Cost-effective Path Research Articles

Laser powder bed fusion of high-strength crack-free Al7075 alloy with the in-situ formation of TiB2/Al3Ti-reinforced phases and nucleation agents

The existence of solidification cracks caused by columnar grains in precipitation-hardened aluminium alloys limit the applicability of Al7075 components manufactured via laser powder bed fusion (LPBF) additive manufacturing. A novel approach was developed to co-incorporate submicron-sized B and micron-grade Ti6Al4V to eliminate hot cracks and to effectively transform coarse columnar grains into fine equiaxed grains, thus improving the mechanical performance of LPBF-fabricated modified Al7075 material. The grain refinement was mainly attributable to the heterogeneous nucleation promoted by the combination of in-situ-formed L12-Al3Ti and TiB2 nano-sized phases. After an optimised T6 heat treatment, excellent comprehensive mechanical properties were achieved, with a tensile strength of 460 MPa and an elongation of 13 %. This research provides an efficient and cost-effective path for addressing crack-sensitive metallic materials used for LPBF additive manufacturing processes.

From Deworming to Cancer Therapy: Benzimidazoles in Hematological Malignancies.

Drug repurposing is a strategy to discover new therapeutic uses for existing drugs, which have well-established toxicity profiles and are often more affordable. This approach has gained significant attention in recent years due to the high costs and low success rates associated with traditional drug development. Drug repositioning offers a more time- and cost-effective path for identifying new treatments. Several FDA-approved non-chemotherapy drugs have been investigated for their anticancer potential. Among these, anthelmintic benzimidazoles (such as albendazole, mebendazole, and flubendazole) have garnered interest due to their effects on microtubules and oncogenic signaling pathways. Blood cancers, which frequently develop resistance and have high mortality rates, present a critical need for effective therapies. This review highlights the recent advances in repurposing benzimidazoles for blood malignancies. These compounds induce cell cycle arrest, differentiation, tubulin depolymerization, loss of heterozygosity, proteasomal degradation, and inhibit oncogenic signaling to exert their anticancer effects. We also discuss current limitations and strategies to overcome them, emphasizing the potential of combining benzimidazoles with standard therapies for improved treatment of hematological cancers.

Promoting proximity to enhance Fe-Ca interaction for efficient integrated CO2 capture and hydrogenation

Integrated CO2 capture and utilization (ICCU) using “capture-conversion” dual functional materials (DFMs) paves a cost-effective path for restricting CO2 emissions by eliminating the energy-intensive intermediate processes. The interactions between catalysts and absorbents are believed pivotal in ICCU; however, there is a lack of environment-friendly strategy to fabricate the interaction for industrial applications. Here, we propose a solvent-free mechanochemical approach to promote the interaction by improving the proximity between natural calcium and iron sources. The interaction was systemically investigated and confirmed using XRD, XPS, TEM, TPR, etc. As a result, the mechanochemical approach derived DFM achieved 5.5 mmol/g CO2 capacity, 87 % CO2 conversion, and 100 % CO selectivity at 650 °C, significantly outperforming the CaO-alone benchmark (CO2 capacity < 4.5mmol/g, CO2 conversion < 73 %). Further incorporating MgO would alleviate the sintering and promote the CO2 capture stability (< 15 % decrease after 20 cycles) by acting as a thermal-stable barrier. Based on in situ XRD, it is further confirmed that Fe-Ca interaction exhibits a dynamic looping mechanism in ICCU. The techno-economic analysis strongly supports the superiority of ICCU catalyzed by naturally sourced DFMs on eliminating the energy and H2 consumption for CO2 capture and upgradation. As a result, producing CO via ICCU using mechanochemical derived DFMs exhibits 20 % and 10 % cost decrease compared to the conventional CCU and ICCU using CaO alone scenarios, pointing out the potential of ICCU technology in industrial applications.

Large-area superconducting nanowire arrays fabricated by nano laser direct writing

We report on the fabrication, structural, and electrical transport characterizations of superconducting nanowire arrays based on nano-laser direct writing (NLDW). The thermal excitation-induced micro/nano fabrication based on the interactions between NLDW and superconducting Nb films was experimentally analyzed and simulated. Experimentally, the arrays of superconducting nanowires have an area of 190 × 190 μm2 with a critical transition temperature Tc of 7.8 K and a critical current density Jc of 20.8 MA cm−2 at 4.0 K. The width and arrangement of the nanowires are precisely controlled, exhibiting a minimal loss of 0.6 K in Tc and excellent Jc after LDW. The width of superconducting nanowires could be further optimized by adjusting parameters such as laser power, irradiation gap, and delay of points. Compared with electron beam lithography and focused ion beam, to some extent, the nanowires fabrication process based on NLDW provides a more efficient and cost-effective path for fabricating large-area superconducting circuits and devices.

A robust cis-Mendelian randomization method with application to drug target discovery

Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on a single genomic region using only cis-SNPs. For example, using cis-pQTLs for a protein as exposure for a disease opens a cost-effective path for drug target discovery. However, few methods effectively handle pleiotropy and linkage disequilibrium (LD) of cis-SNPs. Here, we propose cisMR-cML, a method based on constrained maximum likelihood, robust to IV assumption violations with strong theoretical support. We further clarify the severe but largely neglected consequences of the current practice of modeling marginal, instead of conditional genetic effects, and only using exposure-associated SNPs in cis-MR analysis. Numerical studies demonstrated our method’s superiority over other existing methods. In a drug-target analysis for coronary artery disease (CAD), including a proteome-wide application, we identified three potential drug targets, PCSK9, COLEC11 and FGFR1 for CAD.

Cost Bearing of Individual Project due to Use of Modern Software in Project Management and Detailed Analysis of Same for Making Cost Effective Path

Abstract: Project management in India is witnessing impact of IT Development on its core field. Particularly in India project management had undergone lot of changes. Post industrialisation era demand of skilled project management had reached a statutory requirement. Introduction of RERA enforced private developer and builders to develop the project in stipulated time. The requirement of quick update, organised effort, errorless drawing and documentations, integrated approach demanded use of IT infrastructure alike other Field. As per the other infrastructure Cost of modern use of Software’s demanded Financial Planning and Consideration for Annual basis. The study aims at study of IT infrastructure required for individual project. To list out strategies to control this cost and make a cost-effective way.

Multi-objective optimisation model of a low-cost path to peaking carbon dioxide emissions and carbon neutrality in China

A low-cost path system for achieving carbon neutrality in China was modelled using multi-objective programming by integrating industrial production, electric power, heating, transportation, and forest carbon sequestration. We aimed to minimise the total system cost, CO2 emissions, and air pollutants. The constraints included China's targets of peaking CO2 emissions before 2030; achieving carbon neutrality before 2060; ensuring industry, power, heating, and transportation supplies; promoting green energy; and implementing emission control. The model accounted for industries with high coal consumption, such as steel and chemical industries. Various power sources were considered, including coal-fired, nuclear, wind, and solar energy. Forest carbon sink and carbon capture and storage technologies were employed to achieve the emission reduction goals. The model, which was validated using available research data, offered cost-effective path schemes and exhibited high validity. Our findings emphasise the importance of structural adjustments and emission control, with electric power, heating, and transportation sectors showing higher feasibility and providing greater contributions to achieving carbon neutrality than other industries. Conversely, industrial transformation in sectors such as iron and steel, chemical, and construction materials had low feasibility and limited contribution. The modelling outcomes provide valuable insights for developing low-cost, carbon emission-targeted transportation structures in China's complex system. The results presented here demonstrate the global applicability of this method in contributing to plans aimed at meeting key carbon reduction targets.

Surface Defect Engineering on Constructing High-Performance Noble Metal Active Sites: A Simple and Cost-Effective Path to High-Performance Oxidation Catalysts

Surface Defect Engineering on Constructing High-Performance Noble Metal Active Sites: A Simple and Cost-Effective Path to High-Performance Oxidation Catalysts

Homodyne-detection-based discrete-variable quantum key distribution with a heralded single-photon source

Discrete-variable quantum key distribution (DV-QKD) has recently been implemented using a homodyne detection system, and a notable secret key rate can be achieved by employing an ideal single-photon source. However, most QKD implementations employ practical light sources, including a phase-randomized weak coherent source and a heralded single-photon source, which occasionally produce multiphotons and are vulnerable to photon-number-splitting (PNS) attacks. In this work, we propose a three-decoy-state method using a heralded single-photon source for homodyne-detection-based DV-QKD, thus making it immune to PNS attacks with current technology. Our simulation results demonstrate that our proposed protocol can achieve high-speed and secure key distribution over metropolitan distances. Our work paves a cost-effective path to realize DV-QKD and further incorporate it into classical telecommunication networks.

An Effective Method for Computing the Least-Cost Path Using a Multi-Resolution Raster Cost Surface Model

Calculating the least-cost path (LCP) is a fundamental operation in raster-based geographic information systems (GIS). The LCP is applied to raster cost surfaces, in which it determines the most cost-effective path. Increasing the raster resolution results in a longer computation time to obtain LCP. This paper proposes a method for calculating the LCP using a multi-resolution raster cost surface model to enhance computational performance for large-scale grids. The original raster cost surface is progressively downsampled to generate grids of decreasing resolutions. Subsequently, the path is determined on the low-resolution raster. By performing operations such as filtering directional points and mapping path points, the final path on the high-resolution raster can be obtained. The method enables a parallel computation of paths. Therefore, it significantly improves the efficiency for synthetic raster cost surfaces with continuous or discrete characteristics, as well as for raster cost surfaces generated from real terrain datasets, while also providing an end-to-end path output. The experiments show that 80% of the results are very close to the original LCP, and the accuracy of the remaining paths falls within an acceptable range. At the same time, our method greatly improves the efficiency of path solving on a large-scale raster, fulfilling practical application requirements.

Two-layer management of HVAC-based Multi-energy buildings under proactive demand response of Fast/Slow-charging EVs

Building heating, ventilation, and air conditioning (HVAC) and associated energy consumption make up the more and more important part of the world, whose reduction provides a cost-effective path to the “dual carbon” goal. This paper proposes a two-layer management of HVAC-based multi-energy buildings under proactive demand response of fast/slow-charging electric vehicles (EVs). In this paper, the building HVAC is mathematically formulated via a R-C thermodynamic model, which coordinates with multi-energy converters and storages to form a 100% renewable building. The building management is a challenging optimization problem due to its severe constraints and strong spatio-temporal couplings. In the first layer, a day-ahead multi-energy dispatch is formulated to economically optimize the electrical, heat, gas energy carriers. In the second layer, alternating current (AC) slow charging and direct current (DC) fast charging types of EVs are considered and managed via a novel real-time supply–demand pricing mechanism. After acquiring the economical dispatch references in the first layer, the second layer implements a model predictive control (MPC)-based real-time scheduling to handle the multi-energy supply–demand fluctuations. The original two-layer optimization is further handled via mixed-integer linear program (MILP) reformulation for high-efficient solving. Comparisons have shown the advantageous performances of the proposed two-layer optimization over economics and practicability. Simulations results show that the overall system operating cost can be reduced by at most 3.01% with a higher operational flexibility in building management.

Do globalization and nuclear energy intensify the environmental costs in top nuclear energy-consuming countries?

Nuclear energy is considered an effective alternative to ensure global energy safety, and it has recently started to be promoted as a climate change mitigation solution to achieve low-carbon energy transition targets. Considering this view, this study aims to assess the environmental cost reduction by using nuclear energy efficiency and technological innovation from the prospects of the globalization process. Therefore, the relationship among carbon emissions, nuclear energy, globalization, and technological innovation was assessed in the top ten nuclear energy-consuming countries from 1990 to 2017 while controlling for economic growth and renewable energy. This study applied Common Correlated Effects Mean Group (CCEMG), Augmented Mean Group (AMG), and Dumitrescu-Hurlin causality techniques for model estimation that solves the problem of cross-sectional dependence and slope heterogeneity. The empirical results indicated that nuclear energy and technological innovation diminish environmental costs by reducing carbon emissions. However, globalization increases environmental costs by releasing more carbon emissions into the atmosphere. Moreover, bidirectional causality exists among nuclear energy, renewable energy, and carbon emissions. Consequently, the highest nuclear energy-consuming countries must utilize nuclear energy efficiency to control environmental costs and a cost-effective path to a low-carbon economy. Finally, this perspective intended to appeal to policymakers to do a better job of substantiating their decisions.

Study of Urban Logistics Drone Path Planning Model Incorporating Service Benefit and Risk Cost

The application of drones provides a powerful solution for “the last-mile” logistics services, while the large-scale implementation of logistics drone services will threaten the safety of buildings, pedestrians, vehicles, and other elements in the urban environment. The balance of risk cost and service benefit is accordingly crucial to managing logistics drones. In this study, we proposed a cost-benefit assessment model for quantifying risk cost and service benefit in the urban environment. In addition, a global heuristic path search rule was developed to solve the path planning problem based on risk mitigation and customer service. The cost-benefit assessment model quantifies the risk cost from three environmental elements (buildings, pedestrians, and vehicles) threatened by drone operations based on the collision probability, and the service benefit based on the characteristics of logistics service customers. To explore the effectiveness of the model in this paper, we simulate and analyse the effects of different risk combinations, unknown risk zones, and risk-benefit preferences on the path planning results. The results show that compared with the traditional shortest-distance method, the drone path planning method proposed in this paper can accurately capture the distribution of risks and customers in the urban environment. It is highly reusable in ensuring service benefits while reducing risk costs and generating a cost-effective path for logistics drones. We also compare the algorithm in this paper with the A* algorithm and verify that our algorithm improves the solution quality in complex environments.

Scalable detection of technically challenging variants through modified next-generation sequencing.

Some clinically important genetic variants are not easily evaluated with next-generation sequencing (NGS) methods due to technical challenges arising from high- similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly-T/TG repeats), and other complexities (e.g., MSH2 Boland inversions). We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes. Our adaptations provided high-sensitivity and high-specificity detection for most of the variants and provided a high-sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%-100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats. NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost-effective path to identifying all clinically relevant variants within a single sample.

Assessing bivalve growth using bio-energetic models

Aquaculture can play a key role in providing sustainable and low-cost protein sources, with the potential to help particularly the socially and economically vulnerable population. Although many coastal populations already complement their diet by extracting wild brown mussels (Perna perna, Mytilidae) from the environment, an explicit assessment for mussel growth potential along the Brazilian coast has been conspicuously lacking. We provide a large-scale assessment for prospecting and developing mussel culture by applying a Dynamic Energy Budget (DEB) model coupled with remote sensing. We estimated DEB parameters for the P. perna Brazilian population and used satellite-derived yearly data was used as forcing variables, containing information of chlorophyll-a concentration as a proxy for food concentration, sea-surface temperature to modulate metabolic performance, and particulate organic carbon - discounted the contribution of chlorophyll-a - to take into account the negative effect of particles in the mussel ingestion rates. We then simulated mussel growth along a large region of the Brazilian coast and obtained the time it takes for the mussel to reach a 5 cm market-relevant length within each pixel as a means to visualize mapped mussel growth potential indicating the time it takes to reach commercial length. Our results highlight the regions where mussel growth can be relevant for supporting subsistence livelihoods and also for securing income for local communities by performing economic activities, as many of the identified regions do not yet have active mussel culture sites. We also show that mussels can be used for ecosystem services in regions where farming for human consumption is not advisable. Our study provides further evidence that bioenergetic models coupled with remote sensing allow for a pragmatic and cost-effective path to assess growth performance along large regions with implications for developmental policy and spatial planning.

Identification of Anti-HIV Biomarkers of Helichrysum Species by NMR-Based Metabolomic Analysis.

Several species of the Helichrysum genus have been used ethnobotanically to treat conditions that we today know have been caused by viral infections. Since HIV is a modern disease with no ethnobotanical history, we commenced with a study on the anti-HIV activity of several Helichrysum species. Drug discovery of small molecules from natural resources that is based on the integration of chemical and biological activity by means of metabolomical analyses, enables faster and a more cost-effective path to identify active compounds without the need for a long process of bioassay-guided fractionation. This study used metabolomics to identify anti-HIV compounds as biomarkers from 57 Helichrysum species in a combined study of the chemical and biological data of two previous studies. In the OPLS-DA and hierarchical cluster analyses, anti-HIV activity data was included as a secondary observation, which assisted in the correlation of the phytochemical composition and biological activity of the samples. Clear grouping revealed similarity in chemical composition and bioactivity of the samples. Based on the biological activity of polar extracts, there was a distinct phytochemical difference between active and non-active groups of extracts. This NMR-based metabolomic investigation showed that the chlorogenic acids, compounds with cinnamoyl functional groups, and quinic acid were the most prominent compounds in the Helichrysum species with anti-HIV activity. This study further revealed that the chlorogenic acid type compounds and quinic acid are biomarkers for anti-HIV activity.

Navigating Chinese cities to achieve sustainable development goals by 2030

Achieving the 17 United Nations sustainable development goals (SDGs) in China largely depends on the transition of cities toward sustainable development. However, significant knowledge gaps exist in evaluating the SDG index at the city scale and in understanding how to simulate pathways to achieve the 17 SDGs for Chinese cities by 2030. This study aimed to quantify the SDG index of 285 Chinese cities and developed a forecasting model to simulate the performance of each SDG in each city until 2030 using varied scenarios. The results indicated that although the SDG index in Chinese cities increased by 33.97% during 2005–2016, Chinese cities, which continued their past paths, achieved an average of only five SDGs by 2030. To promote the joint achievement of all SDGs, we designed different paths for all SDGs of each of the 285 cities and simulated their SDG index until 2030. Under the scenarios, 216 Chinese cities (75.79%) could achieve 9–13 more SDGs in 2030 and the overall SDG index can improve from 74.57 in 2030 to 97.49 (target score 100) by adopting more intensive path adjustment. We lastly determined a cost-effective path for each SDG of each city to promote joint achievement of all SDGs by 2030. The proposed simulation model and cost-effective path serve as a foundation for other countries to simulate SDG progress and develop pathways for achieving SDGs in the future.

Research on technical support ability and collaborative planning algorithm in online examination

Starting from a typical online examination EBMG (Examination Behavior Model Graph), this paper obtains the relationship between the examination effectiveness index and the examinee scale through the probability data of the examiner’s examination response behavior, establishes the optimization model of the hardware structure by using the network maximum flow theory, and finds the relationship between the technical support ability and the examinee scale through the analysis of the model. Based on these two relationships, we find a collaborative planning algorithm, which transforms the relationship between the examinee scale and the technical support ability of the system under the same quality of service into the network flow diagram of online examination, and obtains the best cost-effective path of online examination system through the maximum flow algorithm.

Cycling Performance of NMC811 Anode-Free Pouch Cells with 65 Different Electrolyte Formulations

Liquid electrolytes for anode-free Li metal batteries (LMBs) provide a cost-effective path to high energy density. However, liquid electrolytes are challenging due to the reactivity of Li0 with the electrolyte and the resulting Li loss, as well as mossy Li deposits leading to inactive Li and dendrite formation. Thus, more research is needed to develop electrolytes capable of 80 % capacity retention after 800 cycles to meet electric vehicle (EV) demands. Here, we report cycle life results from 65 electrolyte mixtures consisting of various additives or co-solvents added to a dual-salt base electrolyte previously reported by our group. We tested these electrolyte systems using a practical anode-free pouch cell design with a high-loading (16 mg cm−2, or 3.47 mAh cm-2) LiNi0.8Mn0.1Co0.1O2 (NMC811) cathode, with a bare Cu foil as the counter electrode. All cells in this work were cycled at 40 °C with 0.2C/0.5C charge/discharge rates between 3.55–4.40 V. Based on the total energy delivered over 140 cycles, only four electrolytes showed marginal improvement over the baseline, while the other electrolytes were uncompetitive. This data set can serve as a guide for LMB researchers investigating electrolyte systems and highlights the challenges associated with liquid electrolytes.

Processing and microstructure-permeation properties of silica bonded silicon carbide ceramic membrane

Porous SiC is a valuable membrane material for the microfiltration and ultrafiltration of various wastewaters because of its high hydrophilicity and low fouling tendency, but its preparation has been limited by the high sintering temperature. Here, a silica bonded silicon carbide membrane was prepared by the oxidation of SiC at low temperature. When the SiC substrates were sintered in the temperature range from 1200 to 1400℃, their porosity decreased from 45 % to 37 % while the flexural strength increased from 45 to 59 MPa. For the selective layers made from SiC particles with 0.5 μm in diameter, the average pore sizes that sintered at 1050 and 1150 ℃ were 0.34 and 0.26 μm, respectively, corresponding to the water fluxes of 1080 and 1240 L/(m2 h, respectively. Thus, this technique provided a cost-effective path to prepare ceramic membrane at low sintering temperature.