS system was used with a combination of sponge and copper materials. This range shows an increase of 17.47 % and 12.44 % over the DSS with jute and copper and the DSS with the combination of cotton and copper respectively. The DSS showed the highest average energy efficiency when used in conjunction with a combination of sponge and copper, namely 51 % of the average efficiency. This corresponds to an increase of 18.60 % and 10.86 % compared to the combination of DSS with jute and copper and the combination of DSS with cotton and copper respectively. The best evaporation heat transfer coefficient of 345 W/m2K was determined for the combination of DSS with sponge and copper. Average exergy efficiency is also maximum of 3.076 % for the DSS with sponge and copper materials, which is higher than other investigated combinations. The proposed system has an energy payback period of 1.26 years, an energy production factor of 0.78, a life cycle efficiency of 6.9 % and a cost of $0.031 per litre of water produced in the environmental economic analysis.

The combination of high leaf hydraulic safety and water use efficiency allows alpine shrubs to adapt to high‐altitude habitats

Abstract Leaf hydraulic traits are considered the key determinants of gas exchange and therefore affect species distributions along environmental gradients, but the patterns of leaf hydraulic traits and their associations with gas exchange across altitudinal gradients remain largely unknown. Here, we measured leaf hydraulic traits, gas exchange, leaf anatomical traits and plant size traits in two dominant alpine shrubs (Caragana jubata and Salix gilashanica) across an altitudinal gradient from 3100 to 3700 m. The findings indicated that with increasing altitude, both shrub species exhibited an increase in leaf hydraulic safety (more negative Kleaf P50), a decrease in leaf hydraulic efficiency (Kleaf‐max) and an increase in intrinsic water use efficiency (WUEi), thus allowing them to adapt to higher altitude habitats. The more negative Kleaf P50 was associated with a greater ratio of major to minor vein density (VLAmaj/VLAmin), the lower Kleaf‐max was associated with a lower minor vein density (VLAmin) and greater increase in WUEi arose from the small decrease in the photosynthetic rate relative to the stomatal conductance. However, C. jubata was consistent with the ‘hydraulic safety strategy’ with a great decrease in Kleaf P50, a small decrease in Kleaf‐max and a small increase in WUEi along with decreasing plant height and leaf area with increasing altitude. Whereas S. gilashanica was consistent with the ‘photosynthetic efficiency strategy’ with a small decrease in Kleaf P50, a greater decrease in Kleaf‐max and a greater increase in WUEi along with an increasing plant height and unchanged leaf area with increasing altitude. Overall, these findings provide new insights to improve understanding how shift in leaf hydraulic traits and their associations with gas exchange and plant size allow plants to adapt to high‐altitude habitats. Read the free Plain Language Summary for this article on the Journal blog.

Optimized compact fortified weight-prioritized convolutional network for swift skin lesion identification using dermoscopic images

Skin cancer is a leading cause of cancer-related mortality, posing a significant global health challenge. Early detection and treatment are crucial for survival rates. While dermoscopy is a valuable non-invasive imaging tool for diagnosing skin lesions, its reliance on the expertise of dermatologists introduces variability, affecting diagnostic reliability. Existing deep learning models for skin lesion analysis often prioritize accuracy over computational efficiency, limiting their practical application in clinical settings where both rapidity and precision are crucial. To address these limitations, this study proposes a novel model called the Compact Fortified Weight-Prioritized Convolutional Network (CWCN), optimized using the Harbor Seal Whiskers Optimization (HOA) algorithm (CWCN-HOA-SLD-DI). The CWCN is designed to offer a balance between high performance and computational efficiency. Initially, dermoscopic images from the ISIC Archive dataset are collected and subjected to a series of preprocessing steps, including image augmentation to enhance robustness, normalization using log-sinh with Adaptive Box-Cox transformation, and noise removal employing Guided Box Filtering (GBF) and Guided Image Filtering (GIF). The CWCN-HOA framework is then utilized to classify skin lesions into categories such as Malignant, Melanocytic Nevus, Basal Cell Carcinoma, Actinic Keratosis, Benign Keratosis, Dermatofibroma, and Vascular Lesion. The proposed CWCN-HOA-SLD-DI model is implemented in Python, and its performance is evaluated against current methods. The results indicate that the CWCN-HOA approach achieves significant improvements in both classification accuracy as 99.98% and computational efficiency as 92ms. By offering a combination of high performance and computational efficiency, the CWCN-HOA model represents a promising solution for accurate and efficient skin cancer detection. Its potential to improve the diagnostic capabilities of dermatologists and enhance patient outcomes underscores its significance in addressing this critical global health issue.

Dramatic Impact of Materials Combinations on the Chemical Organization of Core-Shell Nanocrystals: Boosting the Tm3+ Emission above 1600 nm.

This article represents the first foray into investigating the consequences of various material combinations on the short-wave infrared (SWIR, 1000-2000 nm) performance of Tm-based core-shell nanocrystals (NCs) above 1600 nm. In total, six different material combinations involving two different types of SWIR-emitting core NCs (α-NaTmF4 and LiTmF4) combined with three different protecting shell materials (α-NaYF4, CaF2, and LiYF4) have been synthesized. All corresponding homo- and heterostructured NCs have been meticulously characterized by powder X-ray diffraction and electron microscopy techniques. The latter revealed that out of the six investigated combinations, only one led to the formation of a true core-shell structure with well-segregated core and shell domains. The direct correlation between the downshifting performance and the spatial localization of Tm3+ ions within the final homo- and heterostructured NCs is established. Interestingly, to achieve the best SWIR performance, the formation of an abrupt interface is not a prerequisite, while the existence of a pure (even thin) protective shell is vital. Remarkably, although all homo- and heterostructured NCs have been synthesized under the exact same experimental conditions, Tm3+ SWIR emission is either fully quenched or highly efficient depending on the type of material combination. The most efficient combination (LiTmF4/LiYF4) achieved a high photoluminescence quantum yield of 39% for SWIR emission above 1600 nm (excitation power density in the range 0.5-3 W/cm2) despite significant intermixing. From now on, highly efficient SWIR-emitting probes with an emission above 1600 nm are within reach to unlock the full potential of in vivo SWIR imaging.