Efficient Choice Research Articles

Node Localization Based on Unsupervised Approach and Secure Routing for Healthcare Management in Delay‐Tolerant Network

ABSTRACTThe ability of the current global healthcare system to continue providing high‐quality medical care has been questioned. By using delay‐tolerant networks (DTNs) in healthcare management, people that spend a lot of time treating illnesses are exposed to more people while also putting their lives in danger. Unsupervised approach‐based node localization and secure routing in DTNs are developed in the proposed method. The proposed adaptive density‐based localization algorithm is constructed in two modules. The entire network is clustered depending on density utilizing density‐based spatial clustering of applications with noise (DBSCAN). An RSA‐based location estimation algorithm is employed to identify the unlocalized node within each cluster. After finding the location of each node, routing mechanism is carried out. An adaptive spray and wait routing strategy is utilized in the proposed method. When a node only has one copy of a message, the spray and wait, routing mechanism moves the relay node while it waits for the destination to be countered. Then modified DNA encryption algorithm is applied for secure data transmission. It is used for encrypting the information before storing it in the network. The trusted center will generate the private key needed for encrypting the data based on the sensitivity level of the information. This proposed algorithm is tested with several metrics which attain better performance, like 94% localization accuracy, 6% localization error, average residual energy of 93%, 5.7 Mbps throughput, 18% encryption time, and 14% decryption time. Thus, the techniques used in the proposed approach are the best choice for node localization, energy efficiency, and secure data transmission in DTN.

Impact of Systematic Modeling Uncertainties on Kilonova Property Estimation

The precise atomic structure and therefore the wavelength-dependent opacities of lanthanides are highly uncertain. This uncertainty introduces systematic errors in modeling transients like kilonovae and estimating key properties such as mass, characteristic velocity, and heavy metal content. Here, we quantify how atomic data from across the literature as well as choices of thermalization efficiency of r-process radioactive decay heating impact the light curve and spectra of kilonovae. Specifically, we analyze the spectra of a grid of models produced by the radiative transfer code Sedona that span the expected range of kilonova properties to identify regions with the highest systematic uncertainty. Our findings indicate that differences in atomic data have a substantial impact on estimates of lanthanide mass fraction, spanning approximately 1 order of magnitude for lanthanide-rich ejecta, and demonstrate the difficulty in precisely measuring the lanthanide fraction in lanthanide-poor ejecta. Mass estimates vary typically by 25%–40% for differing atomic data. Similarly, the choice of thermalization efficiency can affect mass estimates by 20%–50%. Observational properties such as color and decay rate are highly model dependent. Velocity estimation, when fitting solely based on the light curve, can have a typical error of ∼100%. Atomic data of light r-process elements can strongly affect blue emission. Even for well-observed events like GW170817, the total lanthanide production estimated using different atomic data sets can vary by a factor of ∼6.

Spiking Neural Networks for Real-Time Pedestrian Street-Crossing Detection Using Dynamic Vision Sensors in Simulated Adverse Weather Conditions

This study explores the integration of Spiking Neural Networks (SNNs) with Dynamic Vision Sensors (DVSs) to enhance pedestrian street-crossing detection in adverse weather conditions—a critical challenge for autonomous vehicle systems. Utilizing the high temporal resolution and low latency of DVSs, which excel in dynamic, low-light, and high-contrast environments, this research evaluates the effectiveness of SNNs compared to traditional Convolutional Neural Networks (CNNs). The experimental setup involved a custom dataset from the CARLA simulator, designed to mimic real-world variability, including rain, fog, and varying lighting conditions. Additionally, the JAAD dataset was adopted to allow for evaluations using real-world data. The SNN models were optimized using Temporally Effective Batch Normalization (TEBN) and benchmarked against well-established deep learning models, concerning their accuracy, computational efficiency, and energy efficiency in complex weather conditions. This study also conducted a comprehensive analysis of energy consumption, highlighting the significant reduction in energy usage achieved by SNNs when processing DVS data. The results indicate that SNNs, when integrated with DVSs, not only reduce computational overhead but also dramatically lower energy consumption, making them a highly efficient choice for real-time applications in autonomous vehicles (AVs).

Study of Electron Beam Irradiated Palladium on Carbon Catalysts for Transfer Hydrogenation Reactions of Nitroarenes Compounds

Palladium-catalyzed hydrogenation is considered a crucial stage in the entire synthesis of difficult natural products as well as a crucial step in the manufacturing of fine compounds used in pharmaceuticals. When it comes to the reaction rate and simplicity of work-up, using Pd/C as heterogeneous catalyst is one of the best choice for process efficiency. In this study, nitroarenes compounds viz. 3-bromo nitrobenzene, 4-fluoro nitrobenzene, 3-methyl nitrobenzene, 4-hydroxy nitrobenzene reduced by using macro 10% Pd/C and micro 10% Pd/C to 3-bromo aniline, 4-fluoro aniline, 3-methyl aniline, 4-hydroxy aniline respectively and verified from 1H NMR studies. The reduction reactions were similar conditions using electron beam irradiated 250 kGy macro and micro 10% Pd/C catalyst. The effectiveness of commercial sources of palladium on carbon (Pd/C) varies widely, leading to the appreciable variations in the reaction times. The decrease in reaction time has been attributed to the higher dispersion of Pd particles upon irradiation. The physico-chemical characteristics of effective hydrogenation catalysts were determined to be: (i) small Pd particle size and (ii) homogeneous distribution of Pd on the carbon support. With no significant loss of catalytic activity, the electron beam-irradiated catalyst can be used again for five runs. These days, chemists can determine as well as forecast the effectiveness of catalysts before investing time and money in expensive synthetic materials.

Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers

The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry.

Neoliberalism and the Complexities of Conceptualizing Community School Policy for Racial Equity

Full-service community schools are increasingly adopted as educational policy nationwide to transform educational institutions into community hubs, addressing racial and social disparities and countering deficit narratives related to marginalized youth and families. As the movement toward community schooling as an educational policy gains momentum, more research is needed to understand the complex process of conceptualizing such an initiative for racial equity. Spanning from the early planning stages to 3 years into the implementation of community schooling, this paper uncovers the tensions that emerge as school and district leaderships’ interpretation of the purpose of community schooling and root cause of racial inequity unveil conflicting conceptualizations of the community school initiative: community schooling rooted in neoliberal ideals of efficiency, coordination, and service choice, on one hand, and those rooted in more transformative approach with systemic reflection and change in classrooms, schools, and other institutions on the other.

Economic evaluation of acupuncture in treating patients with pain and mental health concerns: the results of the Alberta Complementary Health Integration Project.

The COVID-19 pandemic and its economic impact have heightened the risk of mental health and pain-related issues. The integration of acupuncture with conventional medicine shows promise in improving treatment outcomes for these conditions. The Alberta Complementary Health Integration Project (ABCHIP) aimed to provide acupuncture to youth (aged 24 and under) and seniors (aged 55 and above) experiencing chronic pain, pain management issues, mental health issues, and/or related conditions. The program aimed to promote integrative care, assess the effectiveness and cost-effectiveness of these therapies, and deliver patient-centered care. ABCHIP provided acupuncture to address pain, mental health, and addiction issues at no cost to two vulnerable populations in Alberta: youth and the older adult. A total of 606 patients aged 14-65 received 5,424 acupuncture treatments. Outcome measures included pain interference, pain severity, sleep quality, depression, anxiety, fatigue, anger, and quality of life. Short-term outcomes were assessed through questionnaires completed at the beginning and completion of the treatments, while long-term benefits were estimated using these outcome indicators and existing literature on the economic cost of illnesses. The cost-effectiveness analysis revealed the following ratios per Quality-Adjusted Life Year (QALY): CND12,171 for the overall sample, CND10,766 for patients with pain, CND9,331 for individuals with depression, and CND9,030 for those with anxiety. The cost-benefit analysis demonstrated annual cost savings ranging from CND1,487 to CND5,255, with an average of CND3,371. The study findings indicate that ABCHIP's treatment for pain, depression, anxiety, and sleep issues is cost-effective, leading to substantial cost savings and improved quality of life for patients. The program's cost per Quality-Adjusted Life Year (QALY) is significantly lower than benchmarks used in other countries, demonstrating high cost-effectiveness and value. Patients receiving 12 treatments experienced significant improvements across all measures, with estimated economic benefits surpassing treatment costs. In summary, ABCHIP offers a cost-effective and economically efficient therapy choice for individuals dealing with pain and mental health issues.

Optimizing dose parameters for enhanced maskless lithography in MoS2-based devices

Maskless lithography simplifies the fabrication process and reduces costs compared to electron beam (E-beam) lithography, making it a more efficient choice for patterning nano-devices. Maskless lithography presents a promising avenue for expediting device fabrication by eliminating the need for masks. This technique can streamline the production of basic electronic devices, offering an efficient and low-cost alternative to traditional lithographic methods, like E-beam lithography. This study utilized a 405 nm photodiode to achieve pattern-writing with a minimum linewidth of 1 μm. Exploring optimal parameters includes adjustments in beam intensity, scan speed, and step size. Maskless lithography was applied to 2D transition metal dichalcogenides (TMDCs) material, MoS2, to investigate their electrical transport characteristics. The fabricated device exhibits an ON/OFF ratio of ∼1.7 × 106 and a mobility of ∼0.833 cm2/V·s, indicating a high switching efficiency. The results demonstrate optimized maskless lithography's potential for swift and cost-effective fabrication, offering intermediate-resolution patterning capabilities.

Inhibition of Insulin-like Growth Factor 1 Receptor/Insulin Receptor Signaling by Small-Molecule Inhibitor BMS-754807 Leads to Improved Survival in Experimental Esophageal Adenocarcinoma.

The insulin-like growth factor-1 (IGF-1) and insulin axes are upregulated in obesity and obesity-associated esophageal adenocarcinoma (EAC). Nanoparticle albumin-bound paclitaxel (nab-paclitaxel) is a contemporary nanotechnology-based paclitaxel (PT) bound to human albumin, ensuring its solubility in water rather than a toxic solvent. Here, we examined the benefits of inhibiting insulin-like growth factor-1 receptor/insulin receptor (IGF-1/IR) signaling and the enhancement of nab-paclitaxel effects by inclusion of the small-molecule inhibitor BMS-754807 using both in vitro and in vivo models of EAC. Using multiple EAC cell lines, BMS-754807 and nab-paclitaxel were evaluated as mono and combination therapies for in vitro effects on cell proliferation, cell death, and cell movement. We then analyzed the in vivo anticancer potency with survival improvement with BMS-754807 and nab-paclitaxel mono and combination therapies. BMS-754807 monotherapy suppressed in vitro cell proliferation and wound healing while increasing apoptosis. BMS-754807, when combined with nab-paclitaxel, enhanced those effects on the inhibition of cell proliferation, increment in cell apoptosis, and inhibition of wound healing. BMS-754807 with nab-paclitaxel produced substantially greater antitumor effects by increasing in vivo apoptosis, leading to increased mice survival compared to those of BMS-754807 or nab-paclitaxel monotherapy. Our outcomes support the use of BMS-754807, alone and in combination with nab-paclitaxel, as an efficient and innovative treatment choice for EAC.

Exploring puffed rice as a novel ink for 3D food printing: Rheological characterization and printability analysis

This study introduces a novel approach by using puffed rice (PR) as a sustainable and innovative ink for 3D food printing. Due to gelatinization and dextrinization, PR saw notable water absorption and solubility gains, with a modest viscosity uptick from 39.2 to 49.9 RVU, sharply contrasting Native rice (NR)'s jump from 128.9 to 167.8 RVU, emphasizing PR's minimal retrogradation. Gelatinized rice (GR) demonstrates similar stability in viscosity changes as PR, yet it requires more water and extended processing times for gelatinization. Conversely, PR's puffing process, which eliminates the need for water, offers quicker preparation and notable environmental benefits. Rheological analysis at 25% PR concentration reveals an optimal balance of viscosity (η, 897.4 Pa s), yield stress (τy, 2471.3 Pa), and flow stress (τf, 1509.2 Pa), demonstrating superior viscoelastic properties that facilitate enhanced printability and shape fidelity. Texture Profile Analysis outcomes reveals that PR significantly enhances key textural properties including hardness, adhesiveness, and springiness at this specific concentration. These findings highlight PR's potential as an eco-friendly and efficient ink choice for 3D-printed food products, providing enhanced performance and sustainability compared to GR and NR.

Growth and metabolism of halophilic Candida versatilis and Tetragenococcus halophilus in simultaneous and sequential fermentation of salted soy whey

This study investigated various strategies: mono-, simultaneous and sequential fermentation of halophilic Candida versatilis and Tetragenococcus halophilus to valorize salted whey, a side stream of salted tofu (pressed beancurd) production, with an ultimate goal of creating a soy sauce-like condiment. Growth, glucose, organic acids were monitored throughout fermentation, while free amino acids and volatile compounds were analyzed on the final days. In monoculture fermentation, both C. versatilis and T. halophilus thrived in salted soy whey. However, in co-culture fermentation, an antagonistic relationship was observed, wherein C. versatilis growth was slightly suppressed and T. halophilus was significantly inhibited. In C. versatilis-involved fermentations, no significant (p > 0.05) differences in key volatile and non-volatile chemical components were found among various fermentation modes. Key soy sauce-like volatile compounds, such as 4-ethylguaiacol and 4-ethylphenol, were detected in all C. versatilis-fermented salted soy whey, while T. halophilus primarily functioned as a lactic and acetic acids producer. This study highlights the potential of mixed culture fermentation involving soy sauce yeast and lactic acid bacteria for eventually developing a soy sauce-like condiment from salted soy whey, with C. versatilis playing a crucial role in flavour development. The findings suggest that fermenting of a single culture of C. versatilis in lactic acid-adjusted salted soy whey could be a viable and efficient choice for future production of soy sauce-like condiment.

How much do hospital staff know, how much do they care, and what should they know about economic aspects of Diagnosis Related Groups? The case of an Italian children’s hospital

Background: Diagnosis Related Group (DRG) costing enables more efficient therapeutic choices. For this to occur, staff must be aware of the costs of the resources used in the process.Objective: The paper aims to identify potential information gaps of physicians, nurses, and administrative staff regarding economic aspects. It explores the intersection of financial awareness and the perceived importance of economic factors to evaluate the information deficiencies across these professional groups.Methods: The costs of DRG 546 different phases are estimated. Data on economic factors awareness (EFA) and economic factors importance (EFI) are gathered through a questionnaire. The survey involved 61 Italian employees of an Italian children’s hospital among physicians, nurses, and administrative staff.Results: A trade-off emerges between the scarce knowledge of the DRG economic aspects and their importance for physicians and nurses. Awareness of economic aspects does not depend on years of seniority.Conclusions: Economic factors awareness is low, although the staff considers this issue important. An information gap needs to be addressed. Clinical staff are partially aware of the costs of the activities in which they are directly involved, but they are unaware of other economic aspects of the therapeutic process. Nurses are the professional group with the lowest cost awareness. Different professional groups require different financial information. Physicians and nurses should be aware of relevant costs and the cost of activities with negligible impact on patient outcomes.Potential implications: Administrative offices often do not know what economic data could be helpful in the physicians’ or nurses’ decisions. In addition, medical and nursing staff do not know precisely what information to ask for. Workgroups composed of administrative and healthcare staff should define what relevant financial data should be provided and how.

HPTLC sequentially coupled to UV and SERS: A cost-effective tool for confirmative identification and quantitation of sildenafil in falsified herbal products

The detection of falsified drugs usually requires multi-disciplinary analysis for confirmative identification. Among hyphenated techniques with high specificity detection, thin-layer chromatography coupled with surface-enhanced Raman spectroscopy (TLC-SERS) is an efficient choice, especially for herbal products with diversified matrix. In this study, HPTLC was coupled to two detection techniques: UV absorption and Raman scattering with silver colloid enhancement for the analysis of sildenafil adulterated in herbal products. With this approach, orthogonal UV and SERS spectral data was collected, so that confirmative results could be obtained within a single TLC analysis. How this approach helped to reduce chances of false positive or false negative results was also discussed. The HPTLC sequentially coupled to UV and SERS (HPTLC-UV-SERS) method was developed and validated parallelly on the UV and SERS signals. To improve the repeatability of the SERS signal, several analytical conditions were optimized, so that direct quantitation with TLC-SERS was feasible without chemometric data extrapolation. The determination was done with UV scanning at 304 nm for HPTLC and with SERS signal at 1580 cm−1 (excitation 633 nm). The TLC-SERS method had a detection limit of 1.65 ng/spot, 95 times lower than HPTLC method (157 ng/spot). The HPTLC-UV-SERS method was applied on 24 real herbal samples collected from the market, among which 3 real samples were positive to sildenafil, and quantitation results by UV and SERS were in consistency. Not only this method was proved feasible for practical applications, but the recommendations for TLC-SERS procedures could also be useful in TLC-SERS method development for other compounds.

Optimizing Raw Material Inventory Control for Aluminum Wardrobes Using the Material Requirements Planning (MRP) Method: A Case Study on Amal Jaya SME

This study aims to analyze the implementation of Material Requirement Planning (MRP) method in controlling raw material inventory for aluminum wardrobe production in Amal Jaya SME. The inability to accurately predict the average number of customer orders each month indicates unfulfilled consumer demand. Therefore, effective raw material control becomes crucial to ensure availability in accordance with demand. The objectives of this research are to evaluate the management of raw materials using the MRP method and identify its impact on cost efficiency of raw materials in the production process. Additionally, this study aims to optimize raw material inventory to maximize customer demand fulfillment. The MRP method was chosen as the primary approach in this research. The results of the analysis indicate that the implementation of MRP method with Lot for Lot (LFL) lot sizing is the most efficient choice in controlling raw material inventory. Based on calculations using lot-for-lot and Economic Order Quantity (EOQ) methods, the most efficient inventory expenditure incurred by the company amounts to Rp. 26,274,840. Thus, ordering raw materials with Lot for Lot lot sizing can be used as a solution to optimize the control of aluminum wardrobe inventory in Amal Jaya SME.

Enhanced degradation of sulfathiazole by ionizing radiation activated persulfate and periodate: Performances and mechanisms

Ionizing radiation has attracted significant interests in water purifying. However, it suffers from poor mineralization performance during the decontamination of organic micropollutants such as antibiotics. Herein, the radiolytic degradation of sulfathiazole (STZ) by gamma radiation was investigated. STZ could be completely degraded at 2.0 kGy absorbed dose but TOC removal efficiency was only 22.62 %. Quenching experiments demonstrated that •OH was the main reactive species. Toxicity assessment and phytotoxicity experiments indicated that gamma radiation can comprehensively decrease the toxicity of STZ. Significant enhancements of degradation and mineralization were observed in gamma/persulfate (Gamma/PS) and gamma/periodate (Gamma/PI) processes. The rate constant (k) increased by 1.08 times and TOC removal efficiency increased by 2.01 times with PS addition (1 mM). The k value enhanced by 4.05 times and TOC removal ratio enhanced by 2.66 times with the presence of PI (1 mM). Mechanistic investigation indicated that 1O2 played a major role in STZ degradation in the Gamma/PS and Gamma/PI systems. PI was almost completely transferred into the nontoxic iodate (IO3-), and no toxic reactive iodine species were produced in the Gamma/PI process. Moreover, Gamma/PS and Gamma/PI systems showed a broad-spectrum ability to remove a series of antibiotics. The removal performances and the costs of these systems were competitive compared with other advanced oxidation processes for antibiotics elimination. This study supplied an efficient and sustainable choice for the degradation of antibiotics, and clarified the intrinsic reaction mechanisms in the ionizing radiation-activated PS and PI systems.

Inorganic charge transport layer for efficient Pb-free KSnI3 based perovskite solar cells: a theoretical study

The power conversion efficiency (PCE) of lead (Pb)-based perovskite solar cells (PSCs) is remarkably high; however, the toxicity of Pb poses a significant barrier to their commercial viability. In the current study, the effect of different charge transport layer (CTL) materials on the performance of the Pb free Sn-based (KSnI3) PSCs has been studied by using SCAPS simulations. Tin oxide (SnO2), zinc oxide, and titanium dioxide as electron transport materials, whereas spiro-OMeTAD, copper oxide (Cu2O), and nickel oxide as hole transport layer materials were iterated to achieve the optimum photovoltaic parameters. The photovoltaic parameters were optimized in terms of the active layer and CTL thicknesses, as well as the doping concentration, defect density, and interfacial defect density. Moreover, the impact of series and shunt resistance on the performance of PSCs is also investigated. The most efficient PSC with PCE of 21.75% was achieved with the device structure of FTO/SnO2/KSnI3/Cu2O. This efficiency is higher than previously reported KSnI3 based-PSCs. The SnO2 (ETL) and Cu2O were proven to be most efficient choices for the CTL materials. It was also observed that the carbon, nickel, and selenium can be a cost-effective alternative to gold for the rear contact. This study showcases how KSnI3 with inorganic charge transport layers stands as a prospective stable PSC with the potential to deliver clean, and green renewable energy solutions.

Multi-Objective Optimization Methods for Train Load Planning in Seaport Container Terminals

In this paper we study the planning problem of loading trains in seaport container terminals, which consists in assigning containers to the wagon slots. The train load can be realized considering different objectives, in this work we focus on two very important objectives for terminal managers, that are the minimization of the number of reshuffles in the storage area and the minimization of the total distance covered by the handling equipment between the storage area and the wagons. To address this problem, some multi-objective methods are investigated in the paper, based on the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon$</tex-math> </inline-formula> -constraint approach and the lexicographic algorithm, allowing to find different sets of efficient solutions to be provided to train planners. The experimental tests, devised to compare the proposed multi-objective methods, show that the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon$</tex-math> </inline-formula> -constraint method integrated with a lexicographic approach is the most efficient choice since it allows to obtain a higher number of efficient solutions in shorter computational times. This method can be applied in decision support systems for train planners in order to allow them to decide the train load in an efficient way. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The automation and the process optimization in seaport container terminals is a relevant issue for terminal managers in order to face the strong competitiveness in the logistics and shipping sector and the new emerging problems due to the presence of mega vessels. Among the different operations to be optimally managed in a terminal, the loading of trains is becoming more and more significant, also due to the increase of freight traffic by rail, seen as a cheaper and more sustainable option compared with road transport. The optimal assignment of containers present in a storage area to the wagon slots is a crucial decision in order to reduce operational times and costs in a container terminal. In this paper, we address the train load planning problem considering two important objectives to be minimized, i.e. the number of reshuffles and the distance covered by the handling equipment. The multi-objective methods proposed in the paper are devised to find different efficient solutions in short computational times. The proposed algorithms are intended to be implemented within a decision support tool in which the solutions found are shown to the train planner who chooses the preferred option depending on personal evaluations and on the basis of information coming in real time.

Percutaneous nephrolithotomy for adult renal transplant de novo graft lithiasis: a single center analysis and systematic review of the literature.

Graft stones in renal transplant recipients pose a unique challenge, finding effective interventions to ensure optimal graft function and patient well-being. Various methods of stone clearance have been described for graft stones, including percutaneous nephrolithotomy (PCNL). While PCNL is a promising approach for managing graft stones, specific outcomes and associated characteristics for this approach have not been comprehensively evaluated before. This study aims to evaluate the safety and efficacy of the use of PCNL as the primary intervention of graft stones by assessing stone-free rates (SFR), treatment impact on graft function, and perioperative complications. A retrospective clinical audit was performed for all transplants performed in a single center from 2007 to 2022, which included all graft lithiasis patients who were treated with PCNL. Both perioperative parameters and post-operative outcomes were collected. In addition, a systematic review including articles from MEDLINE, Embase, Web of Science yielded 18 full-text articles published between 1/1/2000 and 15/11/2023. The results pertaining to patients who underwent PCNLs for graft stones were cross-referenced and thoroughly evaluated. The review encompassed a comprehensive analysis of clinical data, postoperative outcomes, and procedural details. The protocol for the systematic review was prospectively registered on PROSPERO (CRD42023486825). In our center, 6 graft lithiasis patients were treated with PCNL. The initial SFR was 83.3%. SFR at 3months and 1year were both 100.0%. SFR at 3years was 66.7%. Other centers reported initial SFR of 82.6-100.0% (interquartile range). SFR at 3months, 1year, 3years was not well reported across the included studies. Incidence of graft lithiasis ranged from 0.44%-2.41%. Most common presentations at diagnosis were oliguria/anuria/acute kidney injury and asymptomatic. Reported complications included blood loss, transient hematuria, high urine output, sepsis, and damage to surrounding structures. The most commonly reported metabolic abnormalities in transplant lithiasis patients included hyperuricemia and hyperparathyroidism. PCNL is a practical and efficient choice for addressing graft lithiasis, demonstrating excellent stone clearance and minimal perioperative complications. These findings show the importance of PCNL as a primary intervention in this complex patient population.

Maximizing Motorcycle Power and Torque with Roller Modifications

In the automotive world, rapid advancements in motorized vehicle technology necessitate consumers to be selective in vehicle choice. This study examines the performance of motorcycles using modified racing rollers versus standard factory rollers. Focusing on a 150cc matic motorcycle, we analyzed power and torque outputs using rollers of different masses (11g, 16g, and standard 15.5g). Field studies and literature reviews were conducted, employing tools like dynotests to measure performance at RPM ranges from 4,700 to 9,500. Results indicate that the 16g roller achieved the highest torque of 12.45 N/m at 6,800 RPM, while the 11g roller attained 12.09 N/m at 67,300 RPM. The standard 15.5g roller reached 12.07 N/m at 76,400 RPM. This research highlights the impact of roller mass on motorcycle performance, providing valuable insights for enhancing vehicle efficiency and consumer choice. Highlight: 16g roller achieves highest torque of 12.45 N/m at 6,800 RPM. 11g roller reaches torque of 12.09 N/m at 67,300 RPM. Standard 15.5g roller attains 12.07 N/m at 76,400 RPM. Keywoard: Motorcycle Performance, Racing Rollers, Torque, Power Output, 150cc Matic

Environmental life cycle assessment of reusable launch vehicle fleets: Large climate impact driven by rocket exhaust emissions

After the success of the reusable Falcon 9 rocket, space actors are pursuing competitive space access by developing Reusable Launch Vehicles (RLVs). While this initiative may enhance recycling rates, it may also trigger the Jevons’ paradox as it amplifies the overall environmental footprint due to increased launch frequencies. It is therefore essential to quantify RLVs’ impacts and identify key design drivers to enable efficient design choices while mitigating undesirable environmental effects.Consequently, this article uses a space specific Life Cycle assessment (LCA) approach to evaluate the environmental footprint, in terms of climate impact, water depletion and land use, of different RLV fleets designed to serve a forecasted European space market. The results show that the LH2 fleet options have 2–8 times lower carbon footprint when compared to the LCH4 fleet as a result of lower propellant consumption and lack of black carbon emissions, suggesting that the environmental burdens are mostly driven by propellant choice. Moreover, the analysis reveals a potential underestimation of climate impacts in previous LCA’s by 2–3 orders of magnitude due to the absence of high altitude characterisation of rocket exhaust emissions and demised aluminium oxides. This increased forcing could lead to fleet choices surpassing the Earth’s carrying capacity given by its planetary boundaries.The methodology and results within this study can support further integration of launch and reentry emissions within LCA by refining modelling techniques, improving impact characterisation and quantifying uncertainties. These advancements can ultimately enable robust eco-design strategies for launch vehicles.