Regular Production Research Articles

Empirical Study on the Pottery Environment and its Contribution to the Economic, Cultural and Institutional Growth of the Community of Huancas, Amazonas, Peru: An Analysis with Smart Pls

This study focuses on analyzing how the pottery environment contributes to the economic, cultural and institutional growth of the community of Huancas, Amazonas, Peru. The research has a non-experimental approach at a descriptive correlational level. A total of 35 pottery families participated in the survey and the data collected were analyzed in SPSS and Smart PLS 4.0 statistical programs. The results indicate that the pottery field in the community of Huancas has contributed positively to economic, cultural and institutional growth (0.942; 0.935 and 0.915) respectively; this work represents the cultural identity of the community, based on the regular production of pots for cooking food and a great variety of vessels, with women being the main protagonists of these crafts (85.7%). In addition, the results indicate that pottery has promoted experiential rural tourism in the community, thus playing a fundamental role in the daily life of the community's artisan families. This study highlights a little-studied aspect of pottery making, and the results will guide decision-making in the management and promotion of this traditional activity, relating it to other activities such as tourism. Received: 12 July 2024 / Accepted: 31 October 2024 / Published: 05 November 2024

Integrating AI in cause-of-death regular statistical production with human and expert system codings

Abstract Background Cause-of-death (CoD) statistics are key indicators in epidemiology and public health. These statistics are derived from death certificates completed by physicians and are usually coded by official statistics authorities according to the standards of the WHO ICD-10 classification to construct time- and cross-country-comparable statistics. For coding causes of death in free-text format in France according to ICD-10, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team. Methods Seq-to-seq DNNs are trained from scratch on previously coded data to ICD-10 code multiple causes and underlying causes of death. Human coding is focused on certificates with a special public health interest or with low confidence in AI prediction quality to maximize the quality of the overall statistics disseminated when human resources are limited. DNNs also directly predict multiple causes and underlying causes of death for part of the certificates. Hence, the coding campaign aims to optimally allocate a coding mode to a given certificate. Results For deaths in 2021, 63% of the certificates are automatically batch coded by the expert system, 14% by the coding team, and 23% by DNNs. Compared to a traditional campaign that would have relied on automatic batch coding and manual coding, the present campaign reaches an accuracy of 95.7% for ICD-10 coding of the underlying cause (97.3% at the European shortlist level). Conclusions The 3-coding mode approach enables timeliness of dissemination of CoD statistics and may lead in the future to more responsive surveillance. Key messages • Deep neural networks trained on already coded data can be integrated into the regular statistical production of the CoD database in a fully controlled way. • The allocation between the different modes of coding can be optimized to achieve best quality and timeliness under the constraint of limited human resources.

The evolution of two‐stage production and order equilibrium in a random yield supply chain with demand information updating

AbstractThe mismatch between production, order, and demand seriously affects supply chain performance. However, most research focus on the mismatch between the retailer's order and customer's demand, which ignores the influence of the supplier's random yield on supply chain members' decision‐making. This paper investigates a two‐stage optimization problem within a two‐echelon supply chain, featuring a supplier with random yield and a retailer updating demand information in real‐time. Faced with a long production lead time, the retailer can either place advance orders at the production season's onset (first‐stage advance order) or opt for instant orders at the beginning of the sales season (second‐stage instant order). To ensure timely order fulfillment, the supplier initially employs a cost‐effective regular production mode with random yield during the production season. If yields are insufficient during sales, a pricier emergency production mode with guaranteed output becomes available. Utilizing a dynamic programming approach, we formulate the two‐stage optimization problem to derive optimal production and order decisions. Our analysis uncovers how realized random yield and stochastic market signals influence emergency production and instant order quantities in the second stage. We compare expected profits in scenarios with perfect and imperfect market signals, probing the members' preferences regarding order strategies. An intriguing finding emerges: as instant wholesale prices rising, the supplier's preferred order strategy diverges from the retailer. By strategic adjustments to the instant wholesale price, we demonstrate the potential for unanimous agreement on preferred order strategies among supply chain members — a quality enhancing the chain's flexibility and performance. Moreover, we extend the model to hybrid order strategies and identify conditions for unanimous preference among the three strategies. To bolster our theoretical findings, we provide numerical examples, lending practical support to our study.

The European Statistics Awards for Nowcasting: A New Approach to Engage with the Scientific Community and to Foster Improved Timeliness of Official Statistics

The European Statistics Awards Programme is a multiannual program for engaging with, and tapping into the potential of, the research and innovation community at large. This is achieved through competitions with pecuniary prizes for the best performers. One of the strands within that program offers awards for the accurate nowcasting of monthly time series of interest to policymakers. This paper presents the design of the nowcasting competition as well as the performance of the best entries of the first annual round. In terms of accuracy, the competition has generated promising results—which do however need further fine-tuning before being possible to deploy in statistical production. The competitions feature a particular prize for submissions having a potential for scaling up to regular statistical production—and in response to this, teams have submitted ample documentation (including code). The awards program should also generate experience that the official statistics community can learn from. This paper demonstrates how the multi-annual nature of the program has allowed various design changes to be implemented for the last nowcasting round. The main work now lies ahead: the paper outlines the plans for further developing the most promising competition contributions, potentially leading to new Eurostat experimental statistics products.

Mechanism of ultrasonic-enhanced leaching for separating organic impurities from the surface of bauxite and H2O2 oxidation-CaO precipitation for purifying the leaching solution

The existence of organic impurities in bauxite significantly hampers the regular production of alumina. This study proposes a low-temperature ultrasonic-enhanced alkali leaching to directly separate organic impurities from bauxite, and purify the leaching solution through H2O2 oxidation and CaO precipitation. Under the optimal conditions of 550 W ultrasonic power, 80 °C, 60 min, and 200 g/L NaOH concentration, the leaching rate of organic carbon in bauxite is 91.02 %, which is 19.01 % higher than conventional alkali leaching, and the organic carbon content in the bauxite decreased from 0.59 % to 0.06 % after leaching. Kinetic studies indicate that the limiting factors of the leaching rate vary under different leaching temperatures and leaching times. Characterization of bauxite before and after leaching using various detection techniques demonstrates the effective separation of organic impurities while basically no loss of alumina and increasing the alumina to silica ratio to 34.13. Subsequently, H2O2 and CaO are introduced to the leaching solution with 20 % and 800 mL/g, respectively. The oxidation process under 550 W ultrasonic power at 90 °C for 60 min achieves an 71.35 % removal rate of organic carbon. GC-MS analysis confirms the successful removal of the main organic substances in the leaching solution, while XRD analysis of the oxidation residue indicates that organic substances are ultimately removed as CaC2O4·H2O and CaCO3. Additionally, a proposed free radical reaction mechanism of H2O2 oxidizing organic substances is discussed. In conclusion, this study providing valuable insights for the removal of organic pollutants in the alumina production process.

Are Socio-Economic Indicators Associated with Food Safety in Public Schools? A Study in Sergipe State, Brazil.

The Brazilian National School Feeding Programme aims to ensure food security and the right to food for public school students. To protect these fundamental rights, a comprehensive approach is needed that includes ensuring food safety. Recognising that low socio-economic conditions, inadequate food safety and child vulnerability can pose a cumulative burden on child development, this study examined food safety in public schools in Sergipe, Brazil, in the context of local socio-economic indicators. All state public schools in Sergipe (n = 314) were included. Food safety and socio-economic data were analysed using secondary sources and geographical maps. The cluster analysis identified two different groups of schools based on socio-economic indicators. While most schools presented regular foodborne illness risks, food production and temperature control had particularly high levels of non-compliance. Schools in areas with higher socio-economic indicators (Cluster 2) had better overall food safety scores (p < 0.001) compared to schools in areas with lower socio-economic indicators (Cluster 1). Cluster 1 schools also had a higher FBI risk when analysing temperature-controlled equipment violations (p = 0.001), food handlers (p = 0.005) and process and production (p = 0.004), which emerged as critical areas. These results emphasise the urgent need for targeted interventions to improve food safety in schools located in areas with lower socio-economic conditions.

Early Versus Late Rapid Force Production During Single-Joint Isometric Hamstring Assessment Using Force Plates.

Ripley, NJ, Barber, R, Fahey, JT, and Comfort, P. Early versus late rapid force production during single-joint isometric hamstring assessment using force plates. J Strength Cond Res XX(X): 000-000, 2024-The aim of this study was to assess differences in time-matched early versus late rapid force (RF) development in female soccer players in the 90-90 isometric hamstring assessment. Twenty-one elite female soccer players (age: 20.7 ± 4.7 years; height: 168.2 ± 5.5 cm; body mass: 62.8 ± 7.0 kg), with no recent (>6 months) history of hamstring strain injury, volunteered to participate in the study. Following a standardized warm-up, each subject performed 3 maximal isometric unilateral hamstring contractions, with their heel resting on a force plate, elevated on a box, to ensure that their hips and knees were at 90°. Data were analyzed to determine peak force, early RF (ERF) 0-100 milliseconds and late RF (LRF) 100-200 milliseconds. Significant and large differences were observed in the percentage of peak force achieved between ERF (52.85 ± 11.53%; 54.99 ± 9.80%) and LRF (15.82 ± 5.58%; 15.25 ± 3.91%) for the left and right limbs, respectively (p < 0.001, g = 2.13-3.06). The large differences between ERF and LRF can be used by practitioners to streamline performance assessment, which in turn will allow practitioners to act upon data collected more effectively. Additionally, regular monitoring ERF production could inform practitioners of any interventions that maybe required, such as reduction of load or introduction of specific recovery modalities and during return to play protocols.

Improving sustainability of precast concrete sandwich wall panels through stone waste aggregates and supplementary

Precast concrete sandwich wall panels offer advantages such as design flexibility, ease of installation, cost-effectiveness, and energy efficiency due to the incorporated insulation layer, but regular concrete production has sustainability issues. This study aims to improve the sustainability of these panels by utilizing stone waste aggregates as a replacement for natural aggregates and supplementary cementitious materials as a partial replacement for cement. The panels were made with two concrete wythes reinforced with steel fibers and joined using basalt fiber-reinforced polymer (BFRP) connectors, with high-density expanded polystyrene (EPS) insulation (30 kg/m3) in between. Self-compacting concrete mixes with varying proportions of stone waste aggregates and supplementary cementitious materials were used. Full-scale wall panels were cast and subjected to flexural tests per ASTM standards, analyzing load-displacement curves, ultimate bearing capacity, and failure modes. The incorporation of steel fibers and stone waste aggregates resulted in substantial increases in failure load and flexural strength compared to controlled concrete panels, with the stone waste steel fiber panels exhibiting significantly higher maximum cracking loads and improved energy absorption and ductility. The inclusion of these sustainable materials, along with basalt fiber connectors and grooves in the EPS layer for mechanical interlock, prevented brittle failure modes and enhanced the composite action, leading to more ductile behavior under flexural loading. Utilizing sustainable materials like stone waste aggregates (100% replacement) and supplementary cementitious materials (30% replacement) in these panels can contribute to eco-friendly and efficient construction practices while maintaining adequate structural performance, paving the way for more sustainable building systems

Implementing EU energy and climate governance: Germany and Sweden as frontrunners?

A core element in the EU’s Governance regulation (Regulation 2018/1999) is the regular production of National Energy and Climate Plans (NECPs). The process involves a dialog with the European Commission intended to lead to changed and improved plans. This new policy mechanism has been characterised as ‘harder soft governance’. Although member states are not obliged to specify binding targets for renewables and energy efficiency, they must report their contribution to fulfilling the overall European target. Furthermore, they must develop a plan for how to reach these contributions (the NECP). In this article we discuss NECP implementation in the first round of establishing NECPs in two traditional climate-policy frontrunners in the EU: Germany and Sweden. A key finding is that both countries did not perceive the NECP process as particularly important for national policy-making. Central targets and measures were mainly based on policies developed independently of the Governance Regulation. However, interaction with the Commission was more important for ‘reluctant’ Sweden than ‘Governance supporter’ Germany. Our study shows that both countries eventually produced the required contributions and plans, lending support to the argument that this new regulation has some ‘harder soft governance’ elements that will influence member states.

Ayurvedic Management of Dry Eye

Dry eye is a multifactorial illness of the tears and ocular surface, dry eye causes pain, disruptions to vision, instability in the tear film, and maybe even damage to the ocular surface. Tear secretion gives the corneal epithelium oxygen and continuously lubricates and moisturises the ocular surface. Dry eyes result from a disruption in regular tear production. Local, systematic and environmental factors play a major role in pathogenesis. Often exacerbated by smoke, wind, heat, low humidity or prolonged use of the eye. One of the most common disorders affecting the eyes is dry eye, affecting millions of people globally. The worldwide prevalence ranges from 5% to 50%, depending on the geographic region, Prevalence rate in India is higher than the global prevalence and ranges from 18.4% to 54.3%. Shushkaksipaka is one among Sarvagata netra rogas disease affecting all parts of the eye can be symptomatically correlated with dry eye. Vata and Pitta vitiation as per Ayurvedic view point are the major contributing pathological factor in its manifestation. This is a single case study of Shushkakshipaka treated with Deepana, Pachana, Kosta Shodhana, followed by 2 sittings of Ksheera Saindhava Prakshalana and Suntyadi Anjana and Anu taila Pratimarsha Nasya. At the end of the study improvement in foreign body sensation and itching. Patient got very significant result is being discussed here.

Using graph neural network to conduct supplier recommendation based on large-scale supply chain

Driven by economic globalisation, various industries have developed a trend towards high specialisation and vertical division of labor, resulting in vast and intricate supply chain networks. However, unforeseen disasters can cause supply chain disruptions, subsequently impacting the regular production and operations of both upstream and downstream enterprises. To tackle this challenge, this study utilises Graph Neural Networks (GNNs) to synthesise graph structural data within the supply chain network, aiming to identify alternative suppliers to mitigate the impact of disruptions. We construct a large-scale knowledge graph to represent the realistic automotive supply chain network in China. Additionally, we propose a GNN-based framework that utilises information about interactions between buyers and suppliers to recommend alternative suppliers from the knowledge graph. Experimental results show that our approach significantly outperforms state-of-the-art GNN-based models, including Light-GCN and NGCF. Our research provides an intelligent and efficient perspective on supplier selection for the Chinese automobile industry.

Transferable AmpCs in Klebsiella pneumoniae: interplay with peptidoglycan recycling, mechanisms of hyperproduction, and virulence implications.

Chromosomal and transferable AmpC β-lactamases represent top resistance mechanisms in different gram-negatives, but knowledge regarding the latter, mostly concerning regulation and virulence-related implications, is far from being complete. To fill this gap, we used Klebsiella pneumoniae (KP) and two different plasmid-encoded AmpCs [DHA-1 (AmpR regulator linked, inducible) and CMY-2 (constitutive)] as models to perform a study in which we show that blockade of peptidoglycan recycling through AmpG permease inactivation abolished DHA-1 inducibility but did not affect CMY-2 production and neither did it alter KP pathogenic behavior. Moreover, whereas regular production of both AmpC-type enzymes did not attenuate KP virulence, when blaDHA-1 was expressed in an ampG-defective mutant, Galleria mellonella killing was significantly (but not drastically) attenuated. Spontaneous DHA-1 hyperproducer mutants were readily obtained in vitro, showing slight or insignificant virulence attenuations together with high-level resistance to β-lactams only mildly affected by basal production (e.g., ceftazidime, ceftolozane/tazobactam). By analyzing diverse DHA-1-harboring clinical KP strains, we demonstrate that the natural selection of these hyperproducers is not exceptional (>10% of the collection), whereas mutational inactivation of the typical AmpC hyperproduction-related gene mpl was the most frequent underlying mechanism. The potential silent dissemination of this kind of strains, for which an important fitness cost-related contention barrier does not seem to exist, is envisaged as a neglected threat for most β-lactams effectiveness, including recently introduced combinations. Analyzing whether this phenomenon is applicable to other transferable β-lactamases and species as well as determining the levels of conferred resistance poses an essential topic to be addressed.IMPORTANCEAlthough there is solid knowledge about the regulation of transferable and especially chromosomal AmpC β-lactamases in Enterobacterales, there are still gaps to fill, mainly related to regulatory mechanisms and virulence interplays of the former. This work addresses them using Klebsiella pneumoniae as model, delving into a barely explored conception: the acquisition of a plasmid-encoded inducible AmpC-type enzyme whose production can be increased through selection of chromosomal mutations, entailing dramatically increased resistance compared to basal expression but minor associated virulence costs. Accordingly, we demonstrate that clinical K. pneumoniae DHA-1 hyperproducer strains are not exceptional. Through this study, we warn for the first time that this phenomenon may be a neglected new threat for β-lactams effectiveness (including some recently introduced ones) silently spreading in the clinical context, not only in K. pneumoniae but potentially also in other pathogens. These facts must be carefully considered in order to design future resistance-preventive strategies.

Bothrops lanceolatus Envenoming in Martinique: A Historical Perspective of the Clinical Effectiveness of Bothrofav Antivenom Treatment.

Bothrofav, a monospecific antivenom, was introduced in June 1991 and has shown excellent effectiveness against life-threatening and thrombotic complications of Bothrops lanceolatus envenoming. Because of the reoccurrence of cerebral stroke events despite the timely administration of antivenom, new batches of Bothrofav were produced and introduced into clinical use in January 2011. This study's aim was to evaluate the effectiveness of Bothrofav generations at treating B. lanceolatus envenoming. During the first period of the study (2000-2010), 107 patients were treated with vials of antivenom produced in June 1991, while 282 envenomed patients were treated with vials of antivenom produced in January 2011 in the second study period (2011-2023). Despite timely antivenom administration, thrombotic complications reoccurred after an interval free of thrombotic events, and a timeframe analysis suggested that the clinical efficacy of Bothrofav declined after it reached its 10-year shelf-life. In of the case of an antivenom shortage due to the absence of regular batch production, no adverse effects were identified before the antivenom reached its 10-year shelf-life, which is beyond the accepted shelf-life for a liquid-formulation antivenom. While our study does not support the use of expired antivenom for potent, life-threatening B. lanceolatus envenoming, it can be a scientific message to public entities proving the necessity of new antivenom production for B. lanceolatus envenoming.

Application of reactor dosimetry techniques for source term validation in F-18 production with a medical cyclotron

Imaging techniques such as positron emission tomography need radionuclides that can be produced with cyclotrons. The involved nuclear reactions mostly produce neutron and gamma radiation, which must be shielded. In order to be able to determine the required thickness of the shielding for a newly bought medical cyclotron, corresponding radiation protection calculations were carried out. The necessary neutron source term was supplied by the manufacturer. To verify this source term, additional source terms were calculated with the MCNP6 and the FLUKA code packages. The results with the source, on base of code internal nuclear models, produced comparable results, but the neutron yield with the source supplied by the manufacturer turned out to be lower by a factor of about 5. To validate the results, experiments were carried out on an already existing cyclotron. Neutron fluence was measured with standard monitors which are used in reactor dosimetry. The experiments were performed during regular 18F production. Activities of the nuclides were measured by gamma spectroscopy and compared with the calculated activities.

Multi-Sensor Observations Reveal Large-Amplitude Nonlinear Internal Waves in the Kara Gates, Arctic Ocean

We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers, and repeated conductivity–temperature–depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas during spring tide in August 2021. Analysis of the field data during an 18-h period from four stations provides evidence that a complex sill in the Kara Gates is the site of regular production of intense large-amplitude nonlinear internal waves. Satellite data show a presence of a relatively warm northeastward surface current from the Barents Sea toward the Kara Sea attaining 0.8–0.9 m/s. Triangle-shaped measurements using three thermal profilers revealed pronounced vertical thermocline oscillations up to 40 m associated with propagation of short-period nonlinear internal waves of depression generated by stratified flow passing a system of shallow sills in the strait. The most intense waves were recorded during the ebb tide slackening and reversal when the background flow was predominantly supercritical. Observed internal waves had wavelengths of ~100 m and traveled northeastward with phase speeds of 0.8–0.9 m/s. The total internal wave energy per unit crest length for the largest waves was estimated to be equal to 1.0–1.8 MJ/m.

The effects of energy consumption of alumina production in the environmental impacts using life cycle assessment

PurposeAluminium industry emits around 1–2% of the world’s total greenhouse gas emissions. Up to one-third of those are linked to the thermal energy consumed during its initial process: the alumina refining (Bayer process). Previous studies consider the Bayer process a single stage despite its being made of several reaction stages. This work presents a disaggregated energy analysis of the Bayer process that facilitates to find relationships between the main variables in regular alumina production and the environmental impacts.MethodsTwo different thermodynamic simulations of the Bayer process were carried out using Aspen V11 software. The results of these simulations were validated with referenced data, and afterwards, they were used to perform a life cycle assessment. ISO 14040 and 14,044 standards were followed during the analysis. LCA was implemented on SimaPro 9.0, and ReCiPe 2016 Midpoint (H) method was used to calculate environmental impacts. The influence of bauxite mineral form, type of fuel (energy input), and the distance from the mine to the plant was analysed throughout the study.Results and discussionAs expected, the type of fuel was revealed as the most crucial factor in the environmental impact of alumina production, with potential savings of up to 75.5% of CO2-equivalent emissions. Nonetheless, the tendency is diverse for other indicators, such as marine eutrophication or terrestrial acidification. On the other hand, while bauxite transportation always has the same impact on the different environmental indicators, bauxite mineral form affects differently depending on the fuel, causing variations in the CO2-eq emissions from 7.7 to 51.3%.ConclusionsResults indicated that the electrification of heat-demanding processes and the use of renewable power is the most effective approach for reducing environmental impacts. This strategy, however, must be considered in combination with others, as interdependent effects exist on the type of mineral used. These results provide strong evidence of the potential for environmentally friendly strategies in the metal industry, including new processes, alternative fuels, or mineral switching to promote more sustainable aluminium production.

Efficient Formulation for Vendor–Buyer System Considering Optimal Allocation Fraction of Green Production

The classical joint economic lot-sizing (JELS) policy in a single-vendor single-buyer system generates an equal production quantity in all cycles, where the input parameters remain static indefinitely. In this paper, a new two-echelon supply chain inventory model is developed involving a hybrid production system. The proposed model simultaneously focuses on green and regular production methods with an optimal allocation fraction of green and regular productions. Unlike the classical mathematical formulation, cycles do not depend on each other, and consequently, each model parameter can be adjusted to be responsive to the dynamic nature of demand rate and/or price fluctuation. A rigorous heuristic approach is used to derive a global optimal solution for a joint hybrid production system. This paper accounts for carbon emissions from production and storage activities related to green and regular produced items along with transportation activity under a multi-level emission-taxing scheme. The results emphasize the significant impact of green production on emissions. That is, the higher the allocation fraction of green production, the lower the total amount of emissions generated by the system, i.e., the system becomes more sustainable. Adopting a hybrid production method not only decreases the greenhouse gas (GHG) emissions dramatically, but also reduces the minimum total cost per unit time when compared with regular production. One of the main findings is that the total system cost generated by the base closed-form formula of the proposed model is considerably lower in the first cycle (subsequent cycles) than that of the existing literature, i.e., 33.59% (16.13%) when the regular production method is assumed. Moreover, the optimal production rate generated by the proposed model is the one that minimizes the emissions production function. In addition, the system earns further revenue by utilizing a mixed transportation policy that combines the Truck Load (TL) and Less than Truck Load (LTL) services. Illustrative examples and special cases that reflect different realistic situations are compared to outline managerial insights.

Can Bulgarian Yogurt enhance astronauts’ performance during the Mars Missions?

Probiotics (pro-for and bio- health) from yogurt are one of the most effective means to stimulate and strengthen the immune system. They help balance and regulate the digestive system, as well as preserve and enrich the gut microbiome. Maintaining a healthy gut microbiome is crucial for human health and well-being, especially for astronauts living in confined and stressful environments, such as those on a mission to Mars. One way to promote gut microbiome diversity is through diet, and Bulgarian yogurt (kiselo mlyako in Bulgarian: киceлo млякo) made with Lactobacillus delbrueckii subsp bulgaricus and Streptococcus thermophilus has shown positive effects on gut health. This paper explores the potential of regular production and consumption of gut-beneficial foods, such as yogurt, during space travel. It analyses whether the dietary limitations and challenges in providing varied and fresh food for astronauts could be addressed through the addition and daily consumption of Bulgarian yogurt. To investigate this, we conducted an experiment with a team of analog astronauts participating in a two-week analog mission in a closed, Mars-like environment at the Mars Desert Research Station in the Utah desert, the USA. In compliment to all recognized health effects of yogurt, the analog astronauts reported that it can be easily prepared and had a positive effect on their overall well-being and gut health. Our study demonstrated the feasibility of incorporating freshly made yogurt into the astronauts’ diet and its potential to significantly contribute to achieving good health and well-being, which is an important goal in the colonization of other planets, such as Mars.

Electrochemical micromachining on nickel and nickel-based superalloys with two-tone sinusoidal signal

Electrochemical micromachining is an emerging technology in the machining field. This method offers several advantages such as exceptional surface quality, minimal cathode depletion, and a high elimination rate. Often, an ultrashort pulse power supply is employed in electrochemical micromachining to address over-machining in non-processing areas. While reducing the pulse duration can enhance processing accuracy, its high cost and impracticality for regular production limit its development. This paper presents the use of a Two-tone sinusoidal signal as an alternative to ultrashort pulse in electrochemical micromachining. We investigated the mechanism behind the reduced machining gap with this signal. By drilling micro-holes in the nickel sheet to optimize parameters such as voltage, fundamental frequency, and harmonic order. Using the Taguchi optimization method, we studied the impact of these control variables on the micromachining process during micro-hole drilling. The study also focused on fabricating micro-structures using the best processing parameters. Our results showed that using the optimized parameters greatly enhanced processing accuracy. Moreover, we found that high machining accuracy could be achieved when working on hard-to-cut super alloy plates.

Finance dependence and exchange rate pass-through: Empirical evidence from China

Does the degree of finance dependence, defined as firms' reliance on external finance for regular production activities, determine exporters' heterogeneous responses to real exchange rate shocks? This paper develops a stylized model to illustrate the role of finance dependence in shaping exporters' pricing decisions when the bilateral real exchange rate fluctuates. The model features distribution costs, endogenous markup, and firm heterogeneity. In the model, finance dependence can impact firms' export pricing decisions in a way isomorphic to firm productivity but in the opposite direction: firms with high finance dependence have a high demand elasticity and a low price elasticity to exchange rate fluctuations. Therefore, in response to real exchange rate shocks, financially more dependent firms exhibit lower exchange rate pass-through into export prices denominated in home country currency (RMB). To assess the model prediction, I develop a firm-destination-year-specific measure of finance dependence based on the basket of goods that firms export and employ the Chinese manufacturing firm export data from 2000 to 2006 for analysis. The empirical test is carried out at the most disaggregated firm-product-destination level and confirms the model prediction.