Strategies For Improving Performance Research Articles

Heterometal modified Fe3O4 hollow nanospheres as efficient catalysts for organic transformations

Iron oxides (e.g. Fe3O4) are ideal support materials for catalytic organic transformations owing to their sufficient natural abundance, excellent thermal stability and magnetic recycling property. Herein, we report the synthesis of active heterometal (M = Pd, Cu) modified Fe3O4 (M-Fe3O4) hollow nanospheres via a two-step solvothermal/annealing method. Due to the uniformly dispersed active heterometal species in the spherical shell of Fe3O4 hollow nanospheres, the as-prepared Pd-Fe3O4 catalyst exhibits remarkable catalytic activity toward 4-nitrophenol reduction with a turnover frequency of 145 min−1, and shows excellent stability and magnetic recyclability. The catalytic efficiency surpasses most of the similar Fe3O4 supported metal catalysts reported in literatures. Particularly, Cu-Fe3O4 exhibited 5 times higher activity for benzyl alcohol oxidation compared to that of bare Fe3O4 synthesized by the same procedure. An impressive conversion of 49.66% and an outstanding selectivity of 100% can be achieved. Moreover, the positive effects of Pd or Cu elements on the 4-NP molecule adsorption were further confirmed via both experimental results and theoretical studies. Our work demonstrate that the activity boost of iron oxides by heterometal modification is a promising strategy for performance improvement.

Simultaneous Near‐Surface Trace Doping and Surface Modifications by Gas–Solid Reactions during One‐Pot Synthesis Enable Stable High‐Voltage Performance of LiCoO2

AbstractLiCoO2 (LCO) with a high theoretical capacity of 274 mAh g–1 can rarely achieve a high practical capacity even at an upper cutoff voltage of 4.6 V due to severe structural instability and interface side reactions. Herein, an in situ strategy of gas–solid modifications during synthesis is proposed to improve the performance of LCO using sulfocompound‐contained expanded graphite (EG) as templates. In situ generated SO2 gas from EG enables the Co‐coating of coherent spinel LixCo2O4 and Li2SO4 and the trace doping of high‐valence S mainly in the near‐surface regions via its reactions with the precursors. The modified LCO possesses excellent structural reversibility, interfacial stability, slight dissolution of Co2+, high diffusion coefficients of Li+, and low O 2p band top. This endows LCO with remarkably improved high‐voltage performance, 222 and 143 mAh g‐1 at 0.1 and 20 C, respectively, and 88% capacity retention over 100 cycles at 1 C for LCO/Li half cells between 2.8 and 4.6 V, and 202 mAh g–1 at 1 C and 87% capacity retention over 1000 cycles between 2.8 and 4.5 V for LCO/graphite full cells. This study provides a unique, simple, and upscalable strategy for performance improvement of electrode materials.

Advances in Detection of Antibiotic Pollutants in Aqueous Media Using Molecular Imprinting Technique-A Review.

Antibiotics constitute one of the emerging categories of persistent organic pollutants, characterised by their expansion of resistant pathogens. Antibiotic pollutants create a major public health challenge, with already identifiable detrimental effects on human and animal health. A fundamental aspect of controlling and preventing the spread of pollutants is the continuous screening and monitoring of environmental samples. Molecular imprinting is a state-of-the-art technique for designing robust biomimetic receptors called molecularly imprinted polymers (MIPs), which mimic natural biomolecules in target-selective recognition. When integrated with an appropriate sensor transducer, MIP demonstrates a potential for the needed environmental monitoring, thus justifying the observed rise in interest in this field of research. This review examines scientific interventions within the last decade on the determination of antibiotic water pollutants using MIP receptors interfaced with label-free sensing platforms, with an expanded focus on optical, piezoelectric, and electrochemical systems. Following these, the review evaluates the analytical performance of outstanding MIP-based sensors for environmentally significant antibiotics, while highlighting the importance of computational chemistry in functional monomer selection and the strategies for signal amplification and performance improvement. Lastly, the review points out the future trends in antibiotic MIP research, as it transits from a proof of concept to the much demanded commercially available entity.

Performance Improvement of Perovskite Solar Cells by Interactions between Nano‐Sized Quantum Dots and Perovskite

AbstractPerovskite solar cells (PSCs) have undergone rapid progress and attracted considerable attention as a promising alternative to conventional photovoltaics but currently still face the challenges of Shockley‐Queisser (SQ) limit and stability. Herein, the use of quantum dots (QDs) for the advancement of PSCs is focused on. The interactions between QDs and perovskite are discussed in terms of energy and charge transfer. The effective strategies for performance improvement of devices treated with QDs are interpreted from the point of view of surface modification (passivation and mixing), and microstructure (buffer function) and nanostructure (core/shell structure). In particular, possible routes to success in surpassing the SQ limit are summarized in association with the corresponding mechanisms. Also, the mechanisms for the enhancement of stability by QD treatment are analyzed, including quantum confinement effect, crystallization, ion migration inhibition, hydrophobicity improvement, passivation, and decomposition suppression. In addition, application of QDs to charge transporting layers is introduced and the resultant changes in device performance and stability are pointed out. The insights gained from this review are very crucial for the further advancement of PSCs treated with QDs.

Designing of Business Performance Measurement Instruments of Notify Coffee With Balanced Scorecard

SMEs are one of the sectors that provide many job opportunities in Indonesia. SME Coffee Shop is one of the SME sub-sectors that is experiencing growth in Indonesia. A performance improvement strategy is needed to maximize the performance of SMEs Coffee Shop in order to compete and develop the business. This paper aims to identify the aligment of the SMEs vision, mission, goals and target, create a strategy map, identify Key Performance Indicator, and develop business used Balanced Scorecard method of Notif Coffee. The object of this research is Notif Coffee which is one of Coffee Shop SMEs in West Java. This study used are primary data obtained by structured interview with Notif Coffee owner and secondary data in the form of literature studies. The data processing and analysis method is carried by Key Performance Indicator and Balanced Scorecard consisting four targets, namely finance, learning and growth, internal business, and customer. The research shows that Notif Coffee have many problem in internal business perspective because Key Performance Indicator shows that target is not achived. The result of this research using balanced scorecard analysis with four perspectives led by the learning and growth, followed by the customer perspective, the financial perspective, and internal perspective.

Latest Performance Improvement Strategies and Techniques Used in 5G Antenna Designing Technology, a Comprehensive Study.

In the recent era, fifth-generation technology (5G) has not been fully implemented in the realm of wireless communication. To have excellent accessible bandwidth feasibility, and in order to achieve the aims of 5G standards, such as higher data rates and ultrahigh-definition video streaming, the millimeter wave (mmWave) band must be employed. Services with minimal latency and many other features are feasible only in the mmWave spectrum. To avoid numerous communication complexities such as high connection losses, short wavelength, and restricted bandwidth, as well as path-loss challenges in the mmWave range, an antenna with wide bandwidth, high gain, narrow steerable beam, high isolation, low side-lobe levels, and multiband features is required to alleviate these difficulties and meet 5G communication standards. To overcome these challenges, specific strategies and techniques should be employed in the traditional antenna designing procedure to excellently improve the performance of the antenna in terms of bandwidth, gain, and efficiency and to reduce the mutual coupling effect between the closely colocated antenna elements in MIMOs and arrays. The researchers reported on a variety of bandwidth and gain improvement approaches. To gain broader coverage, traditional antenna design techniques must be modified. In this study, the latest state-of-the-art work is reviewed, such as the role of the metamaterials (MMTs), parasitic patches, hybrid feeding, EBG structure, impact of the slots with different geometrical shapes in the radiator to achieve the goal of wide bandwidth, boosted gain, reduced side-lobes level, as well as stable radiation properties. Mutual coupling reduction techniques are also briefly reported. The role of reconfigurability is focused on in this study, and at the end, the future challenges in the field of antenna design and possible remedies to such issues are reviewed.

A Performance Improvement Strategy for Concrete Damage Detection Using Stacking Ensemble Learning of Multiple Semantic Segmentation Networks.

Semantic segmentation network-based methods can detect concrete damage at the pixel level. However, the performance of a single semantic segmentation network is often limited. To improve the concrete damage detection performance of a semantic segmentation network, a stacking ensemble learning-based concrete crack detection method using multiple semantic segmentation networks is proposed. To realize this method, a database including 500 images and their labels with concrete crack and spalling is built and divided into training and testing sets. At first, the training and prediction of five semantic segmentation networks (FCN-8s, SegNet, U-Net, PSPNet and DeepLabv3+) are respectively implemented on the built training set according to a five-fold cross-validation principle, where 80% of the training images are used in the training process, and 20% training images are reserved. Then, in predicting the results of reserved training images from trained semantic segmentation networks, the class labels of all pixels are collected, and then four softmax regression-based ensemble learning models are trained using the collected class labels and their true classification labels. The trained ensemble learning models are applied to regressed testing results of semantic segmentation network models. Compared with the best single semantic segmentation network, the best ensemble learning model provides performance improvement of 0.21% PA, 0.54% MPA, 3.66% MIoU, and 0.12% FWIoU, respectively. The study results show that the stacking ensemble learning strategy can indeed improve concrete damage detection performance through ensemble learning of multiple semantic segmentation networks.

Anionic formulation of electrolyte additive towards stable electrocatalytic oxygen evolution in seawater splitting

Hydrogen generation through seawater electrolysis provides a promising, attractive pathway towards the utilization of sustainable energy. However, the catalytic activity and stability of oxygen evolution anode are severely limited by the chloride-induced corrosion and competitive oxidation reactions. In this work, we demonstrate an anion-assisted performance improvement strategy by quick and universal screening of electrolyte additive via correlating Cl− repellency with the anionic properties. Particularly, the addition of phosphate ions is found to enable highly stable alkaline seawater splitting at industry-level current density (0.5 A cm−2) over 500 h using transition metal hydroxides as anodic electrocatalysts. In situ experiments and theoretical simulations further reveal that the dynamic anti-corrosion behaviors of surface-adsorbed phosphate ions are attributed to three factors including repelling Cl− ions without significantly blocking OH− diffusion, preventing transition metal dissolution and acting as a local pH buffer to compensate the fast OH− consumption under high current electrolysis.

Recent advances in regenerative biomaterials.

Nowadays, biomaterials have evolved from the inert supports or functional substitutes to the bioactive materials able to trigger or promote the regenerative potential of tissues. The interdisciplinary progress has broadened the definition of 'biomaterials', and a typical new insight is the concept of tissue induction biomaterials. The term 'regenerative biomaterials' and thus the contents of this article are relevant to yet beyond tissue induction biomaterials. This review summarizes the recent progress of medical materials including metals, ceramics, hydrogels, other polymers and bio-derived materials. As the application aspects are concerned, this article introduces regenerative biomaterials for bone and cartilage regeneration, cardiovascular repair, 3D bioprinting, wound healing and medical cosmetology. Cell-biomaterial interactions are highlighted. Since the global pandemic of coronavirus disease 2019, the review particularly mentions biomaterials for public health emergency. In the last section, perspectives are suggested: (i) creation of new materials is the source of innovation; (ii) modification of existing materials is an effective strategy for performance improvement; (iii) biomaterial degradation and tissue regeneration are required to be harmonious with each other; (iv) host responses can significantly influence the clinical outcomes; (v) the long-term outcomes should be paid more attention to; (vi) the noninvasive approaches for monitoring in vivo dynamic evolution are required to be developed; (vii) public health emergencies call for more research and development of biomaterials; and (viii) clinical translation needs to be pushed forward in a full-chain way. In the future, more new insights are expected to be shed into the brilliant field-regenerative biomaterials.

Symmetrically Fluorinated Benzo[1,2-b:4,5-b']dithiophene-Cored Donor for High-Performance All-Small-Molecule Organic Solar Cells with Improved Active Layer Morphology and Crystallinity.

Side-chain engineering is an efficient molecular design strategy for morphology optimization and performance improvement of organic solar cells (OSCs). Herein, a novel small-molecule donor C-2F, which owns a benzo[1,2-b:4,5-b']dithiophene (BDT) central unit with a symmetrically difluorinated benzene ring as a conjugated side chain, has been synthesized. The conjugated side chain possesses both the symmetry and halogenation effect in novel small molecular donor material. The photovoltaic devices were fabricated with N3 as an acceptor. C-2F:N3 based devices achieved an outstanding power conversion efficiency of 14.64% with a Jsc of 24.87 mA/cm2, a Voc of 0.85 V, and an FF of 69.33%. Then, we investigated the basic material properties, photovoltaic mechanism, and active layer morphology, and the results show that this molecular design strategy of the symmetrically difluorinated moiety as the conjugated side chain provides an effective method for fine-tuning the molecular stacking pattern and active layer phase separation morphology, to improve the all-small-molecule (ASM) OSCs' performances.

Adaptation and validation of the patient assessment of chronic illness care in United States community pharmacies

BackgroundRoles for United States (US)-based community pharmacists in caring for persons with chronic conditions have greatly expanded. The Patient Assessment of Chronic Illness Care (PACIC) was developed to assess patients’ perspectives of care received. However, successful application of this instrument in community pharmacies is uncertain. The objective of this study was to adapt the PACIC for use in community pharmacies (CP-PACIC), assess validity of the CP-PACIC and examine CP-PACIC scale score differences relative to patient characteristics.MethodsThis cross-sectional study surveyed chronically ill adults in Indiana, US who receive care from pharmacists in community pharmacies. The modified CP-PACIC scale consisted of 20-items, which were rated on a 5-point Likert scale from 0 (none of the time) to 4 (always). The total possible score ranged from 0 – 80. An exploratory factor analysis (EFA) was conducted to assess performance and dimensionality. CP-PACIC validity, including face validity, construct validity (via exploratory factor analysis) and internal consistency were assessed. Relationships between patient characteristics and scale scores were evaluated using appropriate statistical tests.ResultsFive hundred forty-six respondents’ data were analyzed. EFA revealed a 2-factor solution (termed advanced pharmacy chronic illness care (AP) and traditional pharmacy chronic illness care (TP) subscales) accounting for 64.7% of variance; all 20 items were retained. The total 20-item CP-PACIC scale had a Cronbach’s alpha (internal consistency) of 0.96; with a 12-item AP subscale Cronbach’s alpha of 0.97 and 8-item TP subscale Cronbach’s alpha of 0.89. Median total score was 12.0 [interquartile range = 27.3]. Median CP-PACIC sores varied across many respondent demographics (i.e., survey administration type, age, sex, education, health condition, number of pharmacy services received, community pharmacy type) such as whether respondents participated in one or more pharmacy service or not (29 vs. 10; p < .001).ConclusionsUnlike the original 5-subscale (patient activation, delivery system design, goal setting, problem solving, and follow-up/coordination) PACIC, analysis demonstrated a 2-factor (AP, TP) solution for the CP-PACIC scale with good internal consistency. As there are no standardized evaluation tools that exist, community pharmacies could find great value in using this CP-PACIC tool to benchmark performance and inform quality improvement strategies for patient care delivery.

Structures, Properties, and Device Applications for [1]Benzothieno[3,2‐b]Benzothiophene Derivatives

Abstract[1]benzothieno[3,2‐b]benzothiophene (BTBT), with two benzene rings as the outermost rings, is referred to as diacene‐fused ladder‐type π‐conjugated thienothiophenes. During the last three decades, derivatives based on BTBT core have been extensively studied due to their tremendous application prospects in organic field‐effect transistors (OFETs) and organic optoelectronic devices. In order to further advance the development of organic electronics, new materials are constantly being synthesized and new methods are constantly evolving. This review mainly focuses on the crystal and electronic structures of BTBT derivatives, the soluble and thermal properties, the fabrication methods, as well as the strategies for performance improvement and optoelectronic applications including OFETs, photodetectors, synaptic devices, and organic light‐emitting transistors. As one of the most promising organic materials, the insight into BTBT‐based molecules will accelerate their potential application and provide important reference value for the development toward commercialized and industrialized organic semiconducting products.

Increasing Compliance of Deep Vein Thrombosis Medical Prophylaxis in Acute Inpatient Rehabilitation Setting.

To improve medication reconciliation and decrease the rate of deep vein thrombosis (DVT) after the transfer of brain-injured neurologically impaired patients from an acute hospital setting to an inpatient rehabilitation facility, a performance improvement strategy was put in place. Such a strategy consisted of adding the proper DVT prophylaxis medication and dosage in the preadmission screen to prevent a delay in receiving the appropriate medication. This resulted in a dramatic reduction of inappropriately discontinued medications from 14.2% of patients to 5.78% over six months (p-value: 0.03). However, after the intervention, we surprisingly observed an increased rate of DVT from 6.2% to 10.11% (p-value: 0.03). This increase may be attributable to a larger number of venous duplex studies performed because of increased awareness of venous thromboembolism (VTE).

Figure of Merit for CRISPR-Based Nucleic Acid-Sensing Systems: Improvement Strategies and Performance Comparison.

Clustered regularly interspaced short palindromic repeats (CRISPR)-based nucleic acid-sensing systems have grown rapidly in the past few years. Nevertheless, an objective approach to benchmark the performances of different CRISPR sensing systems is lacking due to the heterogeneous experimental setup. Here, we developed a quantitative CRISPR sensing figure of merit (FOM) to compare different CRISPR methods and explore performance improvement strategies. The CRISPR sensing FOM is defined as the product of the limit of detection (LOD) and the associated CRISPR reaction time (T). A smaller FOM means that the method can detect smaller target quantities faster. We found that there is a tradeoff between the LOD of the assay and the required reaction time. With the proposed CRISPR sensing FOM, we evaluated five strategies to improve the CRISPR-based sensing: preamplification, enzymes of higher catalytic efficiency, multiple crRNAs, digitalization, and sensitive readout systems. We benchmarked the FOM performances of 57 existing studies and found that the effectiveness of these strategies on improving the FOM is consistent with the model prediction. In particular, we found that digitalization is the most promising amplification-free method for achieving comparable FOM performances (∼1 fM·min) as those using preamplification. The findings here would have broad implications for further optimization of the CRISPR-based sensing.

MILP performance improvement strategies for short-term batch production scheduling: a chemical industry use case

This paper presents the development and mathematical implementation of a production scheduling model utilizing mixed-integer linear programming (MILP). A simplified model of a real-world multi-product batch plant constitutes the basis. The paper shows practical extensions to the model, resulting in a digital twin of the plant. Apart from sequential arrangement, the final model contains maintenance periods, campaign planning and storage constraints to a limited extend. To tackle weak computational performance and missing model features, a condensed mathematical formulation is introduced at first. After stating that these measures do not suffice for applicability in a restrained time period, a novel solution strategy is proposed. The overall non-iterative algorithm comprises a multi-step decomposition approach, which starts with a reduced scope and incrementally complements the schedule in multiple subproblem stages. Each of those optimizations holds less decision variables and makes use of warmstart information obtained from the predecessor model. That way, a first feasible solution accelerates the subsequent improvement process. Furthermore, the optimization focus can be shifted beneficially leveraging the Gurobi solver parameters. Findings suggest that correlation may exist between certain characteristics of the scheduling scope and ideal parameter settings, which yield potential for further investigation. Another promising area for future research addresses the concurrent multi-processing of independent MILPs on a single machine. First observations indicate that significant performance gains can be achieved in some cases, though sound dependencies were not discovered yet.

Metal sulfides based composites as promising efficient microwave absorption materials: A review

• The present synthetic methods of metal sulfides are provided. • The development of metal sulfides based composites for microwave absorption is reviewed. • The influence of structure regulations and materials hybridizations on microwave absorption properties are discussed. The increasingly severe electromagnetic microwave pollution raises higher requirements for the development of efficient microwave absorption (MA) materials. Metal sulfides are regarded as potential robust MA materials because of their unique optical, thermal, electrical, and magnetic properties, as well as the controllable microstructures. However, due to the limited MA performances of unary metal sulfides, morphology regulations and foreign materials hybridizations are adopted as effective strategies to improve their MA performances. Recent years witnessed the fast research progresses on the metal sulfides based MA materials and thus, a systematic literature survey on the materials design, fabrication, characterizations, MA behaviors, and the mechanisms behind is, highly desirable to summarize the rapid progress of this hot research area so as to provide guidance for the future development trend. This review firstly reviewed the research background, research progress, and basic principles of MA materials. Subsequently, the present synthetic methods and performance improvement strategies of metal sulfides based MA materials are systematically introduced. Then, by comparing the MA properties of one-dimensional, two-dimensional, and three-dimensional metal sulfides based composites, the influence of dimensionality and morphology on the MA properties are analyzed. By summarizing the research process of metal sulfides/dielectrics composites, metal sulfides/magnets composites, and metal sulfides/dielectrics/magnets composites MA materials, the influence of foreign materials hybridizations on the loss mechanisms and impedance matching conditions of metal sulfides based composites are revealed. Finally, the challenges and development prospects of metal sulfides based MA materials are presented. This review would provide a comprehensive understanding and insightful guidance for the exploration and development of efficient MA materials with thin thickness, light weight, wide absorption bandwidth, and strong absorption intensity.

MXene-Based Electrodes for Supercapacitor Energy Storage

MXenes, a new class of two-dimensional advanced functional nanomaterials, have been widely researched in the past decade for applications in diverse fields including clean energy and fuels production. The unique layered structures of MXenes simultaneously enhance electrolyte ion transport and provide transition metal active redox sites on the surface. These features make MXenes particularly promising for applications as high-performance electrodes for electrochemical capacitors (supercapacitors). This paper critically reviews the latest advancements in the utilization of MXenes in supercapacitor electrodes. The key structural features and other properties of MXenes that make them ideal for supercapacitor electrodes, including strategies for fabrication, performance improvement, and scalable manufacture of industry-relevant MXene films, are elaborated. Future research needs, challenges, and opportunities in this rapidly emerging area are discussed as well.

The Strategy of Improving the Performance of Cooperatives in the Review of Organizational Culture, Innovation is Mediated by the Entrepreneurial Orientation in Surabaya

Purpose: The aim of research to proved and analyzed strategy to improve cooperative performance through organizational culture, innovation in mediation with entrepreneurship orientation in surabaya city.&#x0D; Design/methodology/approach: The type of this research was surveying research and the data from questionnaire will be as primer data.&#x0D; Findings: The results showed that organizational culture positive and significant effect against the entrepreneurial orientation, innovation is a positive and significant effect against the entrepreneurial orientation, organizational culture positive and significant effect performance improvement strategies towards cooperative, positive effect not significant innovation strategy improved performance of cooperatives, entrepreneurial orientation effect positive and significant performance improvement strategies against the cooperative.&#x0D; Research limitations/implications: The data collected were declared valid and reliable, then processed for analysis using structural equation model or Structural Equation Modeling (SEM).&#x0D; Practical implications: The population study for this research was all primary cooperatives in Surabaya with total 400 cooperatives that have the following characteristics: (a) has a member of a minimum of 100 people, (b) active of operations and implement RAT for 3 years successively, (c) has more than two business units (d) and has assets of over 1 billion rupiah. The sample for this research was 138 primary cooperation.&#x0D; Originality/value: This paper is original&#x0D; Paper type: Literature review

Quality of nursing care in Saudi's healthcare transformation era: A nursing perspective.

The Kingdom of Saudi Arabia corporates performance improvement strategies in health sector to transform hospital operations and instituting a culture of quality through performance improvement initiatives. Quality of nursing care (QNC) is a concern for nursing professionals and administration. Donabedian's 'Quality-of-Care' framework plays a vital role in transforming nursing care and determining appropriate intervention development and implementation plans. To explore the nurses' perception for the QNC and find their perspectives in achievements and gaps by adopting the Donabedian model. A cross-sectional study was conducted on a convenience sample of 639 nurses from a tertiary hospital in Saudi Arabia using Karen-personnel instrument for measuring QNC. The achievements and gaps in nursing care quality determined by redistributing Karen statements to the three dimensions of the Donabedian structure, process and outcome model. The nurses' overall perception of the QNC was positive. According to the Donabedian model, the nurses focussed on care procedures (i.e., process-oriented) and required resources (i.e., structure-oriented), although the transformation era requires nurses' performance to focus on the outcome dimension. To activate the vital roles of nurses in accomplishing health transformation initiatives, there should be collaborative efforts among nursing managers, educators and policy-makers to sustain quality of structure, process and outcome-oriented nursing care and be more outcome-oriented.

Self-Supervised Depth Estimation Leveraging Global Perception and Geometric Smoothness

Self-supervised depth estimation has drawn much attention in recent years as it does not require labeled data but image sequences. Moreover, it can be conveniently used in various applications, such as autonomous driving, robotics, realistic navigation, and smart cities. However, extracting global contextual information from images and predicting a geometrically natural depth map remain challenging. In this paper, we present DLNet for pixel-wise depth estimation, which simultaneously extracts global and local features with the aid of our depth Linformer block. This block consists of the Linformer and innovative soft split multi-layer perceptron blocks. Moreover, a three-dimensional geometry smoothness loss is proposed to predict a geometrically natural depth map by imposing the second-order smoothness constraint on the predicted three-dimensional point clouds, thereby realizing improved performance as a byproduct. Finally, we explore the multi-scale prediction strategy and propose the maximum margin dual-scale prediction strategy for further performance improvement. In experiments on the KITTI and Make3D benchmarks, the proposed DLNet achieves performance competitive to those of the state-of-the-art methods, reducing time and space complexities by more than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$62\%$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$56\%$</tex-math> </inline-formula> at a resolution of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$416 \times 128$</tex-math> </inline-formula> , respectively. Extensive testing on various real-world situations further demonstrates the strong practicality and generalization capability of the proposed model.