Efficiency serves as a crucial metric in assessing the advancement of scientific research for universities. Reasonable inputs of human resources, finances, materials, and other resources, along with high-quality research output, are important guarantees for the research efficiency of Chinese universities. This study delves into the patterns of changes of research efficiency among universities across the 31 provinces and municipalities of China from 2012 to 2022. By scrutinizing input-output perspectives and utilizing data sourced from the China Statistical Yearbook, the analysis unveils prevailing scenarios of input redundancy and output insufficiency in research efficiency across universities. The static and dynamic trends in research efficiency were further investigated by employing a static non-parametric Data Envelopment Analysis (DEA)-BCC model and a dynamic Malmquist index. Key findings from the analysis from 2012 to 2022 include: (1) notable growth in investments in teaching, research equipment assets, and research and development funds among nationwide universities; (2) a steady increase in the mean value of technical efficiency (TE) from 0.97 to 0.99, indicating continuous enhancement in overall efficiency in research input resource allocation across the provinces; (3) the mean Malmquist productivity index of 1.285, with an average annual increase of 28.5%, signifying a consistent improvement in university research efficiency throughout the study period; and (4) the provinces experiencing varying degrees of input redundancy or output insufficiency were selected to suggest the need for tailored strategies in resource allocation. The study underscores the importance of a holistic evaluation system involving stakeholders from government, universities, and society to optimize research efficiency and promote scientific innovation and social development.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

Background: The modified Duke index derived from coronary computed tomography angiography (CCTA) was designed to predict cardiovascular outcomes based on the severity of coronary ste-nosis. However, it does not take into consideration the presence or severity of peri-coronary in-flammation. The peri-coronary fat attenuation index (FAI) is a novel imaging marker determined by CCTA which reflects the degree of inflammation in the coronary tree in patients with coronary artery disease. Purpose: To assess the association between the modified Duke index assessed by CCTA, cardiovascular risk factors and peri-coronary inflammation in the coronary arteries of pa-tients with coronary artery disease. Methods: One hundred seventy-two patients who underwent CCTA for typical angina were assigned into two groups based on the modified Duke index: group 1 – patients with low index ≤ 3 (n=107) and group 2 – patients with high index > 3 (n=65). Demo-graphic, clinical and CCTA data were collected for all patients, and FAI analysis of coronary in-flammation was performed. Results: Patients with increased values of the modified Duke index were significantly older compared to those with a low index (61.83 ± 9.89 vs. 64.78 ± 8.9; p = 0.002). No differences were found between the two groups in terms of gender distribution, hypertension, hypercholesterolemia or smoking history (all p > 0.5). The FAI score was significantly higher in patients from group 2, who presented a significantly higher score of inflammation compared to the patients in group 1, especially at the level of the right coronary artery (FAI score 20.85 ± 15.80 vs. 14.61 ± 16.66; p = 0.01 for the right coronary artery, 13.85 ± 8.04 vs. 10.91 ± 6.5; p = 0.01 for the circumflex artery, and 13.26 ±10.18 vs. 11.37 ± 8.84; p = 0.2 for the left anterior descending artery). CaRi-Heart® analysis identified a significantly higher risk of future events among patients with a high modified Duke index (34.84 % ± 25.86 % versus 16.87 % ± 15.80 %; p

Abstract: The VSI represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with Irritable Bowel Syndrome (IBS) and other Chronic Inflammatory Bowel Diseases (IBD). However, an Italian version of the instrument is not yet available for the reference population. This study utilized a national sample of 500 individuals, including healthy controls and patients with Ulcerative Colitis and Crohn's Disease, to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, the research applied a questionnaire and the VSI through an online format to 500 participants. Data analysis revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.95) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with other measures of anxiety and the severity of gastrointestinal symptoms, confirming its role in enhancing the understanding and management of IBS and IBD in Italy.

Annually, the oak forests of the Zagros Mountain chains, in western Iran and northeastern Iraq, face recurring challenges posed by forest fires, particularly in the Kurdo-Zagrosian forests situated in western Iran and northeastern Iraq. Assessing fire susceptibility relies significantly on vegetation condition. Integrating in situ data, Remote Sensing (RS) data, alongside the integration of Geographical Information Systems (GIS), presents a cost-effective and precise approach to capturing environmental conditions before, during, and after fire events, minimizing the need for extensive fieldwork. This study refines and applies the Zagros Grass Index (ZGI), a local vegetation index tailored to discern between grass-covered surfaces from tree canopies in Zagros forests, identifying the grass masses as the most flammable fuel type. Utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product as input, from 2013 to 2022, the ZGI aims to mitigate the influence of tree canopies, isolating NDVI values solely attributable to grass cover. By incorporating phenological characteristics of forest trees and grass species, the ZGI outperforms NDVI in mapping grass-covered areas that are crucial for fire susceptibility assessment in the study region. Results demonstrate a strong overlap between ZGI-based maps and recorded fire occurrences, validating the efficacy of the index in fire susceptibility estimation.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

Abstract: Field studies with large-stemmed plants Artemisia dubia (wormwood) have been carried out at Vėžaičiai Branch LAMMC since 2018. According to three years of experimental results, annual dry matter (DM) yield varied from 7.94 to 10.14 t ha-1. Growing conditions, nitrogen ap-plication level and harvesting time had significant impacts on Artemisia dubia productivity. This article presents the results of research on preparation and use of Artemisia dubia biomass for en-ergy conversion and evaluation of technological-technical and environmental parameters of these plants utilization for solid biofuel. For experiments were used 6 variants of Artemisia dubia samples, which were grown in 2021: plants were cut three times and two fertilization options were used: (1) no fertilization and (2) fertilization with 180 kg ha-1 of nitrogen fertilizer. These harvested plants were chopped, milled and were pressed into the pellets. The physi-cal-mechanical characteristics (mоisture content, density and strength) of Artemisia dubia pellets were investigated. During this study, it was found that the density in dry mass (DM) of pellets ranged from 1119.86 to 1192.44 kg m-3. The pellet moisture content ranged from 8.80 to 10.49%. After testing of pellet strength, it was found that the pellets which were made from plant bio-mass PK-1-1, were the most resistant to compression, they withstood 560.36 N of pressure. Dry fuel lower heating value (LHV) of pellets was sufficiently high and was very close to pine saw-dust pellets, it varied from 17.46±0.25 MJ kg-1 to 18.14±0.28 MJ kg-1. The ash content of burned pellets ranged from 3.62±0.02% to 6.47±0.09%. Emissions of harmful pollutants – CO2, CO, NOx and unburnt hydrocarbons (CxHy) did not exceed the maximum permissible levels. Summariz-ing the results of investigated properties, cоmbustion and emissiоns of Artemisia dubia pellets, it can be concluded that this biofuel can be used for production of pressed biofuel and it is charac-terized by sufficient high quality, efficient combustion and permissible emissions to the envi-ronment.

Climate change is challenging the agricultural sector worldwide. The pressure exerted by the altered thermal conditions drives the zonal shift for various cultivations. This study presents the multiyear analysis of the Growing Degree Days (GDD) index over the Northern Mediterranean Basin (NMB), focused on the high-value vine cultivation derived from the E-OBS dataset. To handle this extensive environmental dataset, R-language scripts and packages were applied, along with the capabilities of the GIS software. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas of GDD exceeding 2000 heat units. The extracted results specify the viticultural areas where the GDD index surpasses the suitable values for vine cultivation, owing to the increase of the thermal stress risk. In addition to mapping areas with GDD ≥ 2000, spatial calculations of the surface of areas meeting this criterion per country in the study area were made. In the northern parts of the NMB, the rise of the GDD index values indicates the establishment of vine plantations in the future.

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak and accumulated rainfall-based damage are likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (SWRI24−hr−S), derived from normalising the existing 24-hourly water resources index (WRI24−hr−S) in literature, to monitor flash flood risks on an hourly scale. The proposed SWRI24−hr−S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V) and peak (Q). The comprehensive result analysis establishes the practical utility of SWRI24−hr−S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data is available, offering crucial information for flood risk monitoring, assessment, and the development of effective mitigation strategies.

Recent analyses of cosmic microwave background surveys have revealed hints that there may be a non-trivial running of the running of the spectral index. If future experiments were to confirm these hints, it would prove a powerful discriminator of inflationary models, ruling out simple single field models. We discuss how isocurvature perturbations in multi-field models can be invoked to generate large runnings in a non-standard hierarchy, and find that a minimal model capable of practically realising this would be a two-field model with a non-canonical kinetic structure. We also consider alternative scenarios such as variable speed of light models and canonical quantum gravity effects and their implications for runnings of the spectral index.

In the paper the verification of forecasts of precipitation conditions measured by the standardized precipitation index SPI is presented. For the verification of categorical forecasts a contingency table was used. Standard verification measures were used for the SPI value forecast. The 30 day SPI moved every 10 days by 10 days was calculated in 2013-2015 from April to September on the basis of precipitation data from 35 meteorological stations in Poland. Predictions of the 30 day SPI were created in which precipitation was forecasted in the next 10 days (the SPI 10-day forecast) and 20 days (the SPI 20-day forecast). Both for the 10 and 20 days, the forecasts were skewed towards drier categories at the expense of wet categories. There was a good agreement between observed and 10-day forecast categories of precipitation. Less agreement is obtained for 20-day forecasts – these forecasts evidently “over-dry” the assessment of precipitation anomalies. The 10-day SPI value forecast accuracy is acceptable, whereas for the 20-day forecast is unsatisfactory. Both for the SPI categorical and the SPI value forecast, the 10-day SPI forecast is reliable and the 20-day forecast should be accepted with reservation and used with caution.

Aim: To investigate inflammation indices and erythropoietin (EPO) levels for their potential role in distinguishing polycythemia vera (PV) from secondary polycythemia (SP), and to compare different parameter combinations in terms of diagnostic accuracy. Methods: This retrospective cohort was created from patients assessed for polycythemia from January 2020 to December 2023. PV diagnosis was made according to the 2016 WHO criteria (n=145). Those who did not fulfill the criteria were defined as having SP (n=84). Results: NLR, PLR and SII were significantly higher in the PV group (p

This research aimed to investigate the relationship between climate policy uncertainty (CPU), clean energy (ENERGY), carbon emission allowance prices (CARBON), and Bitcoin returns (BTC) for the period from August 2012 to August 2022. The empirical analysis strategies utilized in this study included the Fourier Bootstrap ARDL long-term coefficient estimator, Fourier Granger Causality, and Fourier Toda Yamamoto Causality methods. Following the confirmation of cointegration among the variables, we observed a positive relationship between BTC and CARBON, a positive relationship between BTC and CPU, and a negative relationship between BTC and ENERGY. In terms of causal associations, we identified one-way causality running from CARBON to BTC, BTC to CPU, and BTC to the ENERGY variable. The study underscores the potential benefits and revenue opportunities for investors seeking diversified investment strategies in light of climate change concerns. Furthermore, it suggests actionable strategies for policymakers, such as implementing carbon taxes and educational campaigns, to foster a transition towards clean energy sources within the cryptocurrency mining sector and thereby mitigate environmental impacts.

Taeniid infections pose a significant threat to both animal and public health, as certain tapeworms within this group can also infect humans, potentially leading to severe health conditions. Therefore, this calls for preventive and control measures, such as regular deworming of dogs. While the efficacy of deworming has been established in developed countries, there is a paucity of reported deworming practices in rural areas of developing countries, such as Tanzania. This study aims to understand determinants for helminth treatment-seeking behavior towards control of cestodial taeniid infections in rural settings in northern Tanzania. A cross-sectional study was undertaken in agropastoral and pastoral areas of northern Tanzania. Comprehensive data from household surveys in selected sub-villages were collected to ascertain dog ownership, dog deworming practices, and the availability of dewormers. Analytical methods were employed to discern how various determinants influenced deworming practices among dog owners in these communities. Awareness of dewormers specifically formulated for dogs emerged as a pivotal factor affecting dog deworming practices. Dog owners who were informed about appropriate dog dewormers were nearly two times more likely to engage in deworming compared to those with limited knowledge (OR = 1.78, 95% CI 1.77 - 4.18, p < 0.001). A majority 32(51.6%, 95% CI: 38.7-64.3) acknowledged accessing dewormers for livestock within their wards. Praziquantel a potent dewormer on cestodes was least known to most dog owners 2(13%, 95% CI: 2.3-41.6). Praziquantel, a potent and common dewormer effective against cestodial taeniid infections, remains relatively unknown in rural areas of northern Tanzania. Therefore, more awareness on appropriate deworming agents against taeniids in dogs should be raised in rural dog-keeping communities.

Wheat is widely grown in the Mediterranean region, where plants frequently face water shortages. Recently, more attention to rationalizing irrigation water has been increased due to the adoption of sustainable agricultural systems. Therefore, two field trials were conducted at the Agriculture Research Station of Nubaria, Egypt, in two consecutive seasons (2017/2018 and 2018/2019) to examine three irrigation regimes' effects, i.e., 60, 80, and 100% of crop evapotranspiration (ETc) combined with foliar ascorbic acid (AsA) or vitamin B2 (VB2) on yield and water productivity of wheat in two separate experiments. A split-plot design was used with three replicates. Irrigation treatments occupied the main plots, while the subplot in the first experiment was placed by ascorbic acid (AsA) and vitamin B2 in the second experiment. Results indicated that 100% ETc produced higher wheat yield and its attributes and insignificantly surpassed 80% ETc. Compared to the unsprayed plots, the foliar application of 6 mM ascorbic acid or 2.0 mM vitamin B2 significantly increased grain yield, components, and water use efficiency. The interaction between irrigation regimes (100% ETc or 80% ETc) and foliar application of 6.0 mM ascorbic acid or 2.0 mM vitamin B2 resulted in the highest values with no significant difference. Foliar application of ascorbic acid or vitamin B2 saved 20% of irrigation water while yielding a reduction that did not exceed 10%. The biplot graph of treatments x traits (TT) was a useful statistical tool for examining the impact of treatments on yield and its characteristics and identifying the links between these factors. Results suggest that riboflavin or ascorbic acid may have a potential role as an effective antioxidant for enhancing the tolerance for drought stress in wheat.

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. There are many studies focused on flood impact assessments for administrative districts but fewer on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and rainfall data, combined with crop growing season data to construct a crop flood damage assessment index (CFAI). First, an analytic hierarchy process (AHP) was used to assign weights to the impact factors; then, the weighted composite score method was used to calculate the CFAI; and finally, the impact was classified as slight, moderate, or severe based on the magnitude of the CFAI . This method was used for the Missouri River floods of 2019 in the U.S. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to validate the results. The combined approach achieved a high degree of consistency in spatial distribution. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.

There is a need for alternatives or complements to synthetic fertilizers to enhance agricultural sustainability. Applying organic amendments can play a significant role in this. Insect droppings show high potential, though studies evaluating their agronomic value have only recently begun to emerge. This study compared black soldier fly (Hermetia illucens) and mealworm (Tenebrio molitor) larvae frass with another organic amendment (Nutrimais) derived from composting forestry, agro-industrial, and domestic waste. The experiment also included ammonium nitrate at two rates [the same as the organic amendments, 50 kg ha–1 nitrogen (N) (FullR), and half that rate (HalfR)] and an unfertilized control. The study spanned two growth cycles of lettuce (Lactuca sativa L.) grown in pots, followed by unfertilized oats (Avena sativa L.) to assess the residual effects of the fertilizing treatments. Mealworm larvae frass mineralized rapidly, with an apparent N recovery of 37.4% over the two lettuce growth cycles, indicating its high availability to soil heterotrophic microorganisms. The average dry matter yield (DMY) of lettuce was the highest among all treatments (12.8 and 9.8 g plant–1 in the first and second lettuce cycles), even compared to the FullR treatment (12.2 and 7.8 g plant–1), though without significant differences. Although mealworm larvae frass exhibited a high mineralization rate, the DMY cannot be attributed solely to N supply, as plants in the FullR treatment showed better N nutritional status. Mealworm larvae frass provided strong evidence of a plant biostimulant effect, not explained by the variables measured in this study. Black soldier fly larvae frass exhibited typical behavior of a moderately reactive organic amendment, while Nutrimais showed low reactivity, with a near-neutral mineralization/immobilization balance. The results suggest mealworm larvae frass is recommended for early maturing vegetable crops, whereas Nutrimais appears more suitable for perennial crops with low short-term nutrient requirements.

The fetal splenic artery pulsatility index (PI) is a parameter that reflects fetal well-being and has been used as a predictor of adverse pregnancy outcomes. The aim of this study was to investigate the predictive value of splenic artery PI in GDM class A1 cases for NICU admission. In this prospective case controlled study, only sixty single pregnancy cases diagnosed with gestational diabetes mellitus class A1 were evaluated. Fetal splenic artery Doppler parameters Peak systolic velocity (PSV), Pulsatility index (PI), Resistivity index (RI) and End diastolic velocity (EDV) were measured in all cases. The rate of re-quirement of need of neanoatal intensive care unit was noted. In cases with need fetal intensive care, fetal splenic PI index was found to be statistically significantly lower than in healthy cases without it (0.94 ± 0.29 vs. 1.70 ± 0.53, respectively, p

Surface water distribution extracted from remote sensing data has been used in water resource assessment, coastal management, and environmental change studies. Traditional manual methods for extracting water bodies cannot satisfy the requirements for mass processing of remote sensing data; therefore, accurate automated extraction of such water bodies has remained a challenge. The histogram bimodal method (HBM) is a frequently used objective tool for threshold selection in image segmentation. The threshold is determined by seeking twin peaks, and the valley values between them; however, automatically calculating the threshold is difficult because complex surfaces and image noise which lead to not perfect twin peaks (single or multiple peaks). We developed an operational automated water extraction method, the modified histogram bimodal method (MHBM). The MHBM defines the threshold range of water extraction through mass static data; therefore, it does not require the identification of twin histogram peaks. It then seeks the minimum values in the threshold range to achieve automated threshold. We calibrated the MHBM for many lakes in China using Landsat 8 Operational Land Imager (OLI) images, for which the relative error (RE) and squared correlation coefficient (R2) for threshold accuracy were found to be 2.1% and 0.96, respectively. The RE and root-mean-square error (RMSE) for the area accuracy of MHBM were 0.59% and 7.4 km2. The results show that the MHBM could easily be applied to mass time-series remote sensing data to calculate water thresholds within water index images and successfully extract the spatial distribution of large water bodies automatically.

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

Abstract: Doppler renal resistive index (RRI) has been used for several decades as a potential indi-cator for renal disease and progression. In recent years, RRI has emerged as a useful prognostic indicator for a range of co-morbidities in patients who are acutely unwell and as a potential marker for sub-clinical acute kidney injury (AKI) and post procedural AKI risk. Despite this, the clinical and theoretical determinants of RRI are poorly understood and remain contentious. Method: A narrative review of studies exploring the theoretical, experimental, and clinical evidence for factors affecting RRI. No date restrictions were set. Findings: Both experimental and clinical data confirm that RRI is markedly affected by a range of systemic and renal determinants and is influenced closely by the underlying risk factors and sys-temic vascular changes that lead to progressive renal damage. Discussion: This paper provides an overview of the key haemodynamic determinants of renal re-sistive index and aims to clarify their relative importance. With reference to a simplified theoretical model, evidence from experimental and clinical studies is reviewed. Pathophysiological factors and patient characteristics that influence RRI are explored to provide a better understanding of why RRI values change in the presence of common or complex pathologies. Conclusion: By gaining a better understanding of the complex systemic and renal factors that influ-ence RRI, ultrasound users will be better prepared to understand and interpret changes in RRI across a range of patient presentations.

The present work studies the concept of productivity in shipbuilding and how it should be measured. The existing metrics, shipbuilding process and shipyard organization were studies in order to choose the most adequate metrics which would allow the measuring of a shipyard productivity in a systematic and holistic way. This is achieved by gathering the man-hours spent in each ship organized by cost centre and using Compensated Gross Tonnages as the measure of output from the shipyard. Data was gathered for thirty ships built in the same European yard organized by cost centre. From the data collected it was found that the ratio of hours spent in outfitting to the hours spent in structures is proportional to the complexity of the ship. There was also opportunity to study the work reduction resulting from building ships in series and the shares of labour for ships series and across ship types.

This paper proposes an upper bound for mine productivity and also a simple truck dispatch rule that demonstrates how tight the upper bound can be using simulation. It also proposes a greedy search to approximate the productivity upper bound, which is faster and often exact. Uncertainty is added to the simulation in order to verify how the productivity responds to it. Typically, the productivity upper bound is less tight close to its saturation point as a function of the number of trucks, where adding more trucks only increases queues. Furthermore, more uncertainty in the model typically leads to a less tight upper bound. The results are conducted using real data from an open pit mine in Brazil.

COPD is currently the fourth leading cause of death in the world. Globally, due to continued exposure to COPD risk factors and an aging population, the burden of COPD is expected to increase in the coming decades. The BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index is a practical and multidimensional predictor for prognosis of COPD, and better than FEV1.We used the database of Kaohsiung Chang Gung Memorial Hospital medical center, Taiwan to analyze the correlation between BODE index, healthcare resource utilization, and Charlson comorbidity index (CCI). This retrospective study to collect COPD patients with complete BODE index data who had undergone a 6-minute walk examination in our hospital from January 2015 to December 2016. The medical cost and comorbidities database were analyzed from January 1, 2015, to August 31, 2017. Of 396 patients, 382 (96.5%) were male, with an average age of 71.3 ± 8.4 years. There was a significant association between the BODE index and the CCI of COPD patients (p < 0.001). Healthcare resource utilization was positively correlated with the BODE index during the 32 months of retrospective clinical outcomes: positively correlated with the number of hospitalizations (p<0.001), hospitalization days (p<0.001), hospitalization expenses (p=0.005), and total medical expenses (p=0.024), respectively. Our findings provide the crucial information for clinician to predict medical burden and comorbidities in patients with COPD by using BODE index.

This study aimed to identify the most beneficial attitudes adopted by enterprise participants during their engagement in open-source software (OSS) activities. For this purpose, we selected repositories from GitHub, featuring the top 10 with the highest stars and forks, classified the participants according to their sentiment states, and compared their productivity. The results indicated that participants with positive sentiments were more productive than those with negative sentiments. Consequently, it can be inferred that encouraging organizations to express positive sentiments towards their developers publicly may stimulate OSS community activities and enhance productivity, thereby potentially leading to increased open innovation and sustainability.

The plant productivity-richness relationship (PPR) is one of the most debated and important issues in ecology. There have been distinct stages in the research of this issue, including the discovery of the different PPR shapes, respective tests of influencing processes, and integrative research with vegetation investigation, manipulation experiments, and theoretical analysis. The debate largely focuses on what the dominant shapes and underlying mechanisms are. Recent integrative research works following analyses of respective processes affecting PPR have found that the humped, asymptotic, positive, negative, and irregular shapes of PPR are linked to each other. One shape of PPR may change into another. The balance between positive and negative processes determines the different shapes of PPR. Plant diversity has a globally positive effect on plant productivity.

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

Objective: This paper aims to test and evaluate the Effect of Discipline And Work Environment on Employee Productivity of state-owned public bodies.Design/methodology/approach: This paper uses a quantitative approach using a survey approach. The survey is a study conducted on the employee population of state-owned public agency companies, samples taken from the employee population of state-owned public agency companies to find events related to discipline variables and work environments that can affect employee productivity variables, to analise the influence between discipline variables and the work environment on employee productivity variables using a statistic regression approach. This method is used to explain the influence of discipline variables and work environment on employee productivity variables. This approach is simply to provide a description and test the influence between discipline variables and the work environment on employee productivity variables that can be known how much the influence of discipline variables and work environment on employee productivity variables.Findings: The findings of this study explain that discipline has an influence on the productivity of employees of publicly owned companies, the work environment has an influence on the productivity of employees of publicly owned companies, while together discipline and work environment have an influence on the productivity of employees of publicly owned companies.Practical Implications: The results of the study are recommended for employees to improve the effectiveness and efficiency of the performance of state-owned public bodies.Originality: Previous research conducted to test the influence of discipline and work environment on the productivity of employees of manufacturing companies listed on the Indonesia Stock Exchange, the findings concluded that discipline and work environment have an influence on the work productivity of employees of manufacturing companies listed on the Indonesia Stock Exchange. This research object of research on publicly owned companies owned by the state.

Droughts are a common occurrence in various climates and are primarily caused by a prolonged decrease in rainfall. Several factors contribute to droughts, including temperature, wind speed, relative humidity, rainfall timing, amount, and intensity during the growing season. The objective of this study is to establish a new index, named soil moisture and evapotranspiration revealed drought index (SERDI), for displaying dry and wet conditions based on combining both soil moisture and evapotranspiration (Penman-Monteith) to improve drought early warning and its severity globally. For validation of the SERDI with other indices such as LST, VHI, NDVI, and NDWI, different ways used such as R-square, RMSE, MAPE, and P-value to estimate the accuracy, variability of data, the forecast conditions, and how the significance of data. The results showed that the low RMSE and high r² were found between SERDI with LST and VHI. In contrast, the low R- square and high RMSE were between SERDI with NDVI and NDWI in most of the semi-arid areas. Furthermore, most of the semi-arid areas from Iran, Iraq, Syria, Jordan, and Israel experienced moderate and severe dry conditions, except some parts of these regions had normal conditions in Iran and Syria. The SERDI analysis revealed a strong correlation between (LST) and a moderate correlation with (VHI) across all study areas. However, the relationship between other indices, like (NDWI) and (NDVI), varied depending on the regions. To conclude, SERDI can be used globally for detecting drought based on soil moisture and evapotranspiration.

Protein hydrolysates are plant biostimulants containing amino acids, oligopeptides, and peptides in their composition. When supplied to plants, protein hydrolisates (PH) have been identified to improve nitrogen metabolism, enhance the activity of antioxidant enzymes, boost plant defence response to stresses, and positively impact the quantity and quality of products. Soybean is a crucial global commodity, with nitrogen being the primary nutrient for crop development as it directly affects productivity. This study aimed to evaluate the effect of a HP-based biostimulant on the N metabolism in nodulated soybean plants and their productivity. A greenhouse experiment was conducted to test two modes of application of the 0.20% HP-based biostimulant. Soybean plants, growing in pots, were treated with HP 0.20% either via seed treatment or foliar application (at growth stages V3 and V5). Activities of enzymes and compounds related to N metabolism, gene expression, and productivity components were analysed. It was observed that the mode of application did not significantly influence the results. The application of HP increased the concentration of nitrate, amino acids, and ureides in soybean leaves. It also positively altered the expression of genes such as nitrate reductase, urease, and asparagine. Additionally, it enhanced productivity, resulting in plants with a greater number and weight of pods and grains. Therefore, it is possible to consider HP as a stimulator for increasing soybean productivity, even under non-stressing conditions.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

Rice production is important for global food security but given its large water footprint, efficient irrigation management strategies need to be developed. Expansion of rice growing area is larger than any other crop in Africa due to increasing demand for rice. Three rice irrigation management alternatives with the system of rice intensification (SRI) were field-evaluated against the conventional continuously flooded system (CF) in Tanzania. Production systems included: (1) CF (50 mm ponding depth for the entire season); (2) SRI (40 mm ponding for 3 days and no irrigation for next 5 days); (3) 80% SRI (80% of the SRI ponding); and (4) 50% SRI (50% of the SRI ponding). Experimental evaluation of the four systems was conducted for both wet and dry seasons. For the dry season, the SRI and 80% SRI produced higher yields of 9.68 tons/ha and 11.45 tons/ha and saved 26% and 35% of water, respectively compared to the CF (8.69 tons/ha). The yield advantage of the 80% SRI and SRI over the CF was less during the wet season with 6.01 tons/ha and 5.99 tons/ha of production, and water savings of 30% and 14%, respectively compared to the CF (5.64 tons/ha). The 50% SRI had lowest yield of all for both seasons, 7.48 tons/ha and 4.99 tons/ha for the dry and wet seasons, respectively. Statistically, the 80% SRI treatment outperformed all other treatments over the two seasons with an additional yield of 1.57 tons/ha and 33% (345 mm) water savings compared to the CF. Economic productivity of water (US$/ha-cm) over two seasons was highest for the 80% SRI ($20.27/ha-cm), while it was lowest for the CF ($12.89/ha-cm). Water saved by converting from the CF to the 80% SRI (1.98 million ha-cm) can support a 50% expansion in the current rice irrigated area in Tanzania. Even without irrigation expansion, the 80% SRI can increase rice production by 1.5 million tons annually while enhancing water availability for industrial and environmental uses (e.g., ecological preserves) and help achieve food security in Tanzania and the greater sub-Saharan Africa.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Over the past few decades, there have been major advances in crop productivity across the world, which has been made possible through a combination of productivity enhancing technological innovations. Beyond this achievement however, most parts of Africa are still battling with low crop productivity resulting in food shortages and food insecurity. The yields of many staple crops are still far below their agronomic potentials with output increases being attributed largely to area expansion. This paper examines the implications of the current trends of crop/plant productivity for food security and rural livelihood development in Africa using Ghana as a case study. The paper argues that crop production in Africa is becoming a less viable and unattractive livelihood activity with farmers diversifying out of agriculture into non-agricultural activities such as illegal small-scale mining, which have negative consequences on the ability of African countries to attain the Sustainable Development Goals (SDGs).

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Innovation and technology are important tools of minerals sector efficiency and productivity im-provement. The uptake of technologies has proven important levelrs to improve the productivity of mining sector. This paper provides a comprehensive analysis of mine-level productivity by using a global data of copper, gold, and platinum from 1991-2020. Various drivers of proioductivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in technical efficiency and productivity across mines and regions. A further decomposition of TFP into its different components suggest that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities. The findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in productivity in different commodities (e.g., South Africa vs. Zimbabwe) give policymakers with insights into how to support production scale and productivity through appropriate input mixtures.

While L-PBF offers advantages in terms of geometrical freedom or lightweight construction, its use is often limited by economic constraints or currently achievable part costs. With an anticipated increase of L-PBF machine productivity during the next years, an increase of the share of material costs and the share of non-productive time for powder layer application process is to be expected. This results in a demand for less expensive powder materials and advanced processing strategies for the short-and medium-term advancement of L-PBF. As one possible approach, the processing of gas- and water atomized stainless steel (316L) powders with different morphology and particle size distribution as well as their impact on L-PBF productivity is investigated. The actual powder applicability in L-PBF systems and the L-PBF processability determines the minimum necessary powder quality. The main focus of the presented work is put on the interaction between powder quality, powder layer properties, part quality and cost-effectiveness of the L-PBF process. To this end, the influence of the gas and water-atomized powder properties (particle size and morphology) during the powder layer application process at highest possible powder recoater speeds and the resulting powder bed properties (powder layer density, powder bed density, powder demixing) and part properties (part density and tensile strength) is investigated.

The Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, it is worthwhile assessing its characteristics. The WAI was distributed online among the workers of a healthcare company; the results were compared with data contained in the workers' personal health records and with absence registers. 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in colleagues due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to overreport illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.

This paper explores strategies for fostering efficient vocal communication and collaboration between human workers and collaborative robots (cobots) in assembly processes. Vocal communication enables division of attention of the worker, as it frees the visual attention, and the worker’s hands, dedicated to the task at hand. Speech generation and speech recognition are pre-requisites for effective vocal communication. The study focuses on cobot assistive tasks, where the human is in charge of the work and performs the main tasks while the cobot assists the worker in various peripheral jobs, such as bringing tools, parts, or materials, and returning them, or disposing them; or screwing or packaging the products. A nuanced understanding is necessary for understanding how human-robot interactions can be optimized to enhance overall productivity and safety. Through a comprehensive review of relevant literature and empirical studies, this manuscript identifies key factors influencing successful vocal communication, and proposes practical strategies for implementation.

Background: Research articles are essential for describing new ideas, techniques, and procedures and consolidating concepts. It creates an opportunity to expose studies and publicly assimilate published knowledge. Therefore, one of them is the most used and accepted index to verify the author’s scientific impact is the H-index or Hirsch index. It provides a robust single metric that combines quality and quantity. Therefore, it presents disadvantages, (1) researchers with shorter scientific carriers may have fewer articles and citations than those with longer scientific life; (2) it allows scientists to receive citations even if no new papers are published; (3) it is only useful for comparing the better scientists in a field; (4) this indicator can never decrease; (5) it is only weakly sensitive to the number of citations received; (6) the major and minor (or no) contributor in the research gained equal h-index. Then, the H-index ignores the total of citations and the time of a researcher's experience (“scientific age” [sa]). Objective: Thus, the goal of this study was to present a new index system (GFsa index ©) based on the two variables completely forgotten (total of citations and “scientific age”), introducing a new terminology “scientific age”, to evaluate the best-ranked researchers in Dentistry. Methods: The AD Scientific Index was used, and all researchers included in this study were cited in the AD Scientific Index (2024) in the Dentistry field and had the Google Scholar page accessible for a consultation to manually obtain the total of citations and calculate the “scientific age”. The information was retrieved by two authors (G.V.O.F. and J.C.H.F.), who assessed the data twice to avoid errors or mistakes. For inclusion: a minimum H-index value of 30; for exclusion: (i) the author did not have a Google Scholar page; (ii) duplicated author; or (iii) presented any suspicious activities about manipulation of articles. Then, a dataset of all researchers who were reported in Dentistry was prepared (name, H-index, i10 index, and publications). The formula developed and applied was GFsa=(total number of citations)/(“scientific age)². The Pearson correlation statistically evaluated the data obtained; the confidence interval was 95%. Results: A total of 9,093 researchers in Dentistry were recorded, of whom 1,020 were included. Then, we collected all 1,020 researchers' Google Scholar data (publications, citations, and indexes), and each researcher's total citations and “scientific age” were registered and calculated. The mean “scientific age” registered was 34.18 ± 13.34 (standard error of mean = 0.4181). With this information and data collected, GFsa index © was calculated, presenting a minimum value of 0.2186 and a maximum of 154.8 (mean = 10.33 ± 11.82; standard error of mean = 0.3706). Then, the data was organized and sorted following the ranking obtained in the GFsa index ©. The Pearson correlation showed that the H-index had a weakly positive association with the researcher’s “scientific age”; this fact means that the H-index will increase according to the “scientific age” increase. Otherwise, a moderately negative correlation between GFsa and “scientific age” was demonstrated, whereby a higher GFsa © had a lower “Scientific age”. This assessment shows that the variables introduced were fairly used. Moreover, a positive correlation was observed between both indexes (H-index and GFsa). Conclusion: It is possible to conclude that the new variable reported (“Scientific age”) and using the total citations brought a fairer and more feasible evaluation among the researchers. Thus, we are launching the new GFsa index © and the new information named “Scientific age” for the first time in the literature. The future perspective of the GFsa © application will be (1) the evaluation of the 9,093 researchers in Dentistry (total initially registered), including more authors/researchers in the Dentistry field, (2) expanding the exposition of this new index for other areas of the knowledge, and (3) provide free access of all data through the website (http://gfindex.us.to).

This paper initiates the study of the mathematical aspects of the ad-hoc Lanzhou index. If G is a graph with the vertex set {x1,⋯,xn}, then the ad-hoc Lanzhou index of G is defined by Lz¯(G)=∑i=1ndi(n−1−di)2, where di represents the degree of the vertex xi. Several identities for the ad-hoc Lanzhou index, involving some existing topological indices are established. The problems of finding graphs with the extremum values of the ad-hoc Lanzhou index from the following sets of graphs are also attacked: (i) set of all connected ξ-cyclic graphs of a fixed order, (ii) set of all connected molecular ξ-cyclic graphs of a fixed order, (iii) set of all graphs of a fixed order, (iv) set of all connected molecular graphs of a fixed order.

In geotechnical engineering applications, it is very important to obtain the undrained shear strength of remolded soils accurately and reliably. This study aims to obtain a trustworthy solution to determine the undrained shear strength of remolded clay mixtures using Atterberg limit test results in various states of consistency. An experimental study was carried out involving a wide range of clay mixtures of varying plasticity and geological origin. In the analyses, the variation of the remolded undrained shear strength depending on the cone penetration depth, water content, flow index, liquidity index and log liquidity index were investigated. In the study, the highest undrained shear strength of 100% Na-montmorillonite (NaM) was obtained at 171.89 kPa at 56.60% water content, while the lowest undrained shear strength was obtained for 100% Sepiolite (S), 9.28 kPa at 31.65% water content. The results of this study revealed that the shear strength is significantly affected by soil conditions, rather than dominant clay mineral. Besides, it was observed that the undrained shear strength at the plastic limit was approximately 30-35 times greater than that at liquid limit. The equations of liquid limit-flow index and plasticity index- flow index were proposed. It was concluded that the interdependence between undrained shear strength, liquidity index, log liquidity index, and flow index is not unique due to the different physical and chemical properties of clays.

The objective of the present work was to determine the productivity and costs of timber harvesting and skidding during the first commercial thinning of a Scots pine stand. The analyzed harvesting set consisted of a mini-excavator (34 kW) with an stroke harvester head (gripping range: 4–30 cm), and a farm tractor coupled to an logging trailer with a hydraulic crane. Merchantable timber (roundwood with a minimum diameter of 5 cm inside bark) was harvested from a 25-year old planted Scots pine stand growing on a grid of 1.4×1.8 m. The study showed the productivity of the mini-harvester range from 3.09 to 3.47 m3∙PMH15 -1, and that of the forwarding set to be 4.07 m3∙PMH15 -1. The analyzed model of productivity as a function of individual tree volume and thinning intensity was statistically significant, but the intensity parameter was significant only on plots located along wide access trails (3.7 m) and insignificant on plots located along the narrow access trial (2.5m). The intertree distance was not found to be significant. The calculated net machine costs for the forwarding set and mini-harvester were 36.12 Euro∙PMH 1 and 52.47 Euro∙PMH-1, respectively. An increase in the utilization rate of the harvesting set to 80% would reduce the timber harvesting and skidding costs to 22.07 Euro∙m-3.

The aim of this report is to evaluate the segmental rib index (RI) from T1-T12 spinal level in mild and moderate idiopathic scoliosis (IS) curves of thoracic, thoracolumbar and lumbar type by gender. The relationship of segmental RI to the frontal plane radiological deformity presented as the Cobb angle and to the posterior truncal surface deformity presented as the scoliometric readings of Angle of Trunk Rotation (ATR) in these patients is also assessed. Any statistical significant rela-tionship of these parameters would be very important for biomechanical relations of the rib cage (RC) deformity presented as the rib hump deformity (RHD) and the deformity in the spine and it would thus provide valuable information about scoliogeny. The segmental rib index (RI) is presented in 83 boys and girls with mild and moderate IS. The measurements include the scoliometric readings for truncal asymmetry (TA), the Cobb angle assessment and the segmental RI from T1-T12. The statistical package SPSS 23 was used for statistical analysis. The TA is documented and the Cobb angle is presented by gender and curve type. The segmental RI of thoracic, thoracolumbar and lumbar curves are presented for the first time. The correlations of the segmental RI to surface deformity presented as the rib hump deformity (RHD) in all IS patients and particularly in thoracic curves, to Cobb angle by gender and age and the comparison of the segmental RI index of asymmetric but not scoliotic children to the scoliotic peers by curve (in thoracic, thoracolumbar, lumbar curves) in boys and girls are presented. The findings emphasize the significant protagonistic role of the thoracic asymmetry in relation to the spinal deformity mainly in girls for the thoracic and in boys for the thoracolumbar curves. The cut-off point of age of the examined scoliotics is 14 years, that is when the RI shows stronger correlation with the spinal deformity, namely when the thoracic deformity is decisively effective to the developing thoracic spinal deformity, in terms of Cobb angle. In summary, the results of this study provide aetiological implications for IS, as far as the role of thorax is con-cerned.

The Metropolitan Economic Freedom Index (MEFI) ranks cities based on their support of free market enterprise. In its current state, MEFI purports to measure three constructs (government spending, taxation, and labor market freedom) with three equally weighted variables for each one, assuming perfect substitutability of variables. This study investigates the statistical consistency of MEFI through Confirmatory Factor Analysis. Multiple models investigate current variable selection by providing a potentially better indicator of labor market freedom, aggregation assumptions by removing the requirements for fixed and equal weights, and statistical consistency by evaluating the fit between the data and models. Results indicate that the current MEFI model is not statistically consistent with the data, that weighting of variables should not be equal, that variable selection should be investigated, and that constructs should be re-imagined. The models investigated provide an initial starting point for redefining MEFI.

Plant-microbe interactions are essential for ecosystem health and agricultural productivity. Metabolomics has revolutionized our understanding of these interactions by providing powerful methods to decipher the complex chemical signals involved. This review highlights the various metabolomics techniques used to study plant-microbe interactions, such as mass spectrometry, nuclear magnetic resonance spectroscopy, and advanced imaging technologies. We also discuss the role of contemporary bioinformatics tools, extensive databases, and the increasing influence of artificial intelligence and machine learning in the analysis of metabolomics data. Integrating metabolomics with other omics fields, including transcriptomics, proteomics, and metagenomics, allows for a comprehensive understanding of the molecular mechanisms underlying plant-microbe interactions. The review emphasizes the significance of fluxomics in elucidating the dynamic nature of metabolic networks. While there are challenges in data analysis, integration, and interpretation, metabolomics has profoundly expanded our knowledge of the role metabolites play in shaping plant-microbe interactions. As metabolomics technologies advance and integrate further with other omics approaches, we anticipate groundbreaking discoveries that will provide deeper insights into these complex interactions, ultimately leading to innovative strategies for sustainable agriculture and biotechnology.

Constructing an innovation system centered on new-quality productivity is key to achieving China's technological independence and high-quality development, especially against the backdrop of rapid advancements in artificial intelligence. This article utilizes provincial panel data from China spanning 2010 to 2022 and applies kernel density estimation and the Moran's I index to study the spatiotemporal evolution of artificial intelligence and new-quality productivity. The findings indicate a clustering trend in the development of both factors across regions. Causal empirical analysis using a two-way fixed-effects model reveals that artificial intelligence positively influences new-quality productivity, with conclusions validated by robustness and endogeneity tests.

The research employs both literature and experimental data to develop reasonable strategies for melon fly control. The objects of research were sierozem soils of the Zhanakorgan region (Kyzylorda region), bentonite clays of the Sauran region (Turkestan region), vermicompost obtained at the production site of the Research Institute "Ecology" at the International Kazakh-Turkish University named after Khoja Ahmed Yasawi. The competitive agent 'Vermiserbent' was developed by combining sulphur-perlite-containing waste (SPCW), vermicompost (VC), and natural bentonite clay. When incorporated into the soil, it serves as both an insecticide and a fertiliser recovery agent. Disinfection and enrichment of barren Sierozem soils in southern Kazakhstan could provide an eco-friendly approach to protect cucurbits (melon, watermelon, and pumpkin) against the melon fly. The average yield of watermelon treated with vermiserbent increased by 2.3 t/ha compared to the control, melon by 4.6 t/ha, pumpkin by 5.6 t/ha. The marketability of gourds as watermelons and melon after treatment with fertilizer increased by 1.2 times, and pumpkin by 1.1 times. The findings of studies conducted in agricultural fields in the Turkestan and Kyzylorda regions have shown that it is possible to produce environmentally sound gourds using a mixture of vermicompost, bentonite, and SPCW.

Key performance indicators are essential for any company to enhance its competitiveness. How-ever, a common issue is the manual collection of production data using record sheets, which are later digitized on desktop computers and processed in Excel sheets. Shockingly, 41% of companies in Mexico have no plans for digitalization. This work aims to develop a Real-time Productivity Indicator Monitoring System using Industry 4.0 technologies for a medium-sized manufacturing firm specializing in die-cutting automotive parts. The Advanced Quality Planning methodology was applied to develop the Conceptual, Product, and Process Engineering and its validation. The experimental tests demonstrated a reliability level of 99.98%, which exceeded initial expectations. The primary contributions presented in this work are related to the development of algorithms, communication protocols, data analysis, and general optimization of the calculation process. The study's only limitation was the short experimentation time.

Agricultural intensification increased crop productivity but simplified production with lower diversity of cropping systems, higher genetic uniformity, and a higher uniformity of agricultural landscapes. Associated detrimental effects on the environment and biodiversity as well as the resilience and adaptability of cropping systems to climate change are of growing concern. Crop diversification may stabilize productivity of cropping systems and reduce negative environmental impacts and loss of biodiversity, but a shared understanding of crop diversification including approaches towards a more systematic research is lacking. The current review highlights the use of Cropping Systems Diversification as an Approach to Enhancing Crop Productivity. Crop diversification can be considered as an attempt to increase the diversity of crops through, e.g. crop rotation, multiple cropping or intercropping, compared to specialized farming with the aim to improve the productivity, stability and delivery of ecosystem services. It can be one measure to develop more sustainable production systems, develop value-chains for minor crops. Crop diversification practices can include higher crop diversity, more diverse crop, mixed cropping; cultivation of grain legumes in otherwise cereal dominated systems, perennial leys or grassland and regionally adapted varieties or variety mixtures. Crop diversification and/or additional diversification measures like variation of seeding time or changing cropping patterns have the potential to lead to higher and more stable yields, increase profitability and lead to greater resilience of agro-ecosystems in the long term. These practices have the potential to make cropping systems more diverse in space, time and genetics. Through a balanced portfolio approach to agricultural sustainability, cropping system performance can be optimized in multiple dimensions, including food and biomass production, profit, energy use, pest management, and environmental impacts.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

Background: The accelerated ageing of the world's population will lead to an increase in the number of older persons in the workforce. Computerized Cognitive Training (CCT) is effective in improving cognitive outcomes, but its benefits for older workers remain controversial. We investigate the real-world efficacy of CCT in the workplace, focusing on employees aged 50+ years from a public sector agency. Methods: Case managers (N = 82) were randomized to either Intervention group (24 40-minute CCT sessions two times per week) or waiting list passive Control group. Cognitive ability, wellbeing, job satisfaction, and productivity outcome measures were collected assessed before and after CCT or comparable Control wait time. Results: Participants undergoing CCT improved on a task of executive functioning (p = 0.04). There was a trend toward change in work productivity after CCT (p = 0.09) with the Control group showing a significant decrease (p = 0.02), while the Intervention group remained stable. Conclusions: CCT during office hours has a positive effect on cognition and well-being without affecting the productivity among white-collar office workers. CCT could be considered as an intervention to support the older workforce in managing the cognitive and behavioral challenges of changing workplace demands.

With the growing trend of urbanization and the growing number of people migrating to cities, the demand for the development and construction of new buildings as well as the infrastructure has risen, meaning that the construction industry must adapt to the trends. The growing demands with shorter deadlines for an industry already known for high costs and not delivering on time means that productivity must be increased without increasing the cost. The solution for this might lie in the application of the Lean philosophy to the construction industry. This paper analyses the application of the Lean philosophy in order to increase the productivity in the airport construction site. The paper highlights the potential for enhancing productivity in construction workplaces by concurrently fostering continuous improvement and sustainability through the implementation of the A3 methodology and Lean principles, resulting in waste reduction and increased value.

Artificial Intelligence (AI) is an automation mechanism that runs in a computer system performing tasks that normally require human intelligence, such as visual perception, speech recognition, decision making or translation [1]. Some authors argue that recent developments in AI are leading to a wave of innovation in organizational design and changes to institutionalized norms of the workplace [2]. Techno-optimists even named this present phase the ‘second machine age’, arguing that it now involves the substitution of the human brain (Brynjolfsson and McAfee 2014). Potentially, the ability to apply AI in a generalized way can produce significant technical, economic and social effects in firms. But how many of these AI applications are ready and how far can they be from reaching the manufacturing industry market? The paper will answer the question: what are the implications on industrial productivity and employment in the automotive sector with the recent automation trends in Portugal? We will focus on AI as the most relevant emergent technology to understand the development of automation in areas related to robotics, software, and data communications in Europe (Moniz 2018). R&amp;D investments in industrial processes in general may reflect productivity improvements derived from the increased automation process. Our results will be based on case studies from the automotive and components sector combined with database search by keywords that signal intelligence automation developments and AI applications selected from national R&amp;D projects (on robotics, machine learning, collaborative tools, human-machine interaction, autonomous systems, etc) supported by European structural funds. The implications on industrial productivity and employment will be discussed in relation to automation trends in the automotive sector.

This review presents a comprehensive and systematic study of the field of bacterial plant biostimulants and considers the fundamental and innovative principles underlying this technology. Plant biostimulants are an important tool for modern agriculture as part of an integrated crop management (ICM) system; helping make agriculture more sustainable and resilient. Plant biostimulants contain substance(s) and/or microorganisms whose function when applied to plants or the rhizosphere, is to stimulate natural processes to enhance plant nutrient uptake, nutrient use efficiency, tolerance to abiotic stress, biocontrol, and crop quality. The use of plant biostimulants has gained substantial and significant heed worldwide as an environment-friendly alternative for sustainable agricultural production. Presently, there is an increasing curiosity of industry and researchers in microbial biostimulants especially, bacterial plant biostimulants (BPBs) to improve crop growth and productivity. The BPBs that are based on PGPR (plant growth-promoting rhizobacteria) play plausible roles to promote/stimulate the crop plant growth through several mechanisms that include, i) nutrient acquisition by nitrogen (N₂) fixation and solubilization of insoluble minerals (P, K, Zn), organic acids and siderophores, ii) antimicrobial metabolites and various lytic enzymes, iii) action of growth regulators and stress-responsive/induced phytohormones, iv) ameliorating abiotic stress like drought, high soil salinity, extreme temperatures, oxidative stress, and heavy metals by using different modes of action, and v) plant defense induction modes. Presenting here is a brief review emphasizing the applicability of BPBs as an innovative exertion to fulfill the current food crisis.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

The German wine sector has encountered new challenges in water management recently. To manage water resources responsibly, it is necessary to understand the relationship between the input of water and the output of wine, in terms of quantity and quality. The objectives of this study are to examine water use at the farm scale at three German wineries, and to develop and apply, for the first time, a quality-based indicator. Water use is analyzed in terms of wine production and wine-making over three years. After the spatial and temporal boundaries of the wineries and the water flows are defined, the farm water productivity indicator is calculated to assess water use at the winery scale. Farm water productivity is calculated using the AgroHyd Farmmodel modeling software. Average productivity on a quantity basis is 3.91 L wine per m3 of water. Productivity on a quality basis is 329.24 °Oechsle per m3 of water. Water input from transpiration for wine production accounts for 99.4–99.7% of total water input in the wineries, and, because irrigation is not used, precipitation is the sole source of transpired water. Future studies should use both quality-based and mass-based indicators of productivity.

Many metrics exist for the evaluation of binary classifiers, all with their particular advantages and shortcomings. Recently an “Efficiency Index” for the evaluation of classifiers has been proposed, based on the consistency, or matching, and contradiction, or mismatching, of outcomes. This metric and its confidence intervals are easy to calculate from base data in a 2x2 contingency table, and values can be qualitatively and semi-quantitatively categorised. For medical tests, in which context the Efficiency Index was originally proposed, it facilitates communication of risk (of correct diagnosis versus misdiagnosis) to both clinicians and patients. Variants of the efficiency index (balanced, unbiased) which take into account disease prevalence and test cut-offs have also been described. The objectives of the current paper were firstly to extend the EI construct to other formulations (balanced level, quality) and secondly to explore the utility of EI and all four of its variants when applied to the dataset of a large prospective test accuracy study of a cognitive screening instrument. This showed that the balanced level, quality, and unbiased formulations of EI are more stringent measures.

Let G[F,Vk, Huv] be the graph with k pockets, where F is a simple graph of order n ≥ 1,Vk= {v1,v2,··· ,vk} is a subset of the vertex set of F and Hvis a simple graph of order m ≥ 2,v is a specified vertex of Hv. Also let G[F,Ek, Huv] be the graph with k edge pockets, where F is a simple graph of order n ≥ 2, Ek= {e1,e2,···ek} is a subset of the edge set of F and Huvis a simple graph of order m ≥ 3, uv is a specified edge of Huvsuch that Huv− u is isomorphic to Huv− v. In this paper, we derive closed-form formulas for resistance distance and Kirchhoff index of G[F,Vk, Hv] and G[F,Ek, Huv] in terms of the resistance distance and Kirchhoff index F, Hv and F, Huv, respectively.

Introduction: The viral respiratory disorder known as severe acute respiratory syndrome (SARS) is caused by the SARS-associated coronavirus. End of May 2021, there have been over 170 million reported cases and more than 3.53 million deaths worldwide. In the field of cardiovascular performance, the shock index (SI) is a simple and widely used formula that measures the physiological response prior to systemic hypotension. It is obtained by dividing the heart rate by the systolic blood pressure. Another parameter, the modified shock index (MSI), is defined as the ratio of heart rate to mean arterial pressure (MAP). Methods: In this retrospective study, we examined the data of COVID-19 patients who were admitted to the ICU between June 1st, 2020, and January 31st, 2021. The patient details were collected from the Medical Records Department (MRD) in a tertiary care center. A case-recorded proforma was used to record the patient information, which was then analyzed using SPSS software. Results: The mean age of the patients was 67 years, consisting of 64 males (68.9%) and 29 females (31.1%). The standard deviation was calculated as 13.557. Among the patients, the minimum age recorded was 28, while the maximum age was 97. Patients with known CAD (Coronary Artery Disease) had a higher mortality rate among comorbidities. The p-value for Shock Index and Mortality Status was 0.205 (with an alpha value greater than 0.05), indicating no significant association. However, the modified shock index (MSI) showed a significant association with mortality status. The Pearson chi-square value for MSI and Mortality Status was 4.19, with a p-value of 0.041 (with an alpha value less than 0.05). These results suggest that there is a higher risk of mortality for patients with a Modified Shock Index of less than 0.7 or greater than 1.3. The MSI Odds ratio was found to be 4.500, indicating that such patients have a 4.5 times higher risk of mortality compared to others. Conclusion: In conclusion, our study found that there is no significant association between the Shock Index (SI) and mortality, as the p-value was greater than 0.05. However, the Modified Shock Index (MSI) showed a significant association with mortality status, with a p-value less than 0.05. This suggests that patients with a Modified Shock Index less than 0.7 or greater than 1.3 are at a higher risk of mortality. It is important to consider these findings when assessing the prognosis and potential interventions for COVID-19 patients.

China is striving to leverage the power of science and technology to green its agriculture while increasing grain productivity. In this context, this study presents the green growth rate of agriculture from the DEA-based Green Total Factor Productivity (GTFP) indicator, together with the growth rate of grain yields, and applies it to the case of Jiangsu, a major grain-producing province with a well-developed economy. It is found that Jiangsu's agriculture has generally performed well in the implementation of the two major national strategies of green development and grain security, especially in the northern Jiangsu, which is a major grain-producing area. In contrast, the phased fluctuations of green growth in agriculture in Southern Jiangsu are more pronounced, with even negative green growth occurring during the green agriculture movement. Much of the volatility in agricultural green growth at the provincial, subregional, municipal level comes from the effects of the movement of the green technology frontier led by best practitioners. Accordingly, the possibility of improving the weak state of the catch-up effect on green growth is explored from the perspective of the Chinese government-led agricultural science and innovation system; it also traces the green agricultural initiatives in the main grain-marketing areas that have failed to deliver the expected green growth, and recommends a review of such policies and refinement of the GTFP Index tool for assessing sustainable green growth.

Maintaining the judiciary's power requires a high level of budgetary expenditure, but the specifics of this relationship have yet to be fully explored. Although several studies have analyzed the impact of spending in the judiciary through productivity and performance-related measures, none have employed machine learning techniques. This study examines the productivity of the judiciary based on spending and other variables using machine learning techniques, including clustering and neural networks. The final neural network model supports the results of Pearson's parametric correlation test, which found no significant correlation between expenditure and productivity. This study's findings demonstrate the importance of understanding that increased public budgetary expenditure alone is insufficient for improving the judiciary's efficiency. Instead, other administrative and technical measures are necessary to meet the demands of the Brazilian judiciary and improve service delivery rates. These findings offer important theoretical and managerial contributions to the field.

The construction sector has begun to embrace the digital revolution, intending to improve efficiency. How, on the other hand, should the industry adopt digital tools? And how should the connection between humans and technology function? This study aims to shed light on how the construction sector may bridge the gap between AI deployments’s potential and realized advantages. This article presents research based on a comprehensive review of the literature, case studies of Speller Metcalfe, a design-build and refurbishment project in Malvern, England, Jacobsen Construction, a project digitizing the planning process in Salt Lake City, Utah, USA, and Menkes Development Inc., real-time visibility to construction site insights and data-driven decision-making in Toronto, Canada. The experiences gained via this study show that it is feasible to acquire expertise while adopting sophisticated technologies, such as artificial intelligence, by installing fundamental digital tools (AI). However, when it comes to AI, the level of trust between humans and machines will be the deciding element in its success. This article is a pioneering effort in examining the deployment of AI and how people and technology should interact. This study is limited to three case studies and three digital technologies. To further the study, it is suggested to debate the adaptation of AI on the user's premises, gather more empirical data, and examine case studies from different sectors.

Agile methods promise to achieve high productivity and provide high-quality software. Agile software development is the most important approach that has spread through the world of software development over the past decade. Software team productivity measurement is essential in agile teams to increase the performance of software development. Due to the prevalence of agile methodologies and increasing competition of software development companies, software team productivity has become one of the crucial challenges for agile software companies and teams. Awareness of the level of team productivity can help them to achieve better estimation results on the time and cost of the projects. However, to measure software productivity, there is no definitive solution or approach whether in traditional and agile software development teams that lead to the occurrence of many problems in achieving a reliable definition of software productivity. Hence, this study aims to propose a statistical model to assess the team’s productivity in agile teams. A survey was conducted with forty software companies and measured the impact of six factors of the team on productivity in these companies. The results show that team effectiveness factors including inter-team relationship, quality conformance by the team, team vision, team leader, and requirements handled by the team had a significant impact on the team’s productivity. Moreover, the results also state that inter-team relations affect the most on software teams’ productivity. Finally, the model fit test showed that 80% of productivity depends on team effectiveness factors.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

The Randić index of a graph G is the sum of (dG(u)dG(v))−1/2 over all edges uv of G, where dG(u) denotes the degree of vertex u in G. In this paper, we investigate a few graph transformations that decrease Randić index of graph. By applying those transformations, we determine the minimum Randić index on tricyclic graphs, and characterize the corresponding extremal graphs.

The aim of the research presented here is to assess the impact of depressive disorders on the potential of the labour markets in the countries of the European Union, with particular reference to the disparities between the 'old' and 'new' EU countries. The initial hypothesis of persistent inequalities in the system under study was verified by analysing the process of convergence in the burden of depressive disorders among people aged 20-54 that occurred in the EU-27 group of countries between 1990 and 2019. The study used data from the Global Burden of Disease Study 2019 (IHME, 2020), which examined the number of years lived with disability (YLD) due to depression in the working age population. The analysis showed that the high burden of the consequences of depressive disorders is particularly true for the highly developed economies of the EU-14. The results of the convergence assessment did not confirm the real effect of catching up over time with economies in a more favourable situation, and the inequalities observed at the beginning of the analysis period deepened..

The article's purpose is a citation analysis of the impact of scientific publications by authors of different gender compositions. The PageRank method was chosen to calculate the citation impact of scientific publications, and the citation has also estimated the impact of scientific publications based on the number of citations. The normalized citation impact of scientific publications is calculated according to nine subsets of scientific publications that correspond to patterns of different gender compositions of authors. Also, these estimates were calculated for each country with which the authors of the publications are affiliated. The Citation database was chosen for the scientometric analysis Network Dataset ( ver . 13). The dataset includes more than 5 million scientific publications and 48 million citations. The main subject areas of scientific publications in this database are computer science, artificial intelligence, mathematics, engineering, etc. The results indicate that articles with a predominantly male composition are cited more than articles with a mixed or female composition of authors in this direction. Analysis of advantages in dynamics indicates that in the last decade for developed countries, there has been a decrease in the connection between the citation impact of scientific publications and the gender composition of their authors. However, the obtained results still confirm the presence of gender inequality in science, which may be related to socioeconomic and cultural characteristics, natural homophily, and other factors that contribute to the appearance of gender gaps. An essential consequence of overcoming these gaps, including in science, is ensuring the rights of people in all their diversity.

Bread wheat (Triticum aestivum L.) is staple of Pakistani people. However, its yield at farmer field is low as compared with its genetic potential. Integration of various crop and soil management strategies might be an option to enhance wheat productivity at farmer field. This 2-year experiment was conducted to check the influence of combine application of natural plant water extracts and biochar on the productvity of wheat during the winter season of 2015-16. The experiment consisted of seven treatment viz. (1) control (2) application of biochar (0.18 kg pot-1) alone, (3) application of sorghum water extract (SWE) alone, (4) application of moringa water extract (MWE) alone, (5) application of biochar + SWE, (6) application of biochar + MWE, (7) application of biochar + SWE+MWE. The results revealed that application of both crop water extracts in combination with biochar improved the growth and grain yield of wheat. Use of MWE in combination with biochar enhanced the grain weight, grain number and grain yield of wheat by 44, 14, and 24%, respectively than the control treatment. In crux, use of MWE in combination with biochar might be a viable option to improve the productivity of bread wheat.

This purpose was to compare the ability of body shape index (ABSI) and body roundness index (BRI) with waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and body adiposity index (BAI) to predict metabolic risk. The cross-sectional study was conducted in 17,360 Chinese subjects (were aged 18-95 years old) who escaped cardiovascular disease (CVD) or diabetes. Biochemical and anthropometric variables were measured by trained staff. Receiver operating characteristic curve (ROC) and optimal cutoff values of obesity indices were recruited to compare the predictive ability for metabolic risk factors. The mean age of subjects was 53.7(13.1) years, 41.6 % were males. Within young group (<60 years), the areas under the curve (AUC) demonstrated that WC, BMI, WHR, WHtR and BRI were able to similarly predict high metabolic risk in males (0.74 vs. 0.74 vs. 0.73 vs. 0.73 vs. 0.73) and in females (0.73 vs. 0.73 vs. 0.71 vs. 0.73 vs. 0.73), while the approximate predictive ability were only acquired in males (0.73 vs. 0.73 vs. 0.70 vs. 0.73 vs. 0.73) within elder group (≥60 years). The optimal cut-off values of BRI for high metabolic risk were calculated in males (<60 y: 3.49 vs. ≥60 y: 3.46) and females (<60 y: 3.47 vs. ≥60 y: 3.60). Meanwhile, BRI displayed a strong prediction to elevated BP and elevated TG in males (AUC = 0.64; AUC = 0.70) and to elevated BP, elevated TG and elevated SUA in females (AUC = 0.67; AUC = 0.69; AUC =0.70). BRI was able to similarly predict high metabolic risk compared to WC, BMI, WHR, WHtR and BAI, while ABSI was not. Moreover, BRI revealed specific predictive ability for elevated BP, elevated TG and elevated SUA.

Sombor index was recently defined in 2021 as a new vertex degree based topological index by Gutman and has received great attention of mathematicians and chemists. In this work, we determine how much the Sombor index is effected when we delete a vertex or an edge from a graph. Using the formulae obtained here successively, one can calculate the Sombor indices of large graphs by means of Sombor indices of smaller graphs which are obtained by deletion of vertices or edges.

Global change is affecting vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing offer a unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that NDVI has increased over the studied period, particularly at low and middle elevations and during fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily to temperature or precipitation trends. On the other hand, interannual fluctuation in NDVI is more correlated with temperature and precipitation. RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.

Water scarcity challenges have necessitated the adoption of water-saving techniques in protected and nom-protected farming. This study aimed to assess the performance of a water-saving soil-less cultivation technique and to compare it with conventional soil-based cultivation in protected farming. The soilless technique used local gravel and a mixture of peat-moss, humin-substrate, and perlite in ratios of 4:3:1.5. Three irrigation regimes were imposed using emitters 8Lh-1 design discharge (D1) emitters with 6Lh-1 design discharge (D0.75) and 4Lh-1 de-sign discharge (D0.5) for the two cultivation methods during the growth cycle of tomato by drip irrigation. The vegetative growth, fruit yield and water consumption were measured and water productivity was determined. Moreover, an economic assessment was carried out by estimating and comparing economic coefficients for the two cultivation methods. Estimated coefficients include revenues, net profit, benefit-cost ratio, break-even levels of production and prices, revenues over variable cost, and revenues on investment. The tomato fruit yield under soil-based cultivation overtopped the yield under soilless cultivation. The water productivity under the soilless cultivation was almost twice that (24.3 kg m-3) of the soil-based cultivation (15.5 kg m-3). The soilless cultivation saved 50% of irrigation water applied by the conventional soil-based method, saving energy and soil from deterioration. Revenues and net profits stimulated by higher yield coupled with lower variable cos supported the soil-based cultivation. The economic assessment showed that both cultivation methods were economically viable. However, the soil-based cultivation method was more profitable due to its higher fruit yield. Overall, the results of this study suggest that the soilless cultivation technique is a viable option for wa-ter-saving cultivation. However, the soil-based cultivation method is still more profitable due to its higher fruit yield

Tanzania with 945 million hectares of land area and annual rainfall of 300 mm on 67% of its territorial land is considered as a semi-dry region in the world. Rice production in Tanzania needs to be increased to feed a growing population, whereas water for irrigation is getting scarce. One way to decrease water consumption in paddy fields is to change the irrigation regime for rice production and to replace continuous flooding with alternate wetting and drying. In order to investigate the effect of different regimes of irrigation and nitrogen fertilizer on yield and water productivity of hybrid rice, two greenhouse pot experiments comprising soils from upland and lowland production ecologies were conducted at Sokoine University of Agriculture, Tanzania during crop seasons of 2019. The experiment was arranged in split plots based on randomized completely block design with 3 replications. Water regimes were the main factor comparing continuous flooding (CF) and alternate wetting and drying (AWD) with nitrogen fertilizer levels as the sub-factor including absolute control , 0, 60, 90, 120 and 150 kg/ha. Alternate wetting and drying (AWD) improved water productivity in both upland and lowland production ecologies compared to CF. AWD increased yield under lowland production by 13.3% while in upland there was 18.5% decrease in yield. The average water use varied from 31.5 to 84 L pot-1 under upland trials, while in lowland trials it was 36 to 82.3 L. Higher yield and lower water application led to an increase in WP varying from 1.2 to 1.8 kg cm-3 under upland trials, and 0.6 to 1.5 kg cm-3 under lowland trials. The variation in water productivity among treatments was mainly due to the differences in the yield, water and nitrogen levels used in the production process. Both sets of trials recorded water saving up to 34.3% and 17.3% under lowland and upland trials, respectively. Under upland trials, the yield varied from 39.9 to 124.1 g pot-1 and in lowland trials yield ranged from 20.6 to 118.2 g pot-1 representing paddy rice. The measurements showed that less water can be used to produce more crops under alternative rice growing practices. The results are important for water-scarce areas, providing useful information to policy makers, farmers, agricultural departments, and water management boards in devising future climate-smart adaptation and mitigation strategies.

The production of sugar beet in the Republic of Kazakhstan is insufficient to meet the do-mestic sugar needs of the population. This shortfall is attributed to the natural and climatic conditions, the high cost of production, and the low use of mineral fertilizers. The objective of the study is to investigate the impact of the organic humic fertilizer "Tumat" on the growth, development, yield, and sugar content of sugar beet in the conditions of irrigated light chestnut soils in Southeast Kazakhstan. The research employed widely accepted methods of field experiments and laboratory studies from the Commonwealth of Inde-pendent States. Scientific research confirms the effectiveness of using the organic humic fertilizer "Tumat" for cultivating sugar beets. This fertilizer is highly bioavailable and con-tains a balanced mix of essential macronutrients and micronutrients, polyunsaturated fat-ty acids, and other biologically active substances. Foliar feeding of sugar beets enriches the soil with exchangeable potassium, mobile phosphorus, and easily hydrolyzable nitrogen during the plant's vegetative period. Using "Tumat" fertilizer improves seed germination, stimulates growth and development, accelerates the ripening of sugar beets, and enhances tuber yield and sugar content. "Tumat," an organic humic fertilizer, is recommended as an environmentally safe and effective agricultural product that boosts the productivity and quality of sugar beets, as well as soil fertility.

Agricultural mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sink, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

Over time, the agricultural sector's contribution to the nation's Gross Domestic Product and revenue is declining exponentially; the decline may be attributed to varying problems affecting the agricultural value chain resulting in low productivity. The agricultural value chain comprises a series of activities and value addition processes required to transform raw materials into useable products to maximize the final consumers' utility.¹ The agricultural value chain's marketing activities have been skewed with challenges, thus affecting agricultural productivity and agricultural sector contribution to the economy. The paper critically examines and discuss the impact of agricultural marketing to economic development, a historical review of agricultural marketing in Nigeria, challenges undermining the impact of agricultural marketing, measures to reposition agricultural marketing potential to build back better, policy recommendations to reposition the future of Nigeria's agricultural productivity. The paper aims to promote concerted efforts through knowledge dissemination to build back better through market research and facilitation and boost economic prosperity.

Workplace exercise programs are imperative for improving employee health and wellbeing. Employee cognition and productivity can also benefit from such programs; however, the practical application of interventions to influence these outcomes is poorly understood. This research aimed to assess the suitability of a university Staff Fitness Program for improving employee productivity and cognition. Forty-seven participants were included in the study, comprising 27 Staff Fitness participants and 20 control group participants. A two (groups) x three (time-points) between-subjects/within-subjects design was employed over 14 weeks, comprising ten weeks of once-weekly exercise intervention for Staff Fitness participants. All participants completed the Victoria Stroop Colour and Word Test and the Health and Work Questionnaire at each time-point, to assess cognition and productivity, respectively. Participants also completed the International Physical Activity Questionnaire (short form) at time-point one, three and during training weeks (excluding week one) to measure physical activity. Appropriate T-tests and non-parametric equivalents were used to assess group differences in outcome measures and across time-points. There were no significant between group or longitudinal differences indicative of improved productivity or cognition. The Staff Fitness group demonstrated a non-significant improvement (Z = 73.00, p = .055) in physical activity from time-point one (M = 1540.93 MET-min-week, SD = 1083.74) to three (M = 2077.32 MET-min-week, SD = 1401.48) with a large effect size (d = 0.97), while control group physical activity significantly decreased (Z = 10.00, p = .013). The present Staff Fitness Program benefited employees by improving physical activity, despite no improvements in productivity or cognition. Future research should further explore the application of workplace exercise programs and the manipulation of exercise parameters to show improvements in employee productivity and cognition.

Forest ecosystems provide diverse services and values that contribute to human well-being. Although high proportion of species is still undiscovered, tropical forests alone are thought to host more than 50% of the world’s biodiversity. Beyond supporting via direct use of products like timber, fiber and biomass energy, they play an important role in providing a wide range of ecosystem services such as regulating water flow and quality, water purification, improving infiltration, fresh water, erosion control, carbon sequestration and sedimentation control. They are one of the important parts of terrestrial and the largest carbon pool, occupying an integral position in the global carbon cycle. However, these days, deterioration of nature and forest biodiversity is a severe danger to the global environment. This will be accompanied by increased strains on food supply, causing increased pressure on already delicate ecological systems. Thus, better forest management strategies are necessary for managing forests sustainably. Nevertheless, little is known regarding the existing forest management approaches and their associated benefits and challenges. Multidisciplinary approaches are needed to achieve sustainable management of forests. These can be accomplished if suitable forest management innovations are put in place. Various technologies can also be adopted through applying different forest assessment tools like remote sensing using light detection and ranging technology (LiDAR) in forest management. Harnessing such technologies will definitely result in providing increased socio-economy as well as improved environmental sustainability. However, the speed of transformation depends much on level of commitment of stakeholders including policy makers. As a result, this review is intended to explore existing forest management innovations which are suitable both ecologically as well as socio-economically. This shows that while there is a lot to be improved, there are already developed forest management innovations that are already in use including PFM and MFM, which helps to achieve SFM.

Tree pruning is a management tool in agroforestry systems for reducing shade, enhancing nutrient cycling or providing fodder. However, little information is available on the effect of pruning management on plant growth, non-structural carbohydrate (NSC) levels in the roots and N2 fixation of Sesbania sesban. A glasshouse experiment was conducted to assess the effect of pruning frequency on biomass production, NSC levels and N2 fixation of Sesbania sesban. Treatments included pruning at (i) 3 months only, (ii) 3 and 6 months, and (iii) 3, 6 and 9 months, with each pruning removing shoot biomass above 50% of the initial height. Increased pruning frequency decreased above- and belowground dry matter (DM), and root NSC levels. The decrease in aboveground DM correlated with reduced levels of starch, sugar and total non-structural carbohydrates. Pruning more frequently significantly decreased nodulation, the percentage N derived from the atmosphere and N2 fixed. It could be concluded that more frequent prunings decreases biomass and NSC levels which could reduce the regeneration capacity of trees since they rely on NSCs to regrow. The suppressive effects of increased pruning frequency on N2 fixation could decrease the desirable benefits of legume trees on soil N fertility improvement.

This study is designed to assess and improve apparel sewing section efficiency and productivity throughout line balancing. Apparel industry is one of the oldest and among the most global industry, being primarily concerned with the design and production of cloth and their supply. The central process in apparel manufacturing is the joining together of components which is known as the sewing process , which is the most labour intensive type of manufacturing process .Proper utilization of resources in garment sewing section is more critical to enhance the performance of the apparel industry by reducing production cost and minimizing wastage. For effective utilization of resources in the sewing section, good line balancing is important to increase productivity and production efficiency. This research was a design to analyse and improve the assembling line in the case of Telaje garment manufacturing and sales plc. The study was first conduct observations in the production floor and start work with the selection of sewing line in the garment production process. Among the nine lines of the factory select one on the production floor and one garment ordered product known as five pocket men’s jeans trousers are selected. For this study, both qualitative and quantitative research approaches were employed. Both primary and secondary data sources are used to detail the collected relevant data to understand the current efficiency scenario of the factory. The main challenges to minimizing line efficiency and productivity with the expected performance measurement are improper utilization of resources and improper implementation of line balancing in sewing section, therefore this thesis work shows that the bottleneck process and consequence solution will be searched, and finally significantly improving the productivity by 418 unit products/ day and, hence the efficiency will increase from 28.83% to 50.04% of the line

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types.

This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. We find that: (a) the two series exhibit strong, negative, extreme tail dependence; (b) the negative dependence is stronger in extreme bearish markets than in extreme bullish markets; (c) the dependence gradually weakens as the market return moves toward the center of its distribution, or in quiet markets. The unique dependence structure supports the VIX as a barometer of markets' mood in general. Moreover, applying the proposed method to the S&P 500 returns and the implied variance (VIX²), we find that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in general, both effects are weaker than the dependence relation between the market returns and the log-increments of the VIX.

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.

As abiotic stress, drought limits plant growth and minimizes productivity. The increased request for valuable essential oil extracted from geranium (Pelargonium graveolens L.) is mainly associated with plant growth, which is adversely affected by drought. Melatonin (MT) has been used to enhance plant growth under abiotic stress, however, its impact to overcome drought stress of aromatic plants including geranium is poorly investigated. In the current investigation, MT application at 100 µM was applied under 100 % (well-watered) or 50 % (drought stress) of FC to verify this role. Drought stress markedly reduced growth parameters, herb yield, and total chlorophyll; however, MT alleviated these effects. In contrast, drought enhanced the essential oil percentage in geranium leaves. Despite the reduction in oil yield caused by drought, MT application mitigated this reduction and improved both oil yield and oil components. Besides, MT treatment enhanced the accumulation of total phenols, glutathione, and proline and improved the activity of ascorbate peroxidase, catalase, and glutathione reductase with possible alleviation of drought-induced oxidative damage. Therefore, it reduced both H2O2 and malondialdehyde accumulation, and finally maintained membrane integrity. Overall, this is the first report that reveals that MT application can improve geranium resistance to drought by enhancing the antioxidant potential and protecting the cell membrane from oxidative damage.

Producing cherry tomatoes became interesting to know watering volume and growing design on growth, yield, and quality of cherry tomatoes. The research aimed to intend the best treatment for each treatment of watering volume and Growing design on the productivity and quality of cherry tomato cultivar Ruby. The study is an experimental exploration using RCBD factorial. The treatment factors include: Growing Design (greenhouse, Rain shelter, Screen house) and Watering Volume (100% Etc, 75% ETc, 50% ETc). The result showed that root dry weight and root-shoot ratio were found higher in the screen house design, while fruit firmness was higher in the rain shelter design. Considering the effect of watering volume, higher fruit diameter, heavier fruit, fruits per plant, ultimate fruit &amp; biological yield per plant, higher root &amp; shoot biomass, root-shoot ratio, leaf chlorophyll content, greater fruit skin firmness and elasticity was noted in the 100% ETc treatment. In contrast, the growth rate was higher in 50% ETc treatment. Cultivating cherry tomatoes in a greenhouse using a watering volume of 100% ETc under the results is recommended. These conditions have led to better growth, higher fruit yield, and improved fruit quality, making them favorable options for successful cherry tomato production.

In recent years, Chinese manufacturing enterprises compete to chase the wave of "digital revolution", digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region and industry. In the further study, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises, and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences, and provides certain guidance for enterprises to implement the strategy of digital transformation.

Risk management for technological hazards mainly focuses on the consequences on human lives. Although technological risk analysis evaluates environmental vulnerability, it does not reflect the consequences on environmentally exposed elements, such as rivers, water springs, flora, and fauna. This paper's objective was to propose a conceptual framework and create a multidisciplinary evaluation model for environmental risk analysis in the oil and gas industry. Initially, the problem was approached from a global perspective to justify the necessity of a holistic environmental risk analysis methodology in the oil industry, using environmental risk factors as well as underlying factors, such as environmental fragility and lack of resilience. The holistic assessment was carried out based on probabilistic risk analysis methodologies to obtain a holistic environmental risk index, HERI. This methodology was applied to an oil and gas industry company in Colombia. This allowed greater disaggregation of the results to establish priorities for risk reduction actions and identify the company's weaknesses.

The objective of this study was to evaluate the glycemic index and the satiety response of three Mexican kinds of honey. The values of fructose ranged from 272.40-395.10 g/kg, while the glucose value ringed 232.20-355.50 g/kg. The ratio F/G of sample honey was 1.45, 1.00, and 1.17 for Highland, Multifloral, and Avocado honey, respectively. Twenty-six participants completed this study, which was previously approved by the ethics committee of the Facultad de Salud Pública y Nutrición (CE 2/2018-19). Highland and Avocado honey is classified as medium-GI (69.204.07 and 66.365.74, respectively), while Multifloral honey is classified as high-GI (74.245.98). The Highland honey presented the best satiety response. The difference in IG values and the effect of the satiety response of Highland honey could be explained by the different fractions of carbohydrates in samples and other components such as phytochemicals.

Chellali et al. introduced two degree concepts, ve-degree and ev-degree (Chellali et al, 2017). The ve-degree of a vertex equals to number of different edges which are incident to a vertex from the closed neighborhod of v. Moreover the ev-degree of an edge e=ab equals to the number of vertices of the union of the closed neighborhoods of a and b. The most private feature of these degree concepts is, total number of ve-degrees and total number of ev-degrees equal to first Zagreb index of the graphs for triangle-free graphs. In this paper we introduce ve-degree entropy, ev-degree entropy and investigate the relations between these entropies and the first Zagreb index entropy. Finally we obtain the maximal trees with respect to ve-degree irregularity index.

The article presents the results of studies aimed to identify the effect of foliar treatments of winter wheat, sugar beets and soybeans with mineral and bioorganic fertilizers. Their positive effect on increasing the concentration of mineral forms of nitrogen in soil was revealed. The crop types have a greater influence on the size of nitrous oxide emissions: in winter wheat crops - 679 µg/m3, soybeans - 637.2 µg/m3, sugar beets - 576.8 µg/m3. The amounts of nitrous oxide emissions were lower in the variants without the use of phosphorus-potassium fertilizers. The Ruter AA fertilizer showed the greatest efficiency on winter wheat crops - 42.7 c/ha. Soybean grain yield of 44.2 c/ha was also achieved by using Ruter AA, as well as Geo-humate together with phosphorus-potassium fertilizers. On the background of the actual supply of phosphorus and potassium, maximum yield was obtained when using N30 on the leaf - 39.3 c/ha. Foliar feeding ensured a yield of sugar beet root crops of up to 67.1-77.4 c/ha on the backdrop of the application of phosphorus-potassium fertilizers with the advantage of using Amino turbo. The largest yield of sugar beet roots without use of mineral phosphorus and potassium was ensured by N30 treatment of the leaf in the phases of 4-6 and 8 leaves - 63.2 t/ha. Of the organo-mineral fertilizers and biostimulants, the best result was shown by the use of Ruter A - 62.6 t/ha. We believe that foliar feeding of crops can be a sustainable farming method that can increase crop yields and reduce N2O emissions.

Soil tillage intensity influences the distribution of nutrients, and soil’s physical and me-chanical properties, as well as gas flows. The impact of reduced tillage on these indices in spring barley cultivation is still insufficient and requires more analysis on a global scale. This study was carried out at Vytautas Magnus University, Agriculture Academy (Lithu-ania) in 2022–2023. The aim of the investigation was to determine the effect of the tillage systems on the soil temperature, moisture content, CO2 respiration and concentration in spring barley cultivation limited by the semi-humid subarctic climate. Based on a long-term tillage experiment, five tillage systems were tested: deep and shallow mold-board ploughing, deep cultivation-chiselling, shallow cultivation-chiselling, and no-tillage. Shallow ploughing technology was found to be better at conserving soil moisture and maintaining a higher temperature. Deep cultivation had a lower moisture content and lower soil temperature. Shallow cultivation fields in most cases increased CO2 emissions and CO2 concentration. The results show that in direct sowing fields, most cases had a positive effect on crop density. Direct sowing fields resulted in significantly lower grain yields of spring barley in the years studied.

This paper explores the role of agroforestry in mitigating climate change by sequestering atmospheric carbon in the tropics and subtropics, specifically in the Madhupur Sal forest of Bangladesh. Agroforestry, combining trees with crops on agricultural lands, is recognized for its potential to act as carbon sinks and enhance productivity. The study assesses various agroforestry practices, including Acacia-Pineapple-Turmeric-Papaya, Acacia-Pineapple-Zinger-Banana, and Sal-Pineapple-Aroid combinations. The research reveals improved farm productivity in these agroforestry systems, with different tree species sequestering varying amounts of carbon. Acacia species, ranging from 12 to 25ft in height, sequestered an average of 23.35 lbs/year, while Sal species (Shorea robusta), with trees 45 to 61ft tall, sequestered 49.80 lbs/year on average. Factors such as tree height, diameter at breast height (DBH), number of leaves, and branches influence carbon sequestration. The paper suggests integrating the carbon trading system of the Clean Development Mechanism (CDM) with Carbon Sequestration (CS) potential to leverage agroforestry for greenhouse gas emission reduction in Bangladesh. By emphasizing the profitability of these practices alongside carbon sequestration, the study encourages the adoption of agroforestry as a sustainable and economically viable strategy for climate change mitigation.

Vegetation Net Primary Productivity (NPP) plays a crucial role in terrestrial carbon sinks and the global carbon cycle. Investigating the spatiotemporal evolution and influencing factors in the Yangtze River Delta (YRD) region can furnish a solid scientific foundation for green, low-carbon, and sustainable development in China, as well as a reference for other rapidly urbanizing regions. This study focuses on the YRD region as an illustration and utilizes the Carnegie-Ames-Stanford Approach (CASA model) to quantify NPP in this region from 2000 to 2018. Investigation into the spatiotemporal evolution and influencing factors was conducted using Theil–Sen Median Trend Analysis and Scenario Analysis. The results indicate that (1) the NPP in the YRD region from 2000 to 2018 exhibited pronounced spatial differentiation characteristics, typically exhibiting a spatial distribution pattern of being high in the south and low in the north, high in the west and low in the east. Additionally, the expansion of built-up areas and the reduction of cultivated land have the potential to reduce NPP in the YRD region. Moreover, the influence of LUCC is anticipated to be relatively limited compared to that of climate change. Furthermore, changes in precipitation were found to be positively correlated with changes in NPP, with the effect being relatively more pronounced. The correlation between temperature and NPP demonstrated spatial differentiation, with a mainly positive correlation in the central and southern parts of the YRD and a mainly negative correlation in the northern part. Changes in solar radiation had a negative correlation with changes in NPP. Based on these results, it is recommended that local governments strictly enforce urban development boundaries and manage the disorderly expansion of built-up areas, enhance the regional irrigation infrastructure, and address air pollution, so as to ensure the necessary conditions for the growth of vegetation, reduce greenhouse gas emissions, and control regional temperature rise.

Coffee production around the world is under threat due to climate variability and change, and drought stress will increase in many coffee regions, nutrient management practices could enhance the adaptation capacity of coffee production. Considering that coffee is a sensitive crop to boron (B) deficiency, this research investigated how B nutrition improves resistance to drought stress in coffee under controlled conditions as well how with interaction with calcium (Ca+2) influences productivity, seed compositions, and soil fertility during a production cycle of 5 year. Under controlled conditions for seven months, coffee plants were submitted to water stress with and without B nutrition. In the field, coffee plantation was submitted to two B rates (0,6 and 1,1 kg. ha-1-year-1) with fixed calcium (Ca+2) rate and, a control without Ca+2 and B. After 9 months of growth and seven months of water deficit, under controlled conditions, the application of B significantly (p&lt;0,05) reduced the negative effect of water stress on coffee growth. Under field conditions, after a production cycle of 5 years, the application of 0,6 kg B and 77 kg CaO. ha-1. year-1 yielded 14% more than the control without B and Ca+2. An increase of the B rate to 1.1 kg.ha-1.year-1 with the same Ca+2 rate increased the productivity significantly (p&lt;0,05) by 37% compared to the control. B application also improved significantly (p&lt;0,05) the B content in the soil at 0-30 cm. The B treatments influenced the biochemical composition of the green coffee beans, with a significant (p&lt;0,05) inverse correlation between the B content of the green coffee beans with caffeine, and unsaturated fatty acids (UFAs) mainly, oleic, linoleic, and linolenic acids which are considered negative descriptors of the coffee quality.

Background: Oral narratives are crucial for evaluating youngsters since they reveal a plethora of information about young children's language development. This study aimed to investigate the development of narrative productivity, lexical diversity, syntactic complexity and in Cypriot-Greek-speaking children during preschool and primary school years. An additional aim was to measure the effect of the children’s gender in their performance on the measures of narratives. Methods: One hundred and twenty-nine typically developing Cypriot-Greek-speaking children were recruited for the study. Results: The results showed that the linguistic structure of narrations reflects a subtle developmental trend. As expected, older children tended to produce longer and syntactically more complex stories than the younger ones, which is in line with previous studies. There were significant differences in all productivity measures between the four-year-olds and those aged seven and ten years old. In addition, the results illustrated that there was not any significant effect of gender in the measures of narrative skills. Specifically, gender did not affect the children’s performance in the sample. Boys and girls had similar narrative measurements in all the variables. Conclusions: This study aims to provide initial evidence in retelling narrative development patterns on typically developing Cypriot-Greek speaking children that could be used by speech and language to compare children’s performance and detect language disorders.

Increasing green total factor productivity is the key to achieving green development in agriculture. This study measured the green total factor productivity of Jiangxi’s agriculture, and its regional and temporal evolution characteristics were examined. The fixed-effects model was then used to investigate the model’s fundamental components empirically. The study’s findings reveal the following: During the period under review, technical change was the primary element driving the rise in the green total factor productivity of agriculture. A rising “U”-shaped trend with notable regional variances characterizes the spatial and temporal evolution. The primary factors that affect changes in green total factor productivity in agriculture include the ease of transportation, the per capita disposable income of rural residents, the level of agricultural mechanization, the degree of urbanization, the level of financial support for agriculture, and the percentage of workers in secondary industries. As a result, it is suggested that, in order to substantially increase agricultural green total factor productivity, agricultural green technological support should be strengthened, more fully developed, and promoted in a multi-pronged approach.