Search Results (327)

Redwood (Sequoia sempervirens (Lamb. ex D. Don) Endl.) is a fast-growing, long-lived conifer native to a narrow coastal zone along the western seaboard of the United States. Redwood can accumulate very high amounts of carbon in plantation settings and continuous cover forestry (CCF) represents a highly profitable option, particularly for small-scale forest growers in the North Island of New Zealand. We evaluated the profitability of conceptual CCF regimes using two case study forests: Blue Mountain (109 ha, Taranaki Region, New Zealand) and Spring Creek (467 ha, Manawatu-Whanganui Region, New Zealand). We ran a strategic harvest scheduling model for both properties and used its results to guide a tactical-spatially explicit model harvesting small 0.7 ha units over a period that spanned 35 to 95 years after planting. The internal rates of return (IRRs) were 9.16 and 10.40% for Blue Mountain and Spring Creek, respectively, exceeding those considered robust for other forest species in New Zealand. The study showed that small owners could benefit from carbon revenue during the first 35 years after planting and then switch to a steady annual income from timber, maintaining a relatively constant carbon stock under a continuous cover forestry regime. Implementing adjacency constraints with a minimum green-up period of five years proved feasible. Although small coupes posed operational problems, which were linked to roading and harvesting, these issues were not insurmountable and could be managed with appropriate operational planning. Full article

Of breast cancers, the triple-negative subtype (TNBC) is characterized by aggressive behavior, poor prognosis and limited treatment options due to its high molecular heterogeneity. Since insufficient programmed cell death response is a major hallmark of cancer, here we searched for apoptosis-related biomarkers of prognostic potential in TNBC. The expression of the pro-apoptotic caspase 8, cytochrome c, caspase 3, the anti-apoptotic BCL2 and the caspase-independent mediator, apoptosis-inducing factor-1 (AIF1; gene AIFM1) was tested in TNBC both in silico at transcript and protein level using KM-Plotter, and in situ in our clinical TNBC cohort of 103 cases using immunohistochemistry. Expression data were correlated with overall survival (OS), recurrence-free survival (RFS) and distant metastasis-free survival (DMFS). We found that elevated expression of the executioner apoptotic factors AIF1 and caspase 3, and of BCL2, grants significant OS advantage within TNBC, both at the mRNA and protein level, particularly for chemotherapy-treated vs untreated patients. The dominantly cytoplasmic localization of AIF1 and cleaved-caspase 3 proteins in primary TNBC suggests that chemotherapy may recruit them from the cytoplasmic/mitochondrial stocks to contribute to improved patient survival in proportion to their expression. Our results suggest that testing for the expression of AIF1, caspase 3 and BCL2 may identify partly overlapping TNBC subgroups with favorable prognosis, warranting further research into the potential relevance of apoptosis-targeting treatment strategies. Full article

Enhanced weathering of silicate rocks in agriculture is an option for atmospheric CO₂ removal and fertility improvement. The objective of our work is to characterise some of the agricultural consequences of a basaltic powder amendment on soil-crop systems. Two doses of basalt (80 and 160 t ha⁻¹) were applied to two types of slightly acid soils (sandy or silty clayey), derived from long-term trials at Bordeaux (INRAE, France) and Rothamsted Research (England), respectively. For each soil, half of the pots were planted with ryegrass; the other half were left bare. Thus, the experiment had twelve treatments with four replications per treatment. Soil pH increased with the addition of basalt (+0.8 unit), with a 5% equivalence of that of reactive chalk. The basalt contained macro- and micronutrients. Some cations extractable in the basalt before being mixed to the soil became more extractable with increased weathering, independent of plant cover. Plant uptake generally increased for macronutrients and decreased for micronutrients, due to increased stock (macro) and reduced availability (micronutrients and P), related to pH increases. K supplied in the basalt was responsible for a significant increase in plant yield on the sandy soil, linked to an average basalt K utilisation efficiency of 33%. Our general conclusion is that rock dust applications have to be re-evaluated at each site with differing soil characteristics. Full article

Background: Greater tuberosity fracture–dislocations (GTFDs) represent a distinct subset of proximal humerus fractures, occurring in up to 57% of anterior glenohumeral dislocations. Malreduction may result in impingement, instability, and functional limitation. Treatment is influenced by the displacement magnitude and direction, bone quality, and patient activity level. Methods: This narrative review was based on a comprehensive search of PubMed, Scopus, and Web of Science for English-language articles published between January 2000 and March 2025. Studies on pathomechanics, classification, diagnosis, treatment, and outcomes of GTFDs in adult and pediatric populations were included. Data were analyzed to summarize the current evidence and identify clinical trends. Results: A displacement ≥ 5 mm is the standard surgical threshold, though superior or posterosuperior displacement ≥ 3 mm—and ≥2 mm in overhead athletes—may justify surgery. Conservative treatment remains appropriate for minimally displaced fractures but is associated with up to 48% subacromial impingement and 11% delayed surgery. Surgical options include arthroscopic repair for small or comminuted fragments and open reduction and internal fixation (ORIF) with screws or plates for larger, split-type fractures. Locking plates and double-row suture constructs demonstrate superior biomechanical performance compared with transosseous sutures. Reverse shoulder arthroplasty (RSA) is reserved for elderly patients with poor bone stock, cuff insufficiency, or severe comminution. Pediatric cases require physeal-sparing strategies. Conclusions: GTFDs management demands an individualized approach based on fragment displacement and direction, patient age and activity level, and bone quality. While 5 mm remains the common threshold, lower cutoffs are increasingly adopted in active patients. A tiered treatment algorithm integrating displacement thresholds, fracture morphology, and patient factors is proposed to support surgical decision making. The incorporation of fracture morphologic classifications further refines fixation strategy. Further prospective and pediatric-specific studies are needed to refine treatment algorithms and validate outcomes. Full article

This paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of two-asset financial derivatives. The multivariate models are built to ensure two conditions. First, marginals follow desirable processes, e.g., we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one-dimensional process. These conditions lead to a specific choice of the dependence structure in the form of a local-correlation model. Two popular multi-asset options are entertained: a spread option and a basket option. Full article

The presented research is focused on the development of the bus rapid transit (BRT) system, combining the high capacity of rail transport with the flexibility of bus routes. Classic BRT systems have certain limitations, particularly concerning a single rolling stock capacity. The main motivation of the work is to find efficient and cost-effective solutions to increase passenger traffic in the BRT system while optimizing fuel consumption. The main contribution of this study is the comprehensive analysis and optimization of various configurations of trailer bus trains, which represent a flexible and cost-effective alternative to traditional single or articulated buses. Based on two schemes, four possible options for using trailer bus trains are offered, which differ in the number of sections and working engines. Among the suggested schemes of trailer bus trains, the two-section and three-section schemes with all engines running and the three-section scheme with one engine turned off are appropriate for use due to improved fuel efficiency indicators with better or acceptable traction and speed properties. Calculations carried out on a mathematical model show that, for example, a two-section bus train can provide a reduction of specific fuel consumption per passenger by 6.3% compared to a single bus at full load, while a three-section train can provide even greater savings of up to 8.4%. Selective shutdown of one of the engines in a multi-section train can lead to an additional improvement in fuel efficiency by 5–10%, without leading to a critical reduction in the required traction characteristics. Full article

COVID-19 has caused global problems with complex ramifications. Vulnerable households worry about disruptions to food security. Mobility restrictions, decreased salaries, and supply chain disruptions have increased food insecurity. This study examined the best food security model and its determinants. The primary research data were collected from 257 respondents via cluster random sampling. Binary logistic regression, using R-Studio, was employed to analyze the data. The study showed that the Minimal Model (MM) was optimal in explaining food security status, with three predictors: the available food stock (AFS), education of the household head (EHH), and household income (HIc). This aligned with studies showing that food purchase ability depends on income and education. Male household heads demonstrated better food security than females, while women’s education influenced consumption through improved nutritional knowledge. Higher income provides more alternatives for meeting needs, while decreased income limits options. Food reserve storage influenced household food security during the pandemic. The Minimal Model effectively influenced food security through the AFS, EHH, and HIc. The findings underline the importance of available food stock, household head education, and household income in developing approaches to assist food-insecure households. The research makes a significant contribution to ensuring food availability and promoting sustainable development post-pandemic. Full article

Biofloc technology (BFT) represents a promising approach among sustainable options for the sustainable intensification of shrimp aquaculture, helping to mitigate environmental impacts while maintaining production yields. This study evaluated the effects of stocking density (200, 400, 600, and 800 ind/m³) on the water quality, nitrogen dynamics, and production performance of Penaeus vannamei in BFT systems with limited water exchange (<10%). During an eight-week production-scale trial, water quality exhibited density-dependent deterioration, with TAN and NO₂⁻-N peaks increasing from 0.4 to 2.3 mg/L and 1.0 to 4.2 mg/L, respectively, as density rose from 200 to 800 ind/m³. Concurrently, DO and pH declined significantly from 6.7 to 5.1 mg/L and 7.6 to 7.3, respectively. Production performance revealed critical trade-offs: while yield rose from 3.62 to 9.09 kg/m³, individual growth metrics declined, including harvest body weight (19.14 to 14.12 g), size variation (14.03% to 23.90%), and survival rate (94.6% to 79.8%). Quadratic regression analysis and response surface analysis identified 400~600 ind/m³ as the optimal density range, achieving balanced outcomes: yield (6.74~8.43 kg/m³), harvest body weight (16.72~18.03 g), survival rate (84.0%~93.5%), and feed conversion ratio (1.14~1.22). These findings provide actionable guidelines for optimizing stocking density in commercial BFT systems, highlighting the importance of balancing productivity with environmental sustainability under limited water exchange. Full article

This research empirically investigates how the adoption of restricted stock units (RSUs) affects earnings per share (EPS) and operating profit, focusing on variations across industries. RSUs have emerged as a strategic compensation tool for promoting alignment between employee interests and long-term organizational objectives, while overcoming the short-sighted focus typically associated with conventional stock options. However, previous studies have mainly focused on analyzing the average effect of RSU or verifying only whether there is a short-term improvement in performance after its introduction, and there has been no sufficient review of the long-term effects. In addition, there is a lack of analyses on how the effects of RSU differ by industry. To fill this research gap, this study applied hierarchical regression analysis to S&P 500 company data from 1997 to 2023 to compare and analyze the differential effects of RSU by industry. The analysis showed that the EPS and operating income were only significantly affected by some industries in the early stages of RSU introduction, but the EPS and operating income were significantly improved in all industries in the long term. In addition, it was confirmed that the effects of RSU differ depending on the characteristics of the industry. This study empirically verifies the long-term effects of RSU and the differences by industry, offering practical insights for executives and shareholders when utilizing RSUs as a forward-looking compensation mechanism that fosters sustainable performance and enduring corporate value. Full article

Conventional sources of electricity are limited and they pollute the Earth, so it is necessary to think about an additional source of electricity in the future. Nuclear power is one of the options. Two scenarios using different shares of nuclear power in the future are described in this paper. Scenario 1 describes a moderate increase in nuclear energy use in the future, but with a tendency for a larger increase over 2050. Scenario 2 describes a significant increase in nuclear energy until 2100. Both scenarios are divided into three sub-scenarios (total six) in which the use of different nuclear technologies is analyzed (conventional liquid water reactors, fast breeder reactors and molten salt reactors using thorium as nuclear fuel). In all scenarios, the phase-out of fossil fuel power plants is assumed. One part of the power system is covered by nuclear power plants, and the remaining part is covered by renewable energy power plants. After 2050, an increasing share of the electricity system will be taken over by RES power plants. Nuclear fuel stocks are also analyzed. It is calculated that currently known nuclear fuel stocks are sufficient to meet the needs in all six scenarios. The carbon dioxide emissions saved due to nuclear energy use instead of conventional energy power plants are calculated. The CO_2eq emission savings for Scenario 1 is 87.4% of the recommended emission savings under the IPCC. The CO_2eq emission savings for Scenario 2 is more than sufficient. A calculation of the economic profitability of nuclear energy use is made in relation to fossil power plants and renewable energy power plants. According to calculations, nuclear energy is profitable compared to other energy sources. Nuclear energy use is positive from all the mentioned aspects. Full article

Pakistan’s marine fishing industry is crucial to the country’s economy, generating employment opportunities and foreign revenue. It produces 80% of the country’s total fish production. Otolithes ruber is a commercially important fish on the Makran coast of Pakistan, contributing significantly to the region’s croaker fisheries. This study is the first to apply three length-based approaches for assessing the stock status of O. ruber in the Makran coast: (1) TropFishR to estimate the mortality, growth parameters, and current exploitation status, reference points based on the yield per recruitment model, (2) the length-based Bayesian biomass method (LBB) to calculate stock biomass, and (3) the length-based spawning potential ratio (LBSPR) to estimate the spawning potential ratio. The length–weight relationship of Otolithes ruber was a positive allometric pattern (b = 3.28; R² = 0.94). Growth parameters for Otolithes ruber were L_∞ = 55.47 cm, K = 0.50 year⁻¹. The calculated total mortality rate (Z), natural mortality (M), and fishing mortality (F) were 2.27 year⁻¹, 0.67 year⁻¹, and 1.6 year⁻¹, respectively. The exploitation rate (E) was 0.70, indicating severe overexploitation. The current length at first capture (Lc₅₀) = 27.37 cm was lower than that at first maturity (Lm₅₀) = 30.75 cm, indicating growth overfishing. The current spawning potential ratio (8%) was lower than the optimal value (40%), indicating recruitment overfishing. The current biomass, concerning virgin biomass B/B_o, was also 8%, resulting in a 92% stock decline. We recommend reducing the exploitation pressure by limiting the commercial catch to an optimum length range of 34.5–42.2 cm and reducing fishing pressure by 40% to ensure sustainable fishery management. Full article

This study examines whether Chief Executive Officers (CEOs) exercise a greater proportion of their exercisable options in response to firm-specific stock price bubbles. For a sample of U.S. firms from 1992 to 2021, the study identifies stock price bubble periods using the Generalized Sup Augmented Dickey-Fuller (GSADF) method. A bubble is a statistical measure that detects an ex-post firm-specific stock price exuberance that creates abnormally high variation in stock prices arising from changes in discount rates, R&D and market liquidity. If executives have private information and can infer firm-specific bubbles, they are likely to exercise a greater proportion of their exercisable stock options during bubbles to benefit from their firms’ stock price exuberance. Using data aggregated at the CEO-year level, we find that executives are prone to exercising a larger portion of their vested stock options during market bubbles, with the aim of monetizing on the exuberance in the firm’s stock price. They leverage their expertise and their acquired price-sensitive private information to identify these bubbles. We also find that CEOs’ option exercise activity increases as the duration of the bubble increases to capture the price momentum. Full article

Since the emergence of the Black–Scholes model (BSM) in the early 1970s, models for the pricing of financial options have been developed and evolved with mathematical tools that provide greater efficiency and accuracy in the valuation of these assets. In this research, we have used the generalized conformable derivatives associated with seven obtained conformable models with a closed-form solution that is similar to the traditional Black and Scholes. In addition, an empirical analysis was carried out to test the models with Mexican options contracts listed in 2023. Six foreign options were also tested, in particular three London options and three US options. With this sample, in addition to applying the seven generalized conformable models, we compared the results with the Heston model. We obtained much better results with the conformable models. Similarly, we decided to apply the seven conformable models to the data of the Morales et al. article, and we again determined that the conformable models greatly outperform the approximation of the Black, Scholes (BS), and Merton model with time-varying parameters and the basic Khalil conformable equation. In addition to the base sample, it was decided to test the strength of the seven generalized conformable models on 10 stock options that were out-sampled. In addition to the MSE results, for the sample of six options whose shares were traded in the London and New York stock markets, we tested the positivity and stability of the results. We plotted the values of the option contracts obtained by applying each of the seven generalized conformable models, the values of the contracts obtained by applying the traditional Heston model, and the market value of the contracts. Full article

This study establishes a combination method-based prediction model for the CSI 300 stock index price embedded with options market information. Firstly, utilizing options and spot market information, a BP neural network is employed to predict the CSI 300 stock index price. Secondly, a logical framework based on a combination method is constructed to further optimize the CSI 300 stock index price prediction through decomposition–clustering, error adjustment, and weighted integration approaches. The results demonstrate the following: (1) Compared to price predictions based solely on spot market information, the introduction of options market information significantly enhances the forecasting performance for the CSI 300 index price. (2) From the perspective of options moneyness classification, after incorporating options information, different types of options contracts exhibit varying impacts on the CSI 300 index price prediction. Prior to optimization, predictions incorporating in-the-money call options with maximum trading volume yield the optimal performance based on the MSE metric. (3) Under the logical framework of the combination method, the prediction effect for the CSI 300 stock index price is gradually improved after introducing the decomposition–clustering method, the error adjustment method, and the price-weighted integration method, which shows that it is appropriate to use the combination method to optimize the price prediction. Overall, this study proposes a combination method for price forecasting incorporating options market information across diverse contract types. It allows for weighted integration of prediction results derived from various options information, offering a novel research angle for spot market price prediction. The study also underscores the importance of implicit information mining and multi-market information fusion for price prediction, which is expected to become a key research focus in this field. Full article

Most of Italy’s residential building stock predates contemporary structural safety and energy efficiency regulatory frameworks. Today, policymakers face the challenge of choosing whether to prioritise renovation or opt for demolition and reconstruction; both options carry significant socio-economic and environmental consequences and require extensive knowledge of the built heritage. However, detailed architecture-specific data remain scarce, as existing databases lack granular information. Moreover, traditional urban-level knowledge mapping approaches may be resource-intensive. To address this data gap, this study proposes a semi-automated methodology for generating graph-based digital models representing residential building floor plans. Using graph theory, floor spatial layouts are mapped into connectivity graphs and transformed into topological models. These models are enriched with functional data about spaces by assigning conditional topological rules based on node centrality metrics. The method was tested on 98 buildings in Bologna, Italy, yielding an 89.8% success rate and demonstrating its effectiveness in data-limited contexts. The resulting dataset facilitates the analysis of floor spatial configurations and the extraction of geometric attributes, laying the foundation for future analyses that will integrate machine learning techniques for functional detection and typological clustering. Full article