Abstract This article examines the history of the Value Added Tax (VAT) and its implementation in the agricultural sector in Albania. Although VAT has been applied in Albania since 1996, it has undergone several legal changes over time with respect to tax rates and application within this sector. Recent changes in VAT rates have affected the prices and costs of agricultural inputs, as well as the determination of market selling prices for agricultural products. Given the significant role of agriculture in the Albanian economy, this article aims to analyze VAT rates, along with the VAT compensation and crediting schemes applied across the main agricultural branches. It also identifies the challenges encountered throughout the agricultural supply chain. Additionally, the article highlights selected practices used by European Union (EU) countries in the application of VAT in agriculture.
Kroatologija se razvila kao zasebno interdisciplinarno akademsko područje, formalno priznato unutar hrvatskoga znanstvenog okvira 2009. godine. Ova studija ispituje povijesni razvoj kroatologije, s posebnim naglaskom na njezinu evoluciju pod utjecajem ključnih kulturnih, povijesnih i političkih čimbenika od 19. stoljeća nadalje. Kritički se analiziraju metodološki pristupi koji su središnji za kroatološka istraživanja, poput jezikoslovnih, književnih i kulturoloških studija, te se razmatra njihova integracija u suvremeni akademski diskurs. Nadalje, rad istražuje percepciju kroatologije u javnosti i njezinu distinkciju od srodnih područja, poput kroatistike, pri čemu se naglašavaju aktualne rasprave o njezinoj znanstvenoj i društvenoj relevantnosti. Institucionalni napredci, uključujući uspostavu preddiplomskih, diplomskih i doktorskih programa, znatno su pridonijeli akademskoj vjerodostojnosti kroatologije. Ipak, ostaju izazovi u učvršćivanju njezina identiteta i rješavanju pitanja profesionalnih prilika za njezine diplomante. Ovo istraživanje naglašava nužnost usavršavanja metodoloških okvira i poticanja interdisciplinarne suradnje kako bi se dodatno povećao utjecaj ovoga područja na razumijevanje hrvatskoga nacionalnog identiteta i kulture.
Autoregressive video generation relies on history context for content consistency and storytelling. As video histories grow longer, efficiently encoding them remains an open problem - particularly for personal users and local workflows where compute and memory budgets are limited. We present a lightweight history encoder that maps long video histories into short-length embeddings, pretrained with a frame query objective that learns to attend to content features at arbitrary temporal positions. The pretraining stage provides the encoder with dense history coverage on large-scale video data; the subsequent finetuning stage adapts the pretrained encoder under an autoregressive video generation objective to establish content-level consistency. In this way, the lightweight embeddings achieve comparable performance to heavier alternatives. We evaluate the framework with ablative settings and discuss the architecture designs.
In the last few decades, the European Union (EU) has developed a comprehensive approach to natural
disaster management, with a particular focus on civil protection laws and international cooperation. The EU
acknowledges the importance of proactive measures to minimize the impact of potential crises, namely in the
context of climate change, in response of the increasing complexity and frequency of climate-induced disasters.
This study analyses and discusses EU humanitarian legislation that aims to promote disaster resilience in
member states. It starts with an overview of the EU’s legal framework, continuing with an analysis of the different
types of secondary legislation in the Union, distinguishing their purposes and respective attributes, and then
delves into the already established bases for preventing and mitigating the impacts of natural disasters and the
frequency of such risks. Finally, a critical reflection is made on the strengths and limitations of the legal basis
established by the EU.
Social sciences (General), Social history and conditions. Social problems. Social reform
Mohammed Tayeeb Hasan, Nikolaos Tsantalis, Pouria Alikhanifard
Tracking statements in the commit history of a project is in many cases useful for supporting various software maintenance, comprehension, and evolution tasks. A high level of accuracy can facilitate the adoption of code tracking tools by developers and researchers. To this end, we propose CodeTracker, a refactoring-aware tool that can generate the commit change history for code blocks. To evaluate its accuracy, we created an oracle with the change history of 1,280 code blocks found within 200 methods from 20 popular open-source project repositories. Moreover, we created a baseline based on the current state-of-the-art Abstract Syntax Tree diff tool, namely GumTree 3.0, in order to compare the accuracy and execution time. Our experiments have shown that CodeTracker has a considerably higher precision/recall and faster execution time than the GumTree-based baseline, and can extract the complete change history of a code block with a precision and recall of 99.5% within 3.6 seconds on average.
Se-eun Yoon, Ahmad Bin Rabiah, Zaid Alibadi
et al.
Customers reach out to online live chat agents with various intents, such as asking about product details or requesting a return. In this paper, we propose the problem of predicting user intent from browsing history and address it through a two-stage approach. The first stage classifies a user's browsing history into high-level intent categories. Here, we represent each browsing history as a text sequence of page attributes and use the ground-truth class labels to fine-tune pretrained Transformers. The second stage provides a large language model (LLM) with the browsing history and predicted intent class to generate fine-grained intents. For automatic evaluation, we use a separate LLM to judge the similarity between generated and ground-truth intents, which closely aligns with human judgments. Our two-stage approach yields significant performance gains compared to generating intents without the classification stage.
The mass assembly history (MAH) of dark matter halos plays a crucial role in shaping the formation and evolution of galaxies. MAHs are used extensively in semi-analytic and empirical models of galaxy formation, yet current analytic methods to generate them are inaccurate and unable to capture their relationship with the halo internal structure and large-scale environment. This paper introduces FLORAH, a machine-learning framework for generating assembly histories of ensembles of dark matter halos. We train FLORAH on the assembly histories from the GUREFT and VSMDPL N-body simulations and demonstrate its ability to recover key properties such as the time evolution of mass and concentration. We obtain similar results for the galaxy stellar mass versus halo mass relation and its residuals when we run the Santa Cruz semi-analytic model on FLORAH-generated assembly histories and halo formation histories extracted from an N-body simulation. We further show that FLORAH also reproduces the dependence of clustering on properties other than mass (assembly bias), which is not captured by other analytic methods. By combining multiple networks trained on a suite of simulations with different redshift ranges and mass resolutions, we are able to construct accurate main progenitor branches (MPBs) with a wide dynamic mass range from $z=0$ up to an ultra-high redshift $z \approx 20$, currently far beyond that of a single N-body simulation. FLORAH is the first step towards a machine learning-based framework for planting full merger trees; this will enable the exploration of different galaxy formation scenarios with great computational efficiency at unprecedented accuracy.
İslam Medeniyeti, bu dini kabul etmiş milletlerin, İslam’ın etkisi altında kalarak meydana getirdikleri medeniyetin ortak tanımıdır. Bu kavram, Müslümanlığı kabul etmiş milletlerin tarihinde ayrı ayrı incelenemeyeceği gibi başlı başına tek bir medeniyet olarak da incelenemez. Çünkü, bir İslam dini vardır, fakat bağımsız bir İslam medeniyeti yoktur. Bu da İslamın bir milletin dini olmaması, bütün insanlığa göğüs açan bir din olmasındandır. Bu sebeple İslam medeniyeti demek, Arap - Türk - İran medeniyetleri demektir. Bilimde, şiirde, edebiyatta, mimarlıkta durum böyledir. Yalnız hukukta, İslam medeniyeti, kendine has bir özellik taşımaktadır. Askerlik ve yönetim düzeninde ise, Türklerin etkisi çok büyüktür. İslam medeniyetinin hukuki açıdan, bu medeniyetin en önemli yönünü meydana getirmektedir. Mutlak bir kardeşlik esasına dayanan İslamiyet, Müslümanlar arasındaki zümre farkını kaldırarak, ahlaki yönden yeni ve sağlam esaslar getirmektedir. Nitekim, bu nedenle bile, İslamiyet, bir ahlak medeniyeti olarak da tanımlanabilir.
İslam medeniyeti içinde bulunan topluluklara ve devlet düzenine yeni kurallar getirerek, her sanat ve yönetim şekli, bu medeniyetin içinde genelleşmiş ve toplu olarak İslam medeniyetini ifade eder olmuştur. Bu arada çeşitli sanat kollarında ilerlemeler olmuş resim ve heykeltıraşlığın İslamlıkta yasak olmasına ve hiç bir gelişme kazanamamasına karşılık, mimarlık alanında çok büyük ilerlemeler kazanılmıştır. İslam medeniyeti, bilim alanında da, Türk, Arap ve Acem bilim adamlarının aracılığı ile büyük gelişmeler kazanmış, Ortaçağ boyunca Avrupa ve Asya ülkelerinde iz bırakan bilim adamlarının yetişmesine yol açmıştır.
Rusça hazırladığımız bu ilmi araştırmanın nihai hedefi, İslam’ın, farklı medeniyetlere kattığı ilmi ve kültürel değerleri ortaya çıkarmaktır. Ayrıca, aynı zamanda bir ahlak medeniyeti olan İslam Medeniyetinin, tarihi gelişim sürecindeki faaliyetlere yönelik bilgileri, bütün Rusya coğrafyasında yaşayan halklara ulaştırmak ve aktarmaktır.
A proposição básica deste artigo é apresentar um estudo exploratório acerca dos movimentos educativos populares da década de 1960, especialmente a Campanha de Educação Popular que se desenvolveu na Paraíba entre 1961 e 1964, e as Ligas Camponesas. Objetiva-se, assim, realizar um mapeamento da produção acadêmica dos últimos dez anos (2006-2016) a partir de dois lócus epistêmicos: as reuniões da Associação Nacional de Pesquisa em Educação (Anped) e o Programa de Pós-Graduação em Educação da Universidade Federal da Paraíba-UFPB que possui desde a década de 1970 uma linha de Pesquisa sobre Educação Popular. A dimensão descritiva da produção acadêmica e científica sobre o tema nos possibilitou uma aproximação teórica e conceitual com o objeto de estudo, uma ordenação do conjunto de informações e resultados obtidos sobre a temática, evidenciando a necessidade de pesquisas que tratem sobre a relação entre estas duas práticas de Educação Popular desenvolvidas no Estado da Paraíba na década de 1960.
The first determination of the surface temperature of stars other than the Sun is due to the Hungarian astrophysicist Béla Harkányi. Prompted by the recent unprecedented increase in the availability of stellar temperature estimates from Gaia, coinciding with the 150th anniversary of Harkányi's birth, this article presents the life and work of this neglected, yet remarkable figure in the context of the history of stellar astrophysics.
This paper is a study of the history of the transplant of mathematical tools using negative feedback for macroeconomic stabilization policy from 1948 to 1975 and the subsequent break of the use of control for stabilization policy which occurred from 1975 to 1993. New-classical macroeconomists selected a subset of the tools of control that favored their support of rules against discretionary stabilization policy. The Lucas critique and Kydland and Prescott's time-inconsistency were over-statements that led to the "dark ages" of the prevalence of the stabilization-policy-ineffectiveness idea. These over-statements were later revised following the success of the Taylor rule.
The concentration parameter is a key characteristic of a dark matter halo that conveniently connects the halo's present-day structure with its assembly history. Using 'Dark Sky', a suite of cosmological $N$-body simulations, we investigate how halo concentration evolves with time and emerges from the mass assembly history. We also explore the origin of the scatter in the relation between concentration and assembly history. We show that the evolution of halo concentration has two primary modes: (1) smooth increase due to pseudo-evolution; and (2) intense responses to physical merger events. Merger events induce lasting and substantial changes in halo structures, and we observe a universal response in the concentration parameter. We argue that merger events are a major contributor to the uncertainty in halo concentration at fixed halo mass and formation time. In fact, even haloes that are typically classified as having quiescent formation histories experience multiple minor mergers. These minor mergers drive small deviations from pseudo-evolution, which cause fluctuations in the concentration parameters and result in effectively irreducible scatter in the relation between concentration and assembly history. Hence, caution should be taken when using present-day halo concentration parameter as a proxy for the halo assembly history, especially if the recent merger history is unknown.
The use of online user traces for studies of human mobility has received significant attention in recent years. This growing body of work, and the more general importance of human migration patterns to government and industry, motivates the need for a formalized approach to the computational modeling of human mobility - in particular how and when individuals change their place of residence - from online traces. Prior work on this topic has skirted the underlying computational modeling of residence inference, focusing on migration patterns themselves. As a result, to our knowledge, all prior work has employed heuristics to compute something like residence histories. Here, we formalize the residence assignment problem, which seeks, under constraints associated with the minimum length-of-stay at a residence, the most parsimonious sequence of residence periods and places that explains the movement history of an individual. Here we provide an exact solution for this problem and establish its algorithmic complexity. Because the calculation of optimal residence histories (under the assumptions of the model) is tractable, we believe that this method will be a valuable tool for future work on this topic.
We define a new selection problem, \emph{Selecting with History}, which extends the secretary problem to a setting with historical information. We propose a strategy for this problem and calculate its success probability in the limit of a large sequence.