Scientific African最新文献_第2页

AI-based assessment of climate change impacts on water requirements in Egypt’s New Delta 基于人工智能的气候变化对埃及新三角洲用水需求影响评估

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-13 DOI: 10.1016/j.sciaf.2026.e03182

Attia M El-Tantawi , Fawzia I Moursy , Wael M Almetwaly , Mohamed El-Sayed El-Mahdy

This study assesses the influence of climate change on the projected water requirements (WR) for wheat cultivation in Egypt's New Delta region. Climate projections from five CMIP6 (Coupled Model Intercomparison Project Phase 6) regional climate models under three socio-economic scenarios (SSP2.6, SSP4.5, SSP8.5) were employed to estimate WR utilizing a Deep Learning Artificial Intelligence (DLAI) model. Thirteen meteorological stations throughout the New Delta were examined to evaluate drought indicators, such as the Reconnaissance Drought Index (RDI/eRDI) and the Standardized Precipitation Index (SPI/aSPI). Results indicate a consistent rise in annual RDI and eRDI across most stations, with the most pronounced trends observed in AlFrafrah and Borg Elarab. Conversely, SPI and aSPI values demonstrated declining trends, indicating increasing dryness; approximately 16 % of SPI observations corresponded to moderately dry conditions, with certain stations such as Baharia and Siwa exhibiting severe dryness. WR exhibits a consistent upward trajectory across all scenarios, attaining its peak levels by 2100 under SSP8.5. WR increases by 9–12 % under SSP2.6, 15–18 % under SSP4.5, and 24–36 % under SSP8.5. These findings indicate that climate-induced increases in WR will significantly raise irrigation requirements, highlighting the necessity for ongoing evaluation of water resource development and allocation strategies.

本研究评估了气候变化对埃及新三角洲地区小麦种植预估需水量的影响。利用5个CMIP6（耦合模式比对项目第6阶段）区域气候模式在3种社会经济情景（SSP2.6、SSP4.5、SSP8.5）下的气候预估，利用深度学习人工智能（DLAI）模型估算WR。对新三角洲地区的13个气象站进行了干旱指标评估，如干旱侦察指数（RDI/eRDI）和标准化降水指数（SPI/aSPI）。结果表明，大多数站点的年度RDI和eRDI持续上升，其中AlFrafrah和Borg Elarab的趋势最为明显。相反，SPI和aSPI值呈下降趋势，表明干燥程度增加；大约16%的SPI观测值对应于中度干燥条件，某些站点如巴哈里亚和西瓦显示严重干燥。在所有情景下，WR呈现出一致的上升轨迹，在SSP8.5情景下，WR将在2100年达到峰值。WR在SSP2.6下增加9 - 12%，SSP4.5下增加15 - 18%，SSP8.5下增加24 - 36%。这些研究结果表明，气候引起的水水量增加将显著提高灌溉需求，突出了对水资源开发和分配战略进行持续评估的必要性。

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引用次数: 0

Advanced lifetime data modeling: Extension, structural properties and an application 高级生命周期数据建模：扩展、结构属性和应用程序

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-12 DOI: 10.1016/j.sciaf.2026.e03185

Denylson Takunda Dondo , Regent Retrospect Musekwa , Precious Mdlongwa

This study provides a comprehensive investigation of the Toppe Leone Lomax Logarithmic Distribution (TLLomLD), a newly developed probabilistic model designed to capture various data patterns. The theoretical contribution begins with a rigorous mathematical formulation of the distribution, followed by a detailed examination of its key structural properties. To enable statistical inference, a maximum likelihood estimation (MLE) procedure is utilized for estimating the model parameters. The performance of the proposed framework is further assessed through extensive simulation experiments, demonstrating both the robustness and consistency of the estimators. Finally, the practical relevance of the TLLomLD is illustrated using a real-world dataset, where it exhibits superior adaptability compared to some existing distributions in literature. Collectively, these findings underscore the theoretical depth and applied utility of the TLLomLD, highlighting its potential as a powerful analytical tool for statisticians and applied researchers working with heterogeneous datasets.

本研究提供了对Toppe Leone Lomax对数分布（tlllomld）的全面调查，这是一种新开发的概率模型，旨在捕获各种数据模式。理论贡献始于对分布的严格数学公式，然后是对其关键结构特性的详细检查。为了实现统计推断，使用最大似然估计（MLE）过程来估计模型参数。通过广泛的仿真实验进一步评估了所提出框架的性能，证明了估计器的鲁棒性和一致性。最后，使用现实世界的数据集说明了TLLomLD的实际相关性，与文献中的一些现有分布相比，它表现出优越的适应性。总的来说，这些发现强调了TLLomLD的理论深度和应用效用，突出了它作为统计学家和应用研究人员处理异构数据集的强大分析工具的潜力。

引用次数: 0

Short-term PV plant power forecasting model using CNN-GRU with XGBoost algorithm 基于XGBoost算法的CNN-GRU短期光伏电站功率预测模型

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-11 DOI: 10.1016/j.sciaf.2026.e03184

Lahoucine Oumiguil, Ali Nejmi

Accurate short-term forecasting of photovoltaic (PV) power output is crucial for the efficient integration and operation of PV systems in smart grids. However, the intrinsic unpredictability and hierarchical discontinuity of PV data complicate the attainment of good predictive accuracy through conventional regression procedures. This research introduces a combined deep learning and gradient boosting model for short-term PV power forecasting. A convolutional neural network (CNN) is initially utilized to get important spatial features from input variables. Then, these features are coupled with historical PV power measurements in a gated recurrent unit (GRU) to capture temporal dependencies. The XGBoost technique is also used to represent complex nonlinear relationships in the data, which makes predictions even more accurate. The model is tested using actual PV plant data and gets a R² of 0.79, an RMSE of 23.30 MW, and a MAPE of 16.68%. These improvements show that the hybrid model works well to make predictions more accurate and reliable for real-world use.

准确的光伏发电输出短期预测对于智能电网中光伏系统的高效集成和运行至关重要。然而，PV数据固有的不可预测性和层次不连续性使传统回归方法难以获得良好的预测精度。本文介绍了一种结合深度学习和梯度增强的短期光伏发电功率预测模型。首先利用卷积神经网络（CNN）从输入变量中获取重要的空间特征。然后，将这些特征与门控循环单元（GRU）中的历史PV功率测量相结合，以捕获时间依赖性。XGBoost技术还用于表示数据中的复杂非线性关系，这使得预测更加准确。利用实际光伏电站数据对模型进行了检验，得到R²为0.79，RMSE为23.30 MW， MAPE为16.68%。这些改进表明，混合模型可以很好地使预测更准确、更可靠地用于现实世界。

引用次数: 0

Conscious or unconscious digitalised credit decisions? An application of the dual-system theory to agricultural finance and welfare 有意识还是无意识的数字化信贷决策？二元制度理论在农业财政与福利中的应用

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-11 DOI: 10.1016/j.sciaf.2026.e03186

Mohammed Tanko, Awal Fuseini

There are two systems according to the dual-system theory that influence human decision-making processes in psychology classified as system one and system two. These systems impact human cognition and behaviour and results in actions that are either unconsciously or consciously taken. In the first system, decisions are not the results of deliberate reasoning but default and often intuitive, offering quick but not rational and consistent results. Alternatively, the second system is controlled and deliberate and as such dominates the default system under time sufficiency. Despite the several initiatives to make credit available to farmers, commercial banks consider the agricultural sector risky and informal, with a high cost of holding capital. This result in farmers depending on costly loans from informal sectors that aggravate their debt situations, and restrict their ability to invest in productivity-enhancing inputs. Digitalized microcredit offers farmers alternatives and broad possibilities to access credit with improved efficiency and capable of reaching several underserved rural farming communities. This study therefore intends to examine the effects of digitalized credit on the welfare of farmers using ordinary least square approach and corroborated with Propensity Score Matching (PSM) as a robustness check. The findings indicate that digital financial services increased the income and welfare of rural households, as it provided an accessible and more formalized means of financial support. The research also confirmed the dual-system theory posits that deliberate and conscious decisions, the results of system two lead to reasonable and beneficial outcomes as shown by the welfare indicator in the treatment effects analysis.

根据双系统理论，心理学上有两个影响人类决策过程的系统，分别是系统一和系统二。这些系统影响人类的认知和行为，并导致无意识或有意识地采取行动。在第一个系统中，决策不是深思熟虑的结果，而是默认的，通常是直觉的，提供快速但不理性和一致的结果。另一种选择是，第二种系统是受控的、经过深思熟虑的，因此在时间充足的情况下，它支配着默认系统。尽管有几项向农民提供信贷的倡议，但商业银行认为农业部门风险很大，不正规，持有资本的成本很高。这导致农民依赖来自非正规部门的昂贵贷款，从而加剧了他们的债务状况，并限制了他们投资于提高生产力投入的能力。数字化小额信贷为农民提供了获得信贷的选择和广泛可能性，提高了效率，并能够覆盖几个服务不足的农村农业社区。因此，本研究打算使用普通最小二乘法来检验数字化信贷对农民福利的影响，并通过倾向得分匹配（PSM）作为稳健性检查加以证实。研究结果表明，数字金融服务增加了农村家庭的收入和福利，因为它提供了一种更容易获得和更正式的金融支持手段。研究还证实了双系统理论的假设，即经过深思熟虑和有意识的决策，系统二的结果导致合理和有益的结果，如治疗效果分析中的福利指标所示。

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引用次数: 0

Optimization of cellulase production by Nigrospora oryzae (berk and br.) petch and its application in biomass saccharification and ethanol production 米黑孢菌（黑孢菌和黑孢菌）产纤维素酶的优化及其在生物质糖化和乙醇生产中的应用

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-10 DOI: 10.1016/j.sciaf.2026.e03181

Dukuzimana Olivier, George Isanda Omwenga, Dennis Kipngenoh Cheruiyot, Mathew Piero Ngugi

The increasing demand for sustainable biofuel alternatives has intensified the search for new microbial sources of cellulolytic enzymes. This study aim to evaluate the cellulolytic potential of Nigrospora oryzae and to optimize its cellulase enzyme production using low-cost lignocellulosic substrates, specifically maize cobs and sugarcane bagasse, under solid-state fermentation. Additionally, the study assess the efficiency of crude cellulase enzymes in biomass saccharification and bioethanol production. Molecular identification confirmed the isolate as N. oryzae through ITS sequencing and phylogenetic analysis. N. oryzae exhibited significant cellulolytic activity on carboxymethylcellulose-Congo red agar. Maize cobs and sugarcane bagasse were used as primary substrates for enzyme production. The cultural parameters were optimized using a one-variable-at-a-time (OVAT) approach. The peak filter paperase (FPase) activity reached 11.3 ± 0.94 IU/ml for maize cobs and 8.9 ± 0.47 IU/ml for bagasse on day 9. Additionally, maximum endoglucanase activity was recorded at 19.7 ± 1.74 IU/ml and 15.5 ± 0.76 IU/ml on day 12, respectively. Exoglucanase activity peaked at 3.46 ± 0.25 IU/ml for maize cobs and 2.06 ± 0.11 IU/ml for bagasse. The optimal pH for enzyme secretion ranged from 5 to 6. Nitrogen supplementation with ammonium nitrate, urea, and peptone significantly enhanced enzyme yields. Among the carbon sources tested, fructose, mannitol, and sucrose markedly improved enzyme production compared to glucose, suggesting a partial relief from carbon catabolite repression. An enzyme loading of 5% optimized saccharification efficiency. Simultaneous saccharification and fermentation (SSF) using Saccharomyces cerevisiae achieved maximum ethanol concentrations at substrate levels between 5% and 15%, demonstrating the bio-conversion potential of this system. These findings position Nigrospora oryzae as a promising non-conventional cellulase producer for lignocellulosic bioconversion, with significant implications for sustainable ethanol production.

对可持续生物燃料替代品的需求不断增加，加强了对纤维素水解酶的新微生物来源的研究。本研究旨在评估米黑孢菌的纤维素水解潜力，并在固态发酵条件下，利用低成本的木质纤维素基质，特别是玉米棒子和甘蔗甘蔗渣，优化其纤维素酶的生产。此外，本研究还评估了粗纤维素酶在生物质糖化和生物乙醇生产中的效率。通过ITS测序和系统发育分析，证实该分离物为N. oryzae。N. oryzae对羧甲基纤维素刚果红琼脂具有显著的纤维素水解活性。以玉米芯和甘蔗渣为主要底物制备酶。采用单变量-一次（OVAT）法对培养参数进行优化。第9天，玉米芯滤纸酶（FPase）活性峰值为11.3±0.94 IU/ml，甘蔗渣为8.9±0.47 IU/ml。第12天内切葡聚糖酶活性最高，分别为19.7±1.74 IU/ml和15.5±0.76 IU/ml。玉米芯和甘蔗渣的外葡聚糖酶活性分别为3.46±0.25 IU/ml和2.06±0.11 IU/ml。酶分泌的最佳pH值为5 ~ 6。添加硝酸铵、尿素和蛋白胨显著提高了酶产率。在测试的碳源中，果糖、甘露醇和蔗糖比葡萄糖显著提高酶的产量，这表明碳分解代谢抑制得到部分缓解。加酶量为5%时，糖化效率最佳。使用酿酒酵母的同时糖化和发酵（SSF）在底物水平达到5%至15%之间的最大乙醇浓度，证明了该系统的生物转化潜力。这些发现将米黑孢菌定位为一种有前途的木质纤维素生物转化的非常规纤维素酶生产者，对可持续乙醇生产具有重要意义。

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引用次数: 0

Stacked ensemble modelling of imported malaria from African countries to China 非洲国家输入到中国的疟疾的叠加集合模型

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-10 DOI: 10.1016/j.sciaf.2026.e03180

Eric KamanaID , Jijun ZhaoID

Imported malaria has been a risk of malaria reemergence in countries that have successfully eliminated malaria. This study developed an ensemble machine learning model to analyze and predict imported malaria cases from African countries to China based on data collected from 2012 to 2018.

The stacked ensemble model which combines LASSO, Random forest, and Decision Tree regression, showed a significant improvement in performance, achieving an R² range of 0.82 to 0.98, indicating high predictive accuracy, and outperformed individual base models, with a gain of approximately 15% in MAE reduction, highlighting its effectiveness.

The findings indicate that the increase in Chinese workers, foreign direct investment (FDI) and existing malaria incidence in African countries associate significantly with the rise in imported malaria cases (P = 0.001). The results underscore the importance of collaboration between China and African nations to address malaria, particularly in formulating targeted public health strategies to mitigate imported cases linked to labor movements.

This predictive tool can assist in guiding health interventions and resource allocation in China as intercountry movements continue to grow.

在已成功消除疟疾的国家，输入性疟疾是疟疾再次出现的一个风险。本研究基于2012年至2018年收集的数据，开发了一个集成机器学习模型，用于分析和预测非洲国家向中国输入的疟疾病例。结合LASSO、随机森林和决策树回归的堆叠集成模型在性能上有了显著的提高，R2范围为0.82 ~ 0.98，表明预测精度较高，并且优于单个基础模型，MAE降低了约15%，突出了其有效性。研究结果表明，中国工人、外国直接投资（FDI）和非洲国家现有疟疾发病率的增加与输入性疟疾病例的增加显著相关（P = 0.001）。研究结果强调了中国和非洲国家合作应对疟疾的重要性，特别是在制定有针对性的公共卫生战略以减少与劳工运动有关的输入性病例方面。随着跨国流动的持续增长，这一预测工具有助于指导中国的卫生干预措施和资源分配。

{"title":"Stacked ensemble modelling of imported malaria from African countries to China","authors":"Eric KamanaID , Jijun ZhaoID","doi":"10.1016/j.sciaf.2026.e03180","DOIUrl":"10.1016/j.sciaf.2026.e03180","url":null,"abstract":"<div><div>Imported malaria has been a risk of malaria reemergence in countries that have successfully eliminated malaria. This study developed an ensemble machine learning model to analyze and predict imported malaria cases from African countries to China based on data collected from 2012 to 2018.</div><div>The stacked ensemble model which combines LASSO, Random forest, and Decision Tree regression, showed a significant improvement in performance, achieving an R<sup>2</sup> range of 0.82 to 0.98, indicating high predictive accuracy, and outperformed individual base models, with a gain of approximately 15% in MAE reduction, highlighting its effectiveness.</div><div>The findings indicate that the increase in Chinese workers, foreign direct investment (FDI) and existing malaria incidence in African countries associate significantly with the rise in imported malaria cases (<em>P</em> = 0.001). The results underscore the importance of collaboration between China and African nations to address malaria, particularly in formulating targeted public health strategies to mitigate imported cases linked to labor movements.</div><div>This predictive tool can assist in guiding health interventions and resource allocation in China as intercountry movements continue to grow.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03180"},"PeriodicalIF":3.3,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A generalized lifetime model based on Ailamujia distribution: Statistical properties, different inference estimation and applications to several fields 基于Ailamujia分布的广义寿命模型：统计性质、不同推断估计及其在多个领域的应用

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-08 DOI: 10.1016/j.sciaf.2026.e03179

A.A. Ahmed , Eslam Abdelhakim Seyam , Ahmed R. El-Saeed , Eman O. Abdalla , Shiraz Naserelden , Said G. Nassr

The purpose of this article is to present a new, more flexible lifetime distribution that can be used to model different datasets in different fields. The new distribution is an expansion of the Ailamujia distribution using Khalil new generalized family called Khalil new generalized Ailamujia (KNGA) distribution. This distribution has a J shape, right-skewed, and approximately symmetric-shaped densities. Moreover, its hazard rate function can be increasing, increasing–constant, decreasing, or upside-down bathtub-shaped. Several of its statistical properties such as quantile, median, probability weighted moments, moments, incomplete moments, mean deviations, inequality measures, moments of residual life and reversed residual life functions, measure of uncertainty, and order statistics are explored. The parameter estimation is carried out using two classical methods, namely, the maximum likelihood method and the maximum product spacing method. Moreover, the Bayesian method under symmetric and asymmetric loss functions is presented based on the two classical methods. In addition, the credible intervals of the different parameters were also obtained. A significant amount of simulation studies was conducted to examine the effectiveness of these estimates. We present a methodology to generate samples on R program from any new distribution, even if it doesn’t have a closed form for the quantile function. Finally, different real-world data sets are analyzed to demonstrate the utility and adaptability of the proposed model.

本文的目的是介绍一种新的、更灵活的生命周期分布，可用于为不同领域的不同数据集建模。新分布是利用Khalil新广义族对Ailamujia分布的扩展，称为Khalil新广义Ailamujia （KNGA）分布。该分布呈J形，右偏斜，密度近似对称。此外，它的危险率函数可以是增加、增加不变、减少或倒置浴缸形。探讨了它的一些统计性质，如分位数、中位数、概率加权矩、矩、不完全矩、平均偏差、不等式测度、剩余寿命矩和反向剩余寿命函数、不确定性测度和有序统计。参数估计采用两种经典方法进行，即最大似然法和最大积间距法。在此基础上，提出了对称损失函数和非对称损失函数下的贝叶斯方法。此外，还得到了各参数的可信区间。为了检验这些估计的有效性，进行了大量的模拟研究。我们提出了一种在R程序上从任何新分布生成样本的方法，即使它没有分位数函数的封闭形式。最后，对不同的实际数据集进行了分析，以证明所提出模型的实用性和适应性。

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引用次数: 0

Spatio-temporal evolution of the surface dynamics and the underground water flow of the natural lake Tamda (Middle Atlas, Morocco) 摩洛哥中阿特拉斯天然湖泊Tamda地表动态与地下水流动的时空演变

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-07 DOI: 10.1016/j.sciaf.2026.e03178

Jamal Abbach , Said El Moussaoui , Hajar El Talibi , Charaf Eddine Bouiss

Lake Tamda is a temporary endorheic lake located in the central Middle Atlas (Morocco) that exhibits pronounced seasonal filling and drying phases. This study aims to quantify the respective roles of climatic forcing and subsurface drainage in controlling the lake’s hydrological dynamics within a semi-arid mountain environment. We combine multi-temporal satellite observations (2011–2021) with field measurements, piezometric data, and rainfall records to track variations in lake surface area and groundwater response. Results show that lake expansion is strongly controlled by winter–spring precipitation and snowmelt, while rapid summer drawdown cannot be explained by evaporation alone. Instead, drainage through karstified carbonate bedrock and permeable zones within the landslide dam plays a major role in water loss, with structural lineaments aligning the lake with downstream wells and springs. During recent dry years (2019–2021), reduced rainfall and rising temperatures led to recurrent complete desiccation by late summer. These findings demonstrate that Lake Tamda functions as a precipitation-filled, fracture-drained seasonal lake highly sensitive to climate variability. The lake represents both a valuable geoheritage site and a vulnerable hydrosystem, highlighting the need for integrated hydrogeological monitoring to assess future impacts of climate change.

Tamda湖是位于摩洛哥中部阿特拉斯的一个临时内河湖泊，具有明显的季节性填充和干燥阶段。本研究旨在量化气候强迫和地下排水在控制半干旱山地环境下湖泊水文动态中的各自作用。我们将多时相卫星观测（2011-2021年）与野外测量、测压数据和降雨记录相结合，跟踪湖泊表面积和地下水响应的变化。结果表明，冬春季降水和融雪对湖泊的扩张有强烈的控制作用，而夏季的快速萎缩不能仅用蒸发来解释。相反，通过喀斯特碳酸盐基岩和滑坡坝内渗透带的排水在水分流失中起主要作用，其结构轮廓使湖泊与下游水井和泉水对齐。在最近的干旱年份（2019-2021年），降雨量减少和气温上升导致夏末经常完全干燥。这些结果表明，坦达湖是一个对气候变化高度敏感的降水填充、裂缝排水的季节性湖泊。该湖既是宝贵的地质遗产，也是脆弱的水文系统，因此需要进行综合水文地质监测，以评估气候变化对未来的影响。

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引用次数: 0

Two new unit-interval distributions with applications to COVID-19 and reservoir capacity data 两个新的单位间隔分布，应用于COVID-19和水库容量数据

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-05 DOI: 10.1016/j.sciaf.2025.e03140

M.E. Sobh , Ammar M. Sarhan

Accurate modeling of data restricted to the unit interval is essential across many applied disciplines. This paper proposes two new single-parameter probability distributions tailored for variables supported on

(0, 1)

. The models are mathematically tractable and exhibit notable flexibility, with analytical expressions derived for their survival and hazard functions, moments, and parameter-driven behavior. Their single-parameter structure enables closed-form maximum likelihood and Bayesian estimators, avoiding the heavy numerical optimization typically required by existing unit-interval models. The maximum likelihood estimators are shown to be global solutions, and the Bayesian framework benefits from the conjugacy of the gamma prior, allowing for efficient posterior inference. The performance of the proposed distributions is assessed through extensive simulations and applications to four real datasets. These datasets were selected to encompass both positively and negatively skewed structures, allowing for an evaluation of model performance across diverse distributional shapes. The empirical results demonstrate that the proposed models provide an excellent fit for all skewness patterns and consistently outperform ten established benchmark models based on standard goodness-of-fit criteria.

在许多应用学科中，对限于单位区间的数据进行精确建模是必不可少的。本文针对（0,1）上支持的变量，提出了两个新的单参数概率分布。这些模型在数学上易于处理，并表现出显著的灵活性，其生存和危险函数、矩和参数驱动行为的解析表达式推导出来。它们的单参数结构实现了封闭形式的最大似然和贝叶斯估计，避免了现有单位区间模型通常需要的大量数值优化。最大似然估计量被证明是全局解，贝叶斯框架受益于伽马先验的共轭性，允许有效的后验推理。通过广泛的模拟和四个实际数据集的应用，评估了所提出的分布的性能。这些数据集被选择来包含积极和消极倾斜的结构，允许在不同的分布形状中评估模型的性能。实证结果表明，所提出的模型对所有偏度模式都提供了很好的拟合，并且始终优于基于标准拟合优度标准的10个已建立的基准模型。

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引用次数: 0

Effects of single and double- pulse GMAW on the WAAM fabrication of Al5356 wall on Al- 6082 substrate 单脉冲和双脉冲GMAW对Al- 6082基板上Al5356壁WAAM制备的影响

IF 3.3 Q2 MULTIDISCIPLINARY SCIENCES

Scientific African

Pub Date : 2026-01-04 DOI: 10.1016/j.sciaf.2026.e03177

Ifeyinwa G. Ibekwe , Ahmed H. Awad , Marawan Abdelwahed , Fatai O. Aramide , Mohamed A. Taha

This study investigates the processability of Al5356 wire using Wire Arc Additive Manufacturing (WAAM) with Double Pulse (DP-GMAW) and Single Pulse (SP-GMAW) welding modes. The research aims to understand how varying heat input and pulsing strategies affect the WAAM-processed component morphology, microstructural evolution, and mechanical performance of the fabricated components. The results revealed that DP-GMAW could improve bead geometry, reduce porosity, and lead to refined grain structure through enhanced pool stirring compared to SP- GMAW. Moreover, hardness measurements of the vertical structures show a more uniform distribution along the vertical direction. The SP-GMAW process, although producing higher porosity (3.55%), showed higher tensile strength of 265 MPa compared to DP-GMAW. Both methods demonstrated mechanical properties surpassing those of cast Al5356 alloy. The findings provide insights into optimizing pulsed arc welding parameters for enhanced performance in aluminum WAAM applications.

本研究采用电弧增材制造（WAAM）双脉冲（DP-GMAW）和单脉冲（SP-GMAW）焊接方式对Al5356丝的可加工性进行了研究。该研究旨在了解不同的热输入和脉冲策略如何影响waam加工组件的形貌、微观结构演变和制造组件的机械性能。结果表明，与SP- GMAW相比，DP-GMAW可以通过增强池搅拌改善晶粒几何形状，降低孔隙率，细化晶粒结构。此外，垂直结构的硬度测量显示沿垂直方向的分布更为均匀。与DP-GMAW相比，SP-GMAW工艺的孔隙率（3.55%）更高，抗拉强度为265 MPa。两种方法的力学性能均优于铸造Al5356合金。研究结果为优化脉冲弧焊参数以提高铝WAAM应用的性能提供了见解。

引用次数: 0