Aims: This current study aimed to analyze the demographic characteristics of the agricultural workforce and demonstrate the impact of these characteristics on agricultural activity in terms of production and diversity. It also aimed to clarify the population distribution of the workforce according to demographic and economic indicators, and finally to evaluate its relationship with agricultural activities. Methodology: A descriptive and analytical approach was adopted, relying on statistical data available from official and field sources. The study also tried to determine the size of the workforce and its geographical, age, educational distribution, and analyze the extent of its contribution to agricultural activity. The correlation coefficient was used to measure the relationship between labor force characteristics and agricultural production indicators in the studied areas. Results: After analyzing all the gathered data, the results showed a positive correlation between the density of the agricultural workforce and the level of agricultural production in most of the studied areas, especially in areas with adequate infrastructure and agricultural services. It also showed that the productive age group of the workforce represents the highest percentage of those employed in this sector, in addition to the concentration of workers with limited education in traditional agricultural activities, which limits the expansion of modern methods. Conclusions: It can be concluded that workforce represents one of the fundamental pillars of agricultural sector development, and that improving its demographic and educational characteristics would contribute to increasing agricultural production efficiency significantly. The study emphasized the importance of supporting agricultural training programs and developing workers' skills in order to achieve optimal use of human resources in this vital sector.
History of scholarship and learning. The humanities
As smart city development deepens, its impact on the urban-rural income gap has become a key concern for both the government and society. This article uses panel data from Chinese prefecture-level cities between 2010 and 2022, treating the pilot smart city policy as a quasi-natural experiment, and applying a multi-period difference-in-differences (DID) method to empirically examine how smart city construction affects the urban-rural income gap. It also analyzes the role of economic agglomeration in this process. The research indicates that smart city development has significantly increased the incomes of urban and rural residents and has positively contributed to sharing development benefits between these areas. Mechanism analysis shows that economic agglomeration plays an important mediating and threshold role—smart cities indirectly influence the urban-rural income distribution by fostering economic agglomeration, with this effect showing nonlinear characteristics at different levels of agglomeration. Based on these findings, the article proposes policy recommendations aimed at optimizing economic agglomeration models and advancing urban-rural integrated development, offering theoretical insights and practical strategies for narrowing the income gap and promoting common prosperity.
History of scholarship and learning. The humanities, Social Sciences
W artykule przedstawiono wyniki badań na temat strategii komunikowania buddyjskich związków wyznaniowych zarejestrowanych w Polsce. Badanie przeprowadzono metodami analizy treści oraz analizy danych zastanych. Wykorzystano założenia etnografii wirtualnej, która ma na celu poznanie i opisanie zachowań ludzi i zjawisk dostępnych w internecie oraz ich efektów. Stwierdzono m.in., że buddyjskie związki wyznaniowe stosują nowe media do realizacji strategii komunikacji. Są one ukierunkowane na: autoprezentację, budowanie relacji między członkami wspólnoty, propagowanie buddyzmu, aksjologizację. Strony internetowe realizują wymienione strategie, zwłaszcza w zakresie autoprezentacji. Profile w mediach społecznościowych służą głównie budowaniu relacji oraz aksjologizacji. Buddyzm w Polsce nie jest zjawiskiem masowym, ale istotnym dla kultury polskiej. Badania w tym zakresie służą więc budowaniu wzajemnego szacunku w warunkach wielokulturowych społeczeństw.
History of scholarship and learning. The humanities, Social sciences (General)
Infinitesimals have seen ups and downs in their tumultuous history. In the 18th century, d'Alembert set the tone by describing infinitesimals as chimeras. Some adversaries of infinitesimals, including Moigno and Connes, picked up on the term. We highlight the work of Cauchy, Noël, Poisson and Riemann. We also chronicle reactions by Moigno, Lamarle and Cantor, and signal the start of a revival with Peano.
Contrastive learning operates on a simple yet effective principle: Embeddings of positive pairs are pulled together, while those of negative pairs are pushed apart. In this paper, we propose a unified framework for understanding contrastive learning through the lens of cosine similarity, and present two key theoretical insights derived from this framework. First, in full-batch settings, we show that perfect alignment of positive pairs is unattainable when negative-pair similarities fall below a threshold, and this misalignment can be mitigated by incorporating within-view negative pairs into the objective. Second, in mini-batch settings, smaller batch sizes induce stronger separation among negative pairs in the embedding space, i.e., higher variance in their similarities, which in turn degrades the quality of learned representations compared to full-batch settings. To address this, we propose an auxiliary loss that reduces the variance of negative-pair similarities in mini-batch settings. Empirical results show that incorporating the proposed loss improves performance in small-batch settings.
We introduce a graph-aware autoencoder ensemble framework, with associated formalisms and tooling, designed to facilitate deep learning for scholarship in the humanities. By composing sub-architectures to produce a model isomorphic to a humanistic domain we maintain interpretability while providing function signatures for each sub-architectural choice, allowing both traditional and computational researchers to collaborate without disrupting established practices. We illustrate a practical application of our approach to a historical study of the American post-Atlantic slave trade, and make several specific technical contributions: a novel hybrid graph-convolutional autoencoder mechanism, batching policies for common graph topologies, and masking techniques for particular use-cases. The effectiveness of the framework for broadening participation of diverse domains is demonstrated by a growing suite of two dozen studies, both collaborations with humanists and established tasks from machine learning literature, spanning a variety of fields and data modalities. We make performance comparisons of several different architectural choices and conclude with an ambitious list of imminent next steps for this research.
We study offline off-dynamics reinforcement learning (RL) to utilize data from an easily accessible source domain to enhance policy learning in a target domain with limited data. Our approach centers on return-conditioned supervised learning (RCSL), particularly focusing on Decision Transformer (DT) type frameworks, which can predict actions conditioned on desired return guidance and complete trajectory history. Previous works address the dynamics shift problem by augmenting the reward in the trajectory from the source domain to match the optimal trajectory in the target domain. However, this strategy can not be directly applicable in RCSL owing to (1) the unique form of the RCSL policy class, which explicitly depends on the return, and (2) the absence of a straightforward representation of the optimal trajectory distribution. We propose the Return Augmented (REAG) method for DT type frameworks, where we augment the return in the source domain by aligning its distribution with that in the target domain. We provide the theoretical analysis demonstrating that the RCSL policy learned from REAG achieves the same level of suboptimality as would be obtained without a dynamics shift. We introduce two practical implementations REAG$_\text{Dara}^{*}$ and REAG$_\text{MV}^{*}$ respectively. Thorough experiments on D4RL datasets and various DT-type baselines demonstrate that our methods consistently enhance the performance of DT type frameworks in off-dynamics RL.
Canada’s ongoing colonial relationship with its Indigenous peoples reflects its overall views on multiculturalism and racial diversity. In her “Land as Pedagogy,” Indigenous scholar Leanne Simpson describes how Indigenous cultures use their traditional lands as a heuristic device to continue the education of their cultural customs and histories throughout generations. Conversely, in Intimacies of Four Continents, Lisa Lowe argues for the sharing of colonial experiences as a way of building intimate connections despite the barriers between ‘continents’ upheld by colonial frameworks. In this talk, I will argue that through close engagement with Indigenous literature and scholarship, Indigenous and racialized Canadians can learn how to share their experiences of living as minorities with one another. Indigenous teachings foster intimate connections across these racial differences and distinctions, acting as a “means to observe the historical division of world processes into those that develop modern liberal subjects and modern spheres of social life” (Lowe 17). Focusing specifically on Simpson’s narration of her experience sharing her Indigenous customs with her co-author, Robyn Maynard in Rehearsals for Living, this talk will present traditional Indigenous lands as a heuristic device for racialized Canadians, arguing that this land provides the space needed to form intimate connections to heal from the traumas of colonialism. Therefore, Indigenous customs teach racialized Canadians the importance of continuing the fight against colonial frameworks within Canada; to lose the battle is to lose the formative aspects of their racialized identities. The overall argument of this talk is that reaching across continents and converging based on our experiences living within colonial frameworks — of which the generational implications continue to live on in our bodies — helps colonized individuals to understand each other by partaking in intimate decolonial acts of education.
تعد الرموز من التقانات المهمة التي تثير فضول المتلقي وتزيد رغبته في الوصول الى قصد الشاعر ، والكشف عن دلالاتها القارة داخل نتاجه الشعري ، فديناميكية الرمز تكفل ولوج القارئ الى عمق النص ، فعمل القارئ يصبح فضاء لقراءات متعددة ، ذات الدلالة البعيدة عن الواقع المذكور ، إذ ان الرمز المكاني في النص الأدبي أداة فاعلة في كشف الخبايا النصية المفروزة من دلالاته في بعده المعبر عن البوح المكنون في أهواء الشاعر المكبوتة في دواخلها والمنطوية على ذاتها ، لذا فان اختيار هذا الموضوع يعد محاولة لتسليط الضوء على تلك الرموز وبخاصة الطللية منها ، وإظهار أهميتها في شعر حسام الدين الحاجري ، وما دامت الرموز متعلقة بالقارئ أكثر من ارتباطها بالنص ، لذا وجب على القارئ تفكيك تلك الرموز ، فهذا البحث قائم على رصدها والكشف عن مكنوناتها وبخاصة الرموز (الطللية) بوصفها مكانا محملا بأبعاد وايحاءات كثيرة .
History of scholarship and learning. The humanities, Arts in general
Kulwa Mwita Mang'ana, Daniel Wilson Ndyetabula, Silver John Hokororo
Small and Medium-Sized Enterprises in agriculture sector, contribute significantly to economic change in developing countries by addressing a wide range of unemployment, nutrition, income poverty, and food security issues. Despite their critical role and contribution to economic growth, they have received a great deal of criticism for their poor performance. Most of the challenges confronting these agro-enterprises, however, are the result of poor financial management practices. Previous research studies have indicated generally that financial management practices have an impact on the performance and success for small businesses, yet scholarly research shows there is limited empirical evidence on which financial management practices have an influence on the agri-SMEs performance, which is why it was critical to examine this phenomenon. A total of 427 SMEs in Tanzania's agricultural sector were surveyed and examined. The developed hypotheses were evaluated using Structural Equation Modeling (SEM) with Smart PLS 4 to determine the effect of implementing financial management practices on the performance of agri-SME. Findings from the empirical study shows that working capital management practices and financing management practices have significant positive influence on both financial and organizational performance of the surveyed agro enterprises, while the accounting, financial reporting practices and capital budgeting management practices have insignificant influence on the performance agri-SMEs performance. Based on the findings, the study recommends that the government and regulatory authorities such as the Small Industries Development Organization (SIDO) must continue to emphasize their policies for improved agri-SME performance and sustainability while directly or indirectly encourage managers (venture owners) to consider working capital and financing practices as core to their financial management strategies.
History of scholarship and learning. The humanities, Social sciences (General)
Space Very Long Baseline Interferometry is a radio astronomy technique distinguished by a record-high angular resolution reaching single-digit microseconds of arc. The paper provides a brief account of the history of developments of this technique over the period 1960s-2020s.
Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream. The problem of minimizing the cost associated with collecting labeled observations has gained a lot of attention in recent years, particularly in real-world applications where data is only available in an unlabeled form. Annotating each observation can be time-consuming and costly, making it difficult to obtain large amounts of labeled data. To overcome this issue, many active learning strategies have been proposed in the last decades, aiming to select the most informative observations for labeling in order to improve the performance of machine learning models. These approaches can be broadly divided into two categories: static pool-based and stream-based active learning. Pool-based active learning involves selecting a subset of observations from a closed pool of unlabeled data, and it has been the focus of many surveys and literature reviews. However, the growing availability of data streams has led to an increase in the number of approaches that focus on online active learning, which involves continuously selecting and labeling observations as they arrive in a stream. This work aims to provide an overview of the most recently proposed approaches for selecting the most informative observations from data streams in real time. We review the various techniques that have been proposed and discuss their strengths and limitations, as well as the challenges and opportunities that exist in this area of research.
Architectural education in India is largely envisioned as a technical-vocational course, leading to humanities-related courses like history, to remain alienated from students as well as practitioners. History of Architecture is a core subject in Bachelor of Architecture as per regulatory guidelines, but the program level outcomes are often limited to stylistic study of standard sets of examples of monumental structures from the past. This trend can be traced back to the colonial episteme started during the British programme of instruction and is ingrained in the educational system. This study enquires into the current state of history education at the undergraduate level in architectural schools in India and examines the continuing impact of colonisation on our production of knowledge. This is done by analysing the content of the architectural history curricula of colleges in India and discussions with academic practitioners who have been teaching the subject in those institutions. Unpacking the curricula and their influences on teaching, brought out the perpetuation of colonial biases embedded in architectural history education. The study argues that a well-designed history curriculum has the potential to contextualise design education and create critically aware architects, and thus take a step towards decolonising the practice itself.
Beatriz Garcia-Ortega, Javier Galan-Cubillo, Blanca de-Miguel-Molina
This paper assesses whether and to which extent the COVID-19 pandemic, which represents a scenario of high moral intensity, is influencing the moral reasoning of top CEOs (chief executive officers) in the paradigmatic case of the automotive industry and how this moral reasoning relates to their CSR response to the crisis and their CSR plans in the long run. To this end, we took the CEO letters before and after the pandemic outbreak of the top 15 automotive companies, and applied Weber’s method to conduct a moral reasoning categorization, along with an examination of their CSR approach and initiatives. The results show a predominant moral paralysis among these CEOs, where positive reactions addressed are philanthropic in nature and more likely to be a transient response to the crisis, rather than a sustained long-term improvement of their CSR rooted in a significant moral approach enhancement. Furthermore, CEOs at the lowest stages of moral reasoning, primarily focused on their own business and immediate stakeholders, are less likely to highlight these philanthropic initiatives. The outcome evidences the convenience of addressing CSR from the lens of moral reasoning, and it further draws the attention of the scientific community, companies and their top management, stakeholders, and society to the relevance of investigating and considering the moral reasoning of top management in large corporations and its implications.
History of scholarship and learning. The humanities, Social Sciences
ركز البحث على الدوافع والاسباب المؤدية الى السقوط من خلال حقل فلسفة التاريخ متعرضا الى أراء اهم فلاسفة التاريخ . ابتدأ البحث بتعريف فلسفة التاريخ وعلاقتها بعلم التاريخ واهدافها العامة . ثم تطرق الى نظريات فلسفة التاريخ التي صبت جهدها لمعرفة القوانين او السنن المتحكمة في حركة التاريخ والعوامل التي تنقل المجتمع من مرحلة الى اخرى . الشق الاخر من البحث هو التفسير الاسلامي لحركة التاريخ واسباب سقوط الدول ابتداء من القران الكريم مرورا بفلسفة الامام علي ()التي كانت اكثر دقة وتفصيلا لعوامل النهوض وملامح الانهيار التي اسماها ( مصارع القرون ) ثم تناول البحث اراء المفكرين المسلمين الذين سبقوا ابن خلدون في هذا الباب .
History of scholarship and learning. The humanities, Arts in general
Lun Ai, Johannes Langer, Stephen H. Muggleton
et al.
The topic of comprehensibility of machine-learned theories has recently drawn increasing attention. Inductive Logic Programming (ILP) uses logic programming to derive logic theories from small data based on abduction and induction techniques. Learned theories are represented in the form of rules as declarative descriptions of obtained knowledge. In earlier work, the authors provided the first evidence of a measurable increase in human comprehension based on machine-learned logic rules for simple classification tasks. In a later study, it was found that the presentation of machine-learned explanations to humans can produce both beneficial and harmful effects in the context of game learning. We continue our investigation of comprehensibility by examining the effects of the ordering of concept presentations on human comprehension. In this work, we examine the explanatory effects of curriculum order and the presence of machine-learned explanations for sequential problem-solving. We show that 1) there exist tasks A and B such that learning A before B has a better human comprehension with respect to learning B before A and 2) there exist tasks A and B such that the presence of explanations when learning A contributes to improved human comprehension when subsequently learning B. We propose a framework for the effects of sequential teaching on comprehension based on an existing definition of comprehensibility and provide evidence for support from data collected in human trials. Empirical results show that sequential teaching of concepts with increasing complexity a) has a beneficial effect on human comprehension and b) leads to human re-discovery of divide-and-conquer problem-solving strategies, and c) studying machine-learned explanations allows adaptations of human problem-solving strategy with better performance.
Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai
et al.
Transfer learning is crucial in training deep neural networks on new target tasks. Current transfer learning methods always assume at least one of (i) source and target task label spaces overlap, (ii) source datasets are available, and (iii) target network architectures are consistent with source ones. However, holding these assumptions is difficult in practical settings because the target task rarely has the same labels as the source task, the source dataset access is restricted due to storage costs and privacy, and the target architecture is often specialized to each task. To transfer source knowledge without these assumptions, we propose a transfer learning method that uses deep generative models and is composed of the following two stages: pseudo pre-training (PP) and pseudo semi-supervised learning (P-SSL). PP trains a target architecture with an artificial dataset synthesized by using conditional source generative models. P-SSL applies SSL algorithms to labeled target data and unlabeled pseudo samples, which are generated by cascading the source classifier and generative models to condition them with target samples. Our experimental results indicate that our method can outperform the baselines of scratch training and knowledge distillation.
Gurpreet Singh, S. Al’Aref, Benjamin C. Lee
et al.
Conventional scoring and identification methods for coronary artery calcium (CAC) and aortic calcium (AC) result in information loss from the original image and can be time-consuming. In this study, we sought to demonstrate an end-to-end deep learning model as an alternative to the conventional methods. Scans of 377 patients with no history of coronary artery disease (CAD) were obtained and annotated. A deep learning model was trained, tested and validated in a 60:20:20 split. Within the cohort, mean age was 64.2 ± 9.8 years, and 33% were female. Left anterior descending, right coronary artery, left circumflex, triple vessel, and aortic calcifications were present in 74.87%, 55.82%, 57.41%, 46.03%, and 85.41% of patients respectively. An overall Dice score of 0.952 (interquartile range 0.921, 0.981) was achieved. Stratified by subgroups, there was no difference between male (0.948, interquartile range 0.920, 0.981) and female (0.965, interquartile range 0.933, 0.980) patients (p = 0.350), or, between age <65 (0.950, interquartile range 0.913, 0.981) and age ≥65 (0.957, interquartile range 0.930, 0.9778) (p = 0.742). There was good correlation and agreement for CAC prediction (rho = 0.876, p < 0.001), with a mean difference of 11.2% (p = 0.100). AC correlated well (rho = 0.947, p < 0.001), with a mean difference of 9% (p = 0.070). Automated segmentation took approximately 4 s per patient. Taken together, the deep-end learning model was able to robustly identify vessel-specific CAC and AC with high accuracy, and predict Agatston scores that correlated well with manual annotation, facilitating application into areas of research and clinical importance.
Abstract The article explores issues of narrative time and space. It embraces a conception of geography, of space, as place involving relations among people, with ‘their own stories to tell’. And as story, as narrative, geography can be captured by a ‘story grammar’: Who, What, When, Where, Why, and How (the 5 Ws + H). When and Where, time and space, are the fundamental axes of narrative, different cultures differently grounding narrative in time (the ‘once upon a time’ of Western culture) or in space (the Western Apaches of Arizona). The article explores the ways in which new computational tools allow us to understand and represent actors and their actions in the setting of time and space, ways for geography to meet history, via linguistics. The article illustrates the geographical and historical implications of the approach by focusing on lynching narratives from hundreds of newspaper articles (Georgia, 1875–1930).