Changes In Output Research Articles

Accuracy and Readability of Kidney Stone Patient Information Materials Generated by a Large Language Model Compared to Official Urologic Organizations

ObjectiveTo compare the readability and accuracy of large language model generated patient information materials (PIMs) to those supplied by the American Urological Association (AUA), Canadian Urological Association (CUA), and European Association of Urology (EAU) for kidney stones. MethodsPIMs from AUA, CUA, and EAU related to nephrolithiasis were obtained and categorized. The most frequent patient questions related to kidney stones were identified from an internet query and input into GPT-3.5 and GPT-4. PIMs and ChatGPT outputs were assessed for accuracy and readability using previously published indexes. We also assessed changes in ChatGPT outputs when a reading level was specified (grade 6). ResultsReadability scores were better for PIMs from the CUA (Grade level 10 – 12), AUA (8 – 10), or EAU (9 -11) compared to the chatbot. GPT-3.5 had the worst readability scores at Grade 13-14 and GPT-4 was likewise less readable than urologic organization PIMs with scores of 11-13. While organizational PIMs were deemed to be accurate, the chatbot had high accuracy with minor details omitted. GPT-4 was more accurate in general stone information, dietary and medical management of kidney stones topics in comparison to GPT-3.5, while both models had the same accuracy in the surgical management of nephrolithiasis topics. ConclusionsCurrent PIMs from major urologic organizations for kidney stones remain more readable than publicly available GPT outputs, but they are still higher than the reading ability of the general population. Of the available PIMs for kidney stones, those from the AUA are the most readable. Although Chatbot outputs for common kidney stone patient queries have a high degree of accuracy with minor omitted details, it is important for clinicians to understand their strengths and limitations.

Analysing the Total Factor Productivity Change Among Urban Cooperative Banks in India: The Malmquist Productivity Approach

This study investigates the total factor productivity (TFP) growth among urban cooperative banks in India during 2014–2020. The measurement of productivity is done using the data envelopment analysis-based Malmquist productivity index. We use two different models, viz., the intermediation approach and the production approach, to see how productivity estimates vary with the change in inputs and outputs. Our results show a large asymmetry in productivity estimates both among banks and over time. TFP estimates were consistently higher under the production approach vis-à-vis the intermediation approach. Further, the empirical results show that productivity gains were mainly determined by technological progress rather than efficiency improvements. Thus, collaborations in technological know-how can be beneficial to productivity growth. JEL Classifications: G15, G21, G34

Highly Sensitive Paper-Based Force Sensors with Natural Micro-Nanostructure Sensitive Element.

Flexible paper-based force sensors have garnered significant attention for their important potential applications in healthcare wearables, portable electronics, etc. However, most studies have only used paper as the flexible substrate for sensors, not fully exploiting the potential of paper's micro-nanostructure for sensing. This article proposes a novel approach where paper serves both as the sensitive element and the flexible substrate of force sensors. Under external mechanical forces, the micro-nanostructure of the conductive-treated paper will change, leading to significant changes in the related electrical output and thus enabling sensing. To demonstrate the feasibility and universality of this new method, the article takes paper-based capacitive pressure sensors and paper-based resistive strain sensors as examples, detailing their fabrication processes, constructing sensing principle models based on the micro-nanostructure of paper materials, and testing their main sensing performance. For the capacitive paper-based pressure sensor, it achieves a high sensitivity of 1.623 kPa-1, a fast response time of 240 ms, and a minimum pressure resolution of 4.1 Pa. As for the resistive paper-based strain sensor, it achieves a high sensitivity of 72 and a fast response time of 300 ms. The proposed new method offers advantages such as high sensitivity, simplicity in the fabrication process, environmental friendliness, and cost-effectiveness, providing new insights into the research of flexible force sensors.

Economic viability of using OvSynch and fixed timed artificial insemination protocol in breeding improvement of pastoral herds in the rangelands.

Though using Assisted Reproductive Technologies (ARTs) can improve oestrus detection, conception and pregnancy success, thus benefit breeding program implementation, empirical evidence of their economic viability is lacking to inform investment decisions in pastoral herds. This study assessed economic viability of using OvSynch and fixed Timed Artificial Insemination (TAI) protocol in Sahiwal upgrading breeding program under two hypothetical cases of best and worst in activity-based money allocations when pastoral herds deploy either optimal or low input husbandry practices. From herd owners' assessment of milk production, best-case scenarios attain on average 10 L/cow/day with optimal husbandry and 5 L/cow/day with low input husbandry. The worst-case scenarios attain 5 L/cow/day with optimal husbandry and 1 L/cow/day with low input husbandry. Benefit- Cost Analysis (BCA) estimated Net Present Value (NPV), Benefit-Cost ratio (BCR) and Internal Rate of Return (IRR) to establish economic viability of using OvSynch and TAI Protocol in pastoral breeding programs. Both best-case scenarios retuned positive NPVs (82,028 and 6,912), BCR values (1.68 and 1.08) and IRR (27.46% and 8.08%) while worst-case scenarios returned negative NPVs (-135,855 and -141,025), BCR values of below 1 (0.87 and 0.66) and IRR values below the minimum rate of returns. These economic parameters were sensitive to price changes in inputs and outputs, under both optimal and low input husbandry practices. Results indicate that using OvSynch and TAI Protocol is a profitable and economically viable investment under optimal husbandry practices but not under low input husbandry practices. By implications, use of OvSynch and TAI Protocol in Sahiwal upgrading breeding programs need be accompanied with improved husbandry practices and de-risking pastoral herd owners from price changes in input and output markets.

Optimization model of new energy consumption based on load demand-side response

As a technically and economically feasible and potentially resource-rich regulation tool, demand-side response can effectively strengthen the guarantee of new energy consumption, and is expected to play an enhanced key role in the construction of new power systems. This paper analyzes the factors affecting the linkage between demand-side and new energy generation side, the promotion of new energy consumption by demand-side response, and proposes a method to respond to the change of new energy output from the customer side, using interruptible load, transferable load, shiftable load, and curtailable load strategies to respond to the peak regulation problem brought by new energy access to the grid. The optimal demand-side response strategy is obtained by constructing a new energy consumption optimization model and solving it with the direct non-inferiority solution method, taking into account the economic and new energy consumption objectives. Finally, the effectiveness of the method is verified by simulating the IEEE 37-node system with multiple new energy configurations.

A Comparative Study on the Structural Response of Multi-Linked Floating Offshore Structure between Digital Model and Physical Model Test for Digital Twin Implementation

A digital twin is a virtual model of a real-world structure (such as a device or equipment) which supports various problems or operations that occur throughout the life cycle of the structure through linkage with the actual structure. Digital twins have limitations as a general simulation method because the characteristic changes (motion, stress, vibration, etc.) that occur in the actual structure must be acquired through installed sensors. Additionally, it takes a huge computing cost to output changes in the structure’s characteristics in real time. In particular, in the case of ships and offshore structures, simulation requires a lot of time and resources due to the size of the analysis model and environmental conditions where the wave load acts irregularly, so the application of a different simulation methodology from existing ones is required. The order reduction method, which accurately represents the system’s characteristics and expresses them in a smaller model, can significantly reduce analysis time and is an effective option. In this study, to analyze the applicability of the order reduction method to the development of digital twins for offshore structures, the structural responses of a multi-connected floating offshore structure were estimated by applying the order reduction method based on distortion base mode. The order reduction method based on the distortion base mode predicts the responses by constructing an order-reduced conversion matrix consisting of the selected distortion base mode, based on the mode vector’s orthogonality and autocorrelation coefficients. The predicted structural responses with the reduced order model (ROM) were compared with numerical analysis results derived using the higher order boundary element method and finite element method with in-house code owned by the Korea Research Institute of Ship & Ocean Engineering and measured responses with a model test. When compared with the numerical analysis results, the structural responses were predicted with high accuracy in the wave direction and wave frequency band of the selected distortion base mode, but there are differences due to changed characteristics of the structure when compared with the results of the model test. In addition, differences were also seen in reduced order model evaluation with different sensor locations, and it was confirmed that the more similar the extracted distortion base modes of input sensor location set is to the distortion base modes of predicted location set, the higher accuracy is in predicting the structural responses. As a result, the performance of the reduced order model is determined by the distortion base mode selection method, the locations of the sensor, and the prediction for the structural response.

Türkiye'de Konteynerleşmenin Gelişimi ve Hacimsel Yoğunluğunun Araştırılması

Containerization has caused significant structural, operational, and strategic changes in ports. Ports, which have an important role in the development of a country, also have an impact on the regional distribution of development. Therefore, changes in port throughputs, market shares and regional concentrations seen under the influence of changes caused by containerization are key indicators for analyzing the effects of ports on the regional distribution of development. Thus, the effects of ports on regional recovery and development movements, trade patterns and cargo flow in the region can be revealed. This article examines the changes in container volume of port authorities in Türkiye between 2004 and 2022 and the concentration and spread trends of containerization. The aim of this study is to provide a perspective to decision makers in determining future development and investment strategies as a result of determining the current situation of Turkish ports. In this study, Gini Coefficient and Shift-Share analysis methods were used. The necessary data for this study was obtained from the official institutions of the Republic of Türkiye. The results show that state ports, due to their sluggish and less dynamic structures, are being replaced by private ports that can respond to demands quickly and offer efficient container operations thanks to their advanced technology infrastructures. The findings show that today Turkish container traffic is more evenly distributed among existing ports. Moreover, although container volumetric concentration is still more dominant in the Marmara region, significant increases in container volumetric concentration have been observed in the Mediterranean, Aegean, and Black Sea regions.

Modeling Price Policy of Industries within the Frames of Inter-Sectoral Balance Methodology

The subject of inter-sectoral balance has been adequately developed in scientific community, however, we think that insufficient attention was paid to inserting price rates of industries in the model of inter-sectoral relations, as they produce a serious impact on making decisions concerning each industry production. The article deals with working-out a mathematic approach to modeling industry behavior in view of price policy development. The theoretical base of the research was formed by key provisions of the economic theory and the theory of inter-sectoral balance. The authors analyze dynamics of product prices set by industries with regard to inter-sectoral dependence and respective changes in output, added value, margin and volumes of sold products in each industry. As a result of the research the inter-sectoral model of shaping price policy of industries was built, which takes into account parameters of demand and urge of every industry for maximum profits. Different scenarios of changing demand parameters and production interactions were studied. Model experiments allowed authors to come to the conclusion that a rise in demand for one industry product cannot always increase production of related industries. As product price in the industry goes up, costs of other industries also rise, which can have an adverse effect on their product demand on the part of end customer. And on the contrary, a drop in demand for one industry product can support other related industries on constant demand factors at the expense of cost cutting. The proposed model could be useful for private and state sectors in planning investment policy at the same time it could reveal macro-economic trends, which is necessary to resolve problems of tardy or inadequate response of business entity on possible risks.

Flow Characteristics Analysis of a 1 GW Hydraulic Turbine at Rated Condition and Overload Operation Condition

Flow stability is extremely important for hydraulic turbines, especially for 1 GW hydraulic turbines, and has a strong impact on mesh stability. However, turbines often operate under non-design conditions, and current research on this aspect is still lacking. So a model of the fluid domains of a high-quality installed 1 GW Francis turbine was established to investigate the flow characteristics of the turbine and fluid domains. CFD simulations of a 1 GW Francis turbine under rated load and overload operation conditions were performed. According to simulation results, when the turbine is under the overload operation condition, the internal flow stability of the 1 GW hydraulic turbine can be obviously different from that of the rated load. In the overload condition, the flow field is more turbulent and a large number of vortices are generated in the draft tube, resulting in significant changes in pressure, flow rate, and output. In order to improve calculation accuracy, a pure clearance model containing only clearances and pressure balance pipes was established. The results of the full flow channel and pure clearance were compared. It was found that under the rated operating condition and the overload condition, compared with the pure clearance model, the axial force of the runner calculated by the full flow channel model is approximately 2–7% biased, the radial force is biased by approximately 7–8%, and the leakage flow is smaller.

Multicolor Tunable Upconversion Luminescence via Near‐Infrared Manipulation of Population Pathways of Er3+ Ions Excited‐State Levels for Volumetric Color Displays

AbstractPrecise control over multicolor luminescence of upconversion nanoparticles (UCNPs) is of significant importance for their applications in widespread fields of research. However, realizing the tunable emissions in single UCNPs with a single lanthanide element remains a great challenge. Herein, without multiple lanthanide elements, a new strategy for the regulation of the excited‐state level population pathways of the same lanthanide activator Er3+ ion to obtain multicolor‐tunable upconversion luminescence is proposed through utilizing 980 nm coupled 1973 nm synergistic excitation. Unlike typical single wavelength excitation, the synergistic excitation may affect population pathways of the excited‐state level of Er3+ ion by adjusting excitation wavelength and power density, resulting in a dynamically adjustable change in luminescence color output. Notably, multicolor luminescence involving green, chartreuse, yellow, orange, and red can be tuned dynamically in the NaYF4:Er3+ single UCNPs by using the tunable 980/1973 nm synergistic excitation. This dynamic luminescence color variation from these UCNPs has demonstrated promising potential applications in volumetric color display. The results provide a new approach to achieve multicolor‐tunable upconversion luminescence at single nanoparticles level and open up the possibility of developing true three‐dimensional volumetric color display technologies with resolution at the nanometer range.

A risk-averse approach for distribution locational marginal price calculation in electrical distribution networks

As distributed generation (DG) systems continue reshaping power networks, optimizing pricing strategies at DG buses using the distribution locational marginal price (DLMP) concept becomes critical for economic efficiency and the optimal operation of the network. This paper proposes a novel approach that combines Information Gap Decision Theory (IGDT) and Particle Swarm Optimization (PSO) to address these challenges. IGDT offers a robust framework for optimizing pricing in the presence of uncertainties and incomplete information in the distribution network. It quantifies and models these uncertainties, enabling the creation of adaptable pricing strategies that respond effectively to changes in DG output and market conditions. To further refine pricing strategies, PSO is integrated into the IGDT framework. PSO's iterative approach allows for the discovery of optimal pricing parameters at DG buses, striking a balance between maximizing DG owner profits and ensuring system optimality. Extensive simulations on two realistic distribution network models validate the effectiveness of the proposed IGDT-PSO approach. It demonstrates that DG owners can reliably achieve their predefined profit targets while also adhering to the objectives of the distribution network.

A multi-model approach based on CARIMA-SARIMA-GPM for assessing the impacts of climate change on concentrated photovoltaic (CPV) potential

This research paper proposes a novel multi-model approach, integrating the CARIMA-SARIMA-GPM framework, to assess the combined impacts of climate change and land use change on the potential of concentrated photovoltaic (CPV) systems. By considering both climatic variables and land use patterns, this study aims to provide a comprehensive understanding of how these factors influence CPV performance in the context of a changing environment. The proposed methodology offers valuable insights into the future viability and sustainability of CPV technology, enabling informed decision-making for policymakers, energy planners, and investors in the Middle East and Africa. As a result, the ability of the hybrid evolutionary CARIMA-SARIMA-GPM to predict the potential of CPV energy output for assessing the impacts of climate change on it was investigated in Alice Springs, the Middle East, and Africa. The outcome showed that the hybrid model significantly outperformed the other machine learning approaches. The fitted model was used to assess the potential impacts of climate change on CPV generation in Alice Springs, Australia, as well as the Middle East's and Africa's comparable climatic conditions. According to the study, climate change had the greatest impact on solar CPV energy production in Alice Springs, where it decreased the most by 8.577% under moderate forcing scenarios (SSP245) during the boreal summer season; moderately in the Middle East, where it decreased the mode by 2.316% under mitigation scenarios (SSP126) during the boreal summer season; and extremely minimally in Africa, where it decreased the mode by 1.263% under the far future sequencing period (2051–2099). Climate change also increased solar CPV energy production significantly in the Middle East in the far future sequencing period (2051–2099), as well as in Alice Springs, Australia, and Africa in the near future sequencing period (2015–2050). The strongest forcing scenario (SSP585) increased by 7.644% during the boreal autumn season in Africa; moderately increased by 6.502% during the boreal spring season in the Middle East; and had the least beneficial effects in Alice Springs, Australia, with increases of 5.538% during the boreal winter season. On an annual basis, all three regions showed a similar trend. Climate change (CLC) and urban expansion (URE) were also investigated in the Middle East and Africa for their effects on changes in solar CPV energy output. URE had a greater impact in Africa than the Middle East under the effective scenario, with a URE value of 45.45% for Africa and 20.15% for the Middle East, whereas CLC had a greater impact in the Middle East than Africa, with a CLC value of 29.01% compared to 5.47% for Africa. CLC and CPV residual factors, on the other hand, have a greater impact in the Middle East than in Africa, with effects of 29.01% and 50.83%, respectively, compared to 5.47% and 49.09%. The potential difference that drives the remediation of specific pollutants lies in the application of advanced technologies and sustainable practices. By exploring innovative solutions, such as using renewable energy sources like concentrated photovoltaic (CPV) systems, we can effectively mitigate the impacts of climate change and land use changes on pollutant concentrations. These technologies have the potential to significantly reduce pollution levels and create a cleaner and healthier environment for future generations. Assessing the CPV potential in different regions like Alice Springs, Australia, the Middle East, and Africa allows us to identify areas with high solar energy resources that can be harnessed for efficient pollutant remediation. Implementing prompt climate mitigation and adaptation measures is crucial for achieving a net-zero energy transition in the Middle East and Africa by 2050. In this context, prioritizing solar energy as the primary source of renewable energy is imperative for successful low-carbon economic planning in these regions.

On Changes in Inputs and Outputs of Agricultural Mineral Nutrients (e. g. Ca, Mg, K and Si) in Finland Between 1950-75 - with Discussion on Problems and Solutions

On Changes in Inputs and Outputs of Agricultural Mineral Nutrients (e. g. Ca, Mg, K and Si) in Finland Between 1950-75 - with Discussion on Problems and Solutions

Target setting using an enhanced inverse DEA approach: application to Spanish universities

This paper proposes a non-oriented, non-radial Inverse Data Envelopment Analysis (InvDEA) approach for target setting. The changes of any input and output dimensions may be fixed. In addition to the corresponding multiobjective optimisation model, the approach includes a prior step that checks the feasibility of the input and output changes that are fixed and revises them if necessary. This Pre-InvDEA model uses Goal Programming (GP) and guarantees the feasibility of those changes. The approach also includes a Post-InvDEA multiobjective optimisation model to optimise the input and output changes given in order to guarantee that the computed target is efficient. The overall target-setting approach is conceived as an interactive process so that the three steps (Pre-InvDEA, InvDEA, and Post-InvDEA) may be run more than once until a satisfactory target is determined. The application of the proposed approach to computing efficient targets for Spanish universities is presented.

An intelligent ratiometric fluorescent assay based on MOF nanozyme-mediated tandem catalysis that guided by contrary logic circuit for highly sensitive sarcosine detection and smartphone-based portable sensing application

As the well-known test-indicator for early prostate cancer (PCa), sarcosine (SA) is closely related to the differential pathological process, which makes its accurate determination increasingly significant. Herein, we for the first time expanded the peroxidase (POD)-like property of facile-synthesized Zn-TCPP(Fe) MOF to fluorescent substrates and exploited it to ratiometric fluorescent (RF) sensing. By harnessing the effective catalytic oxidation of MOF nanozyme toward two fluorescent substrates (Scopoletin, SC; Amplex Red, AR) with contrary changes, and target-responsive (SA + SOx)/MOF/(SC + AR) tandem catalytic reaction, we constructed the first MOF nanozyme-based RF sensor for the quantitative determination of SA. Superior to previous works, the operation of this RF sensor is under the guidance of AND-(AND^NAND) contrary logic circuit. The dual-channel binary output changes (from 1/0 to 0/1) not only enable the intelligent logical recognition of SA, bringing strengthened reliability and accuracy, but also manifest the proof-of-concept discrimination of PCa individuals and healthy ones. Through recording the fluorescence alterations of SC (F465) and AR (F585), two segments of linear relationships between ratiometric values (F585/F465) and varied contents of SA are realized successfully. The LOD for SA could reach to as low as 39.98 nM, which outperforms all nanozyme-originated SA sensors reported till now. Moreover, this sensor also demonstrates high selectivity and satisfactory performance in human serum samples. Furthermore, the portable sensing of SA is realized under the assistance of smartphone-based RGB analysis, demonstrating the potential of point-of-care diagnostics of PCa in the future.

Climatic sensitivity of seasonal ice-cover, water temperature and biogeochemical cycling in Lake 239 of the Experimental Lakes Area (ELA), Ontario, Canada

Regional climate plays an important role on in-lake physical and biogeochemical processes and determines the state of water quality and ecology of the lakes. This paper presents the result of a one-dimensional numerical modelling of lake ice cover, water temperature, as well as nutrient and phytoplankton dynamics in Lake 239 (Rawson Lake) located in the Experimental Lakes Area (ELA), Ontario, Canada. Using observed meteorological and inflow/outflow data, the Multi-year Lake simulation model (MyLake) was setup to replicate measured lake water temperature, ice-cover, dissolved organic carbon, particulate and dissolved phosphorus, and chlorophyll-a concentrations over the entire depth of the lake. The sensitivity of the lake to changes in climatic drivers, specifically to changes in surface air temperature and wind speed, was examined by incrementally changing the model input forcing for temperature and wind speed and mapping the resulting changes in the simulated outputs. The results show that lake processes are generally as sensitive to changes in wind speed as they are to changes in air temperature. Simulated changes in lake variables corresponding to projected changes in Global Climate Models (GCMs) under RCP4.5 and RCP8.5 emission scenarios reveal a general increase in lake water temperature and the corresponding decrease in lake ice thickness and ice cover duration under the changing climate. While lake water temperature increases at all depths, the shallow epilimnion layer is more sensitive to the changing climate than the deeper hypolimnion layer, reaching mean annual change value of +3.7 °C for RCP 8.5 and the 2090s as compared to the 1990s baseline period. While the simulated change in lake ice thickness reaches −20 cm by 2090s for the RCP 8.5 scenario, the corresponding change in ice-cover duration reaches -47 days. These changes are shown to result in seasonal changes in the biogeochemical cycling over the depth of the lake with projected increases in chlorophyll-a concentration during ice covered season of December to May reaching up to +0.15 mg/m3 for RCP 8.5 and the 2090s followed by a decrease during open water season of June to November reaching −0.15 mg/m3 compared to the 1990s baseline period.

Simulation of a Hybrid System Wind Turbine-Battery-Ultracapacitor.

In order to improve the predictability of power generation from wind, short term energy storage in batteries combined with ultra capacitors (UCaps) is proposed. The system is simulated with SIMULINK and contains detailed models of a lead acid battery pack and a simple model of the UCap bank. The wind energy conversion system (WECS) is simulated by measured time series with a time resolution of one second. The objective of the simulation is to determinate the system configuration that is able to guarantee a predictable energy output to the grid during a given time interval. Within this time, the storage system should be able to compensate all type of rapid changes originated by wind speed fluctuations. Another important issue is the integration of an ultra capacitor bank. It is investigated its influence on the charge and discharge stress of the battery. It is demonstrated that quick changes in wind power generation can be covered by a reasonable size of battery capacity for a prediction time interval of 10 min. Very short transients in energy flow (1-10 s) are absorbed by the UCap bank which minimizes the deterioration of the battery because important current peaks do not reach the battery. The final system design is based on measurements at a 600 kW constant speed WECS. Its typical, very sharp changes in power output (more than 200 kW/s possible) are smoothed by a 500 Ah lead acid battery with 300 cells in series (voltage range: 480 – 720 V). In parallel to the battery a 10 F UCap bank is connected. To hold 720 V, the bank consists of 240 UCaps connected in series (3 V / 2400 F each).

Obstacles to the development of China's marine economy: Total factor productivity loss from resource mismatch

The total factor productivity (TFP) of the marine economy loss due to the resource mismatch remains a major obstacle to the development of China's marine economy. This study analyzes the intrinsic mechanism of the four types of capital mismatches, including natural, knowledge, social, and institutional, affecting the TFP of the marine economy. Firstly, the Stochastic Frontier Analysis model is used to obtain the TFP in 11 Chinese coastal provinces from 2000 to 2020. Then the four types of capital are unified into the HK model to study their spatio-temporal characteristics, and the extended Syrquin decomposition is used to analyze the sources of the changes in the marine economic output during the whole study period. At the same time, we estimate the output gap and the contribution of distortionary changes in each type of resource. Finally, we use Bootstrap to measure the impact of each type of resource mismatch on TFP. The results show that ① TFP is on the rise and belongs to the middle level. Nevertheless, there is a slow growth rate, noticeable regional differences, with a specific "path dependence". ② All capitals are distorted, and only the distortion coefficient of natural capital is greater than 1. Spatially, resources are under-allocated in the economic pioneer regions and over-allocated in the latecomer regions. ③ At present, China's marine economic growth is mainly driven by resource inputs. Correcting the inter-regional resource distortion can raise output by 21%. ④ The contribution of knowledge and social capital distortions is positive but small, while institutional and natural capital contribute more but fluctuate sharply. Resource allocation tends to be rationalized in Shanghai, Zhejiang, Fujian, Shandong, and Guangdong. ⑤ The mismatch of natural capital shows an “inverted U-shaped” trend, with 2006 as the "inflection point". The mismatch of knowledge, social, and institutional capital shows a decreasing trend and remains stable. Mismatch of all capitals harms the TFP of the marine economy, and institutional capital mismatch has the greatest impact. This assessment framework can measure the extent of other resource mismatches in other regions of the world, and the results of the study can provide lessons for localities to promote efficient resource allocation and enhance TFP in the marine economy.

Theta-tACS modulates cerebellar-related motor functions and cerebellar-cortical connectivity

ObjectiveTo evaluate the effects of cerebellar transcranial alternating current stimulation (tACS) delivered at cerebellar-resonant frequencies, i.e., theta (θ) and gamma (γ), on upper limb motor performance and cerebellum-primary motor cortex (M1) connectivity, as assessed by cerebellar-brain inhibition (CBI), in healthy subjects. MethodsParticipants underwent cerebellar-tACS while performing three cerebellar-dependent motor tasks: (i) rhythmic finger-tapping, (ii) arm reaching-to-grasp (‘grasping’) and (iii) arm reaching-to-point (‘pointing’) an object. Also, we evaluated possible changes in CBI during cerebellar-tACS. Resultsθ-tACS decreased movement regularity during the tapping task and increased the duration of the pointing task compared to sham- and γ-tACS. Additionally, θ-tACS increased the CBI effectiveness (greater inhibition). The effect of θ-tACS on movement rhythm correlated with CBI changes and less tapping regularity corresponded to greater CBI. ConclusionsCerebellar-tACS delivered at the θ frequency modulates cerebellar-related motor behavior and this effect is, at least in part, mediated by changes in the cerebellar inhibitory output onto M1. The effects of θ-tACS may be due to the modulation of cerebellar neurons that resonate to the θ rhythm. SignificanceThese findings contribute to a better understanding of the physiological mechanisms of motor control and provide new evidence on cerebellar non-invasive brain stimulation.

Methane output across life stages in sheep, how it differs from lambs to adult ewes using portable accumulation chambers.

Methane (CH4) produced from enteric fermentation is a potent greenhouse gas produced by ruminant animals. Multiple measurements are required across life stages to develop an understanding of how CH4 output changes throughout the animal's lifetime. The objectives of the current study were to estimate CH4 output across life stages in sheep and to investigate the relationship between CH4 output and dry matter (DM) intake (DMI). Data were generated on a total of 266 female Suffolk and Texel animals. Methane and carbon dioxide (CO2) output, estimated using portable accumulation chambers, and DMI, estimated using the n-alkane technique outdoors and using individual penning indoors, were quantified across the animal's life stage; as lambs (<12 mo), nulliparous hoggets (12 to 24 mo) and ewes (primiparous or greater; > 24 mo). Ewes were further classified as pregnant, lactating, and dry (non-pregnant and non-lactating). Multiple measurements were taken within and across the life stages of the same animals. A linear mixed model was used to determine if CH4 and CO2 output differed across life stages and using a separate linear mixed model the factors associated with CH4 output within each life stage were also investigated. Methane, CO2 output, and DMI differed by life stage (P < 0.05), with lactating ewes producing the greatest amount of CH4 (25.99 g CH4/d) and CO2 (1711.6 g CO2/d), while also having the highest DMI (2.18 kg DM/d). Methane output differed by live-weight of the animals across all life stages (P < 0.001). As ewe body condition score increased CH4 output declined (P < 0.05). Correlations between CH4 output measured across life stages ranged from 0.26 (SE 0.08; lambs and lactating ewes) to 0.59 (SE 0.06; hoggets and pregnant ewes), while correlations between CO2 output measured across life stages ranged from 0.12 (SE 0.06; lambs and hoggets) to 0.65 (SE 0.06; hoggets and lactating ewes). DMI was moderately correlated with CH4 (0.44; SE 0.04) and CO2 output (0.59; SE 0.03). Results from this study provide estimates of CH4 output across life stages in a pasture-based sheep production system and offer valuable information for the national inventory and the marginal abatement cost curve on the optimum time to target mitigation strategies.