Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Joint Local-Global Iris Representations via Spatial Calibration for Generalized Presentation Attack Detection

—Existing Iris Presentation Attack Detection (IPAD) systems do not generalize well across datasets, sensors and subjects. The main reason for the same is the presence of similarities in bonafide samples and attacks, and intricate iris textures. The proposed DFCANet (Dense Feature Calibration Attention-Assisted Network) uses feature calibration convolution and residual learning to generate domain-specific iris feature representations at local and global scales. DFCANet’s channel attention enables the use of discriminative feature learning across channels. Compared to state-of-the-art methods, DF-CANet achieves significant performance gains for the IIITD-CLI, IIITD-WVU, IIIT-CSD, Clarkson-15, Clarkson-17, NDCLD-13, and NDCLD-15 benchmark datasets. Incremental learning in DFCANet overcomes data scarcity issues and cross-domain challenges. This paper also pursues the challenging soft-lens attack scenarios. An additional study conducted over contact lens detection task suggests high domain-specific feature modeling capacities of the proposed network.
A Giant Left Ventricular Pseudoaneurysm in Behçet¿s Disease

Behçet’s disease is a systemic illness characterised by orogenital ulcers and uveitis that can affect the articular, gastrointestinal, cardiovascular, and neurological systems. We present the case of a 23 year-old North African male without cardiovascular risk factors, who arrived at the emergency room with chest pain that had been developing for 15 days. The chest pain was made more acute when taking deep breaths. The patient also experienced dysthermia and was shivering. Physical examination revealed a fever of 38.5C, orogenital ulcers, pansystolic murmur upon cardiac auscultation, and an apical beat displaced upwards and to the left. The ECG registered sinus rhythm with Q waves in the precordial derivations. Concentrations of troponin I (5.5 ng/dL) and C-reactive protein (15.4 mg/dL) were high, and so was the globular sedimentation velocity (108 mm/s). The chest x-ray showed a left paracardiac mass that obscured the cardiac silhouette. The transthoracic echocardiography showed a pseudoaneurysm of massive dimensions (59×86 mm) on the anterolateral wall of the left ventricle, with a thin neck (2.5×3 mm) (Figure 1) The contrast echocardiography showed that there was flow between the left ventricle and the pseudoaneurysm (Figure 2), which eliminated the possibility of thrombi in the interior. The rest of the examination was normal. The coronariography showed epicardial arteries of normal size and only the second diagonal artery, a branch of the anterior descending artery, was occluded. The patient underwent operation to remove the pseudoaneurysm, and there were no complications in the post-operatory period. The anatomopathologic study showed abundant fibrous tissue with areas of acute and chronic inflammation, with an abundance of neutrophils and thrombotic areas. To study the febrile syndrome, a thoraco-abdominal computerised tomography was taken that clearly showed thrombosis of the hepatic portal vein. Blood, urine, and faeces tests, and those from the extirpated mass, were negative. The co-existence of orogenital ulcers and the extensive cardiovascular damage, together with the high concentration of acute phase reactants led to the diagnosis of Behçet’s disease. Behçet’s disease is a vascular illness that affects the skin, mucous membranes, articulations, and the cardiovascular, neurological, and gastrointestinal systems. Cardiovascular conditions in particular have been described in 7%-46% of all patients. It generally affects young patients and includes coronary and valvular heart disease, myocarditis, and pericarditis, and the formation of intracavity thrombi. Ventricular pseudoaneurysms in Behçet’s disease are exceptional and they appear most frequently after an acute myocardial infarction. In this instance, the coronariography showed total occlusion of a diagonal branch of the descending anterior artery. The anterolateral position of the pseudoaneurysm could be related to the thrombosis of the mentioned coronary artery and the resulting infarction of the anterolateral ventricular wall. Unlike other
ExplainerX: An Integrated and Explainable AI Framework for Nearly Zero-Energy Buildings

Climate change is a pressing global issue primarily driven by excessive energy consumption, with the building sector being a major contributor. In response to this challenge, Nearly Zero-Energy Buildings (NZEBs) have emerged as a promising solution. These buildings are designed to generate as much energy as they consume by leveraging energy-efficient technologies and renewable energy sources. However, achieving the NZEB goal relies on accurately predicting a building’s future energy usage. This precision is crucial for efficiently managing energy production, consumption, storage, and distribution within NZEBs. The current Artificial Intelligence (AI) solutions face significant shortcomings that extend beyond mere performance issues. These include critical aspects such as the lack of transparency in gathered data and predicted results, oversight in identifying model drift (especially in fast-paced sectors like energy), and the use of disparate tools in the model development process. This paper addresses these issues when developing AI solutions for NZEB projects by introducing ExplainerX, an integrated and explainable framework that streamlines all stages of building transparent and high-performance prediction models. ExplainerX ensures transparency in both data and results, accounts for data changes in dynamic settings, and promotes effective energy management in buildings. It leverages different components of the CRISP-DM methodology, providing explanations for each pipeline and tracing every decision made by data scientists and decision-makers. The framework is illustrated through a case study utilizing real datasets from the EU Improvement Project. ExplainerX source code is available on our GitHub repository.
Peran Profitabilitas dalam Memoderasi Kinerja Lingkungan, Islamic Social Reporting dan Ukuran Dewan Komisaris Terhadap Nilai Perusahaan

Tujuan dari dilakukan penelitian ini adalah untuk mengetahui faktor-faktor yang dapat memengaruhi nilai perusahaan dengan dilakukan pengujian interaksi menggunakan profitabilitas. Populasi dalam penelitian ini yaitu seluruh perusahaan yang masuk daftar Jakarta Islamic Indeks selama kurun waktu 2017-2021 yang berjumlah 53 perusahaan. Perolehan sampel dilakukan dengan teknik purposive sampling dan diperoleh 8 perusahaan. Penelitian ini menggunakan pendekatan kuantitatif dengan data sekunder dan analisis data dibantu dengan sofware eviews-12. Hasil yang diperoleh dari penelitian ini yaitu kinerja lingkungan dan Islamic Social Reporting (ISR) tidak berdampak pada nilai perusahaan, sedangkan ukuran dewan komisaris berdampak negatif signifikan pada nilai perusahaan. Profitabilitas tidak mampu memoderasi kinerja lingkungan terhadap nilai perusahaan, namun memperlemah pengaruh dari Islamic Social Reporting (ISR) dan ukuran dewan komisaris terhadap nilai perusahaan. Penelitian ini memiliki keterbatasan pada rasio profitabilitas yang hanya diukur dengan Return On Equity (ROE) serta hanya menggunakan 8 perusahaan sebagai sampel penelitian yang sesuai dengan kriteria penelitian.
LOS BARRIOS ARTÍSTICOS COMO BASE LOCAL DE LA CULTURA GLOBAL El caso del Raval de Barcelona ARTISTIC NEIGHBORHOODS AS LOCAL BASE OF GLOBAL CULTURE Analysis of the case of the Raval in Barcelona

Artistic neighborhoods, one of the urban phenomenons most characteristic of the beginning century, are beoming an important object of study in the social sciences. However the analysis is overly centered on their economic impact or the cultural policies that have contributed to their creation. In this article, we propose to center the study of artistic neighborhoods in the urban, social and artistic dynamics that explain their emergence and rationale for their development. In this respect, we suggest that in a typical-ideal sense an artistic neighborhood posseses a historical-symbolic heritage, a concentration of creators and intermediaries, represents an emerging pole within world culture and generates a label for its artistic style. Finally, cultural policy performs an initiating and catalzying role. We use the case of the Raval neighborhood in Barcelona to exemplify this analysis. In this sense, we show how the Raval is symbollicaly charged, having an important presence of artists and small cultural businesses, makes up the core of emerging,hybrid and multicultural art in Barcelona and in addition counts on the presence of two cultural institutions oriented towards cultural governance. From these conditions we see the generation of an artistic dynamic that is unique and local which at the same time synthesizes a characteristic artistic style which is very exportable in the global cultural market.
What Disrupts Flow in Office Work? The Impact of Frequency and Relevance of IT-Mediated Interruptions

Flow, the holistic sensation people experience when they act with total involvement, is a known driver for desired work outcomes like task performance. However, the increasing ubiquity of IT at work can disrupt employees’ flow. Thus, the impact of IT-mediated interruptions on flow warrants more attention in research and practice. We conducted a NeuroIS laboratory experiment focusing on a typical office work task—an invoice matching task (i.e., matching customer payments to invoices). We manipulated interruption frequency (low, high) and content relevance (irrelevant, relevant) to study the impact of interruptions on self-reported flow, its dimensions, and high-frequency heart rate variability (HF-HRV; calculated from electrocardiography recordings) as a proxy for parasympathetic nervous system (PNS) activation. We found that content relevance moderated the relationship between interruption frequency and self-reported flow and that these results vary along flow dimensions. Content relevance also moderated the relationship between interruption frequency and PNS activation. Furthermore, self-reported flow was positively associated with both perceived and objective task performance, while PNS activation was not related to either performance measure. Lastly, we found no relationship between PNS activation (measured by HF-HRV) and self-reported flow, contributing to an important debate in the NeuroIS literature on whether physiological evidence constitutes an alternative or a complement to self-reports. Overall, our findings indicate that frequent interruptions are not harmful per se. Rather, considering content relevance is critical for a more comprehensive understanding of the effects on self-reported flow, its dimensions, and the underlying physiology.
Influence of food packaging color and foods type on consumer purchase intention: the mediating role of perceived fluency

Packaging color entices and influences consumer perceptions and significantly affects the identification of products. Marketers manipulate the exterior packaging to influence consumer expectations, experiences, and behaviors. Building upon psychological literature on colors and emotions, we explored the influence of food packaging color and food type on consumers’ purchase intentions. Study 1 explored the interaction effects between food packaging color (warm vs. cold) and food type (vice foods vs. virtue foods) on consumers’ purchase intentions. Study 2 examined whether perceived fluency mediates the interaction effect of food packaging color and food type on consumers’ purchase intentions. The results showed that for vice foods, characterized by tastiness but unhealthiness, the utilization of warm-colored food packaging enhances consumer purchase intent. In contrast, for virtue foods that are healthful but lack gustatory appeal, the use of cold food packaging colors will lead to higher consumer purchase intent. Perceived fluency mediates the interaction effect of food packaging color and food type on consumers’ purchase intentions. This study will assist marketers to exploring a range of possibilities for packing color, impacting both the physiological and cognitive dimensions of consumer behavior related to food products, and offering practical implications for market managers.
Outage-Constrained Energy-Efficient Resource Allocation for IRS-Assisted Secure Communications

In this paper, we investigate the resource allocation problem of a downlink system from a multi-antenna base station (BS) to multiple single-antenna legitimate users, where an intelligent reflecting surface (IRS) is employed to guarantee the physical layer security from multiple single-antenna eavesdroppers. Considering the passive characteristic of eavesdroppers, only statistic channel state information (CSI) can be obtained for all channels related to eavesdroppers and artificial noise (AN) is applied to handle this challenging issue. Aiming to maximize the secrecy energy efficiency (SEE), we jointly optimize the beamformers and AN at the BS and phase shifts at the IRS subject to secrecy outage probability (SOP) constraints. To tackle the non-convexity of the formulated problem, an alternating optimization (AO) scheme based on Dinkelbach's algorithm and successive convex approximation (SCA) approach is proposed. Simulation results verify the convergence of the proposed scheme and demonstrate that both IRS and AN can significantly improve the SEE. Meanwhile, it is illustrated that with sufficient transmit power budget, the AN-assisted scheme even outperforms the IRS-assisted scheme.
Exploring content-based group recommendation for suggesting restaurants in Havana City

Recommender systems (RSs) are a relevant kind of artificial intelligence-based systems focused on providing users with the information that best fit their preferences and needs in a search space overloaded of possible options. Specifically, group recommender systems (GRSs) are a special type of RS centered on recommending items that are consumed in groups and not individually, being TV program and touristic packages key examples of such items. The current work is focused on proposing a content-based group recommendation approach (CB-GRS) contextualized to the restaurant recommendation domain. In contrast to previous content-based group recommendation models, the proposal incorporates novel stages such as restaurants feature imputation, the generation of a virtual group profile, the use of feature weighting, and the automatic selection of the most appropriate aggregation approach for composing group recommendations. The proposal is evaluated in an original recommendation scenario, related to restaurant from Havana City in Cuba, where several restaurant attributes are identified for applying the proposed CB-GRS approach. The experimental protocol evaluates individually each component of the proposal, evidencing their importance as part of the whole framework. Furthermore, the comparison with previous works has been also developed. The proposed approach can be applied in other recommendation scenarios, and in addition, the developed experimental protocol is generalizable for the evaluation of further content-based individual and group recommendation approaches in the tourism domain.
Can social media play a role in developing building occupancy curves for small area estimation

As small area population estimation continues to advance toward increasingly finer spatial scales, population modelers are ultimately confronted with understanding the occupancy of actual buildings and facility spaces. The need for characterizing building occupancy intersects a number of other related disciplines including green building technologies, natural hazards risk analytics, and public safety occupancy standards. While much has been gained in using survey diaries, sensor technologies, and downscaling data fusion techniques, there is a growing interest in the use of social media data to further illuminate building use patterns. This paper initiates a research agenda in this domain by proposing an explicit social media model that assists in delineating and articulating the opportunities, challenges, and limitations of using social media in the specific case of building use dynamics.
SUPERIOR TASTE AND KEEPING QUALITY ARE STEADY GOALS OF THE PEACH BREEDING ACTIVITY AT CRA-FRF, ITALY

Mature peaches and nectarines have a short life on tree and after harvest. Due to the rapid loss of firmness, melting peaches and nectarines are often picked at a premature physiological stage, especially when they are intended for distant markets, to the detriment of the quality at consumption. In the most important peach-growing countries in Europe, the excessive early harvest has caused the loss of considerable market share. Releasing new cultivars which, together with the good and broad environmental adaptability, are featured with fruit having superior taste and long keeping quality on tree and at post-harvest has been a steady goal of the CRA-FRF (Italy) peach breeding program since its start, in 1980. Significant improvement of the fruit keeping quality was obtained by introducing, through controlled crosses, the non-melting, the slow softening and the stony-hard traits into fresh market peaches. The stony-hard fruit, in particular, keeps a very firm and crispy texture for weeks on the tree, well beyond the physiological ripening. Improvement in taste was obtained by selecting for the high sugar content, either combining it with the low acidity trait, monogenic and dominant, or discarding genotypes characterized by excessive acidity. Good taste was also associated with other novel traits such as the flat shape, the red flesh or the complete lack of red pigmentation. Morphological and qualitative description of the most advanced CRA-FRF breeding selections are provided.
Mutual Information Based Image Registration for Medical Imaging

Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. Image registration geometrically aligns two images (the reference and test images). This thesis discusses about the medical image registration by using correlation with mutual information. It also mentions about the problematic issue that arises during the feature matching stage in the mutual information based medical image registration. The matched results shows that by changing (can be decreasing or increasing depending on the image) the windows size of the image more matched points can be obtained. This thesis also focuses on registration of two images which are rotationally misaligned and gives the procedure to measure this angle of rotation using mutual information. Typically,registration application are in remote sensing, image mosaicing, weather forecasting, super-resolution image creation, in medicine (computerized tomography (CT) and magnetic resonance image (MRI) combining in order to obtain more complete information about the patient, monitoring tumor growth etc. This thesis describes image mosaicing by using mutual information.Here image mosaicing has been discussed for both medical and satellite images. The thesis concludes with results obtained by applying above mentioned techniques and also provides with the possible changes that could be made in future for obtaining better results.
Increase Merge Efficiency in LSM Trees Through Coordinated Partitioning of Sorted Runs

The performance of an LSM-tree-based system heavily relies on the compaction strategy employed. Two main categories of compaction strategies exist: leveled and stack-based. Leveled compaction offers several advantages. Firstly, its incremental merge style enables breaking down large compactions into smaller sub-compactions through partitioning. This partitioning enhances parallelism during compaction execution, reduces write stalling, and improves disk utilization. Additionally, for specific workloads like sequential insertions, it allows moving entire files to lower levels without the need for rewriting them, thus saving disk I/O. These moves are known as trivial-moves. On the other hand, stack-based policies typically lack support for these desired properties. Their large compactions either perform no partitioning or rely on naive partitioning methods, resulting in limited opportunities for parallelism and trivial-moves.The goal of this paper is to facilitate the compaction advantages of leveled strategies in stack-based systems, hence creating a hybrid strategy that combines the advantages of both worlds. To achieve this, we propose two novel coordinated partitioning algorithms, namely Local-Range and Global-Range. These algorithms can be applied to any stack-based compaction strategy to enhance parallelism during compactions and create more opportunities for trivial-moves, resulting in improved overall compaction cost. We extend RocksDB to support partitioning on stack-based strategies and conduct a comparative analysis against several baselines using various workloads. The experimental results demonstrate that the Global-Range partitioning method significantly enhances compaction performance with minimal overhead.
Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa

The bioeconomy offers an opportunity to implement a truly sustainable global economy based on biological resources, which, thanks to biotechnologies, become renewable. In this study, we conducted a bioeconomic analysis of the three most important species of sea snook in northern Sinaloa using fishery and mathematical models to support the selection of the species with the highest growth and feasibility. Our results showed a condition factor lower than 1 (K < 1) for the three species. The size condition factor was higher in younger organisms for the three snook species. The growth rates were K = 0.320, K = 0.160, and K = 0.440 for C. viridis, C. nigrescens, and C. medius, respectively. Individual growth was 1.8 g/day for C. viridis, 1.47 g/day for C. nigrescens, and 0.91 g/day for C. medius. The length-to-weight ratio indicated negative allometric growth (b = 2.82, b = 2.72, and b = 2.73, respectively) for C. viridis, C. nigrescens, and C. medius. The simulation for possible commercial cultivation reflected varied sizes: 600 g for C. viridis and C. nigrescens and 400 g for C. medius. The financial projection of C. viridis produced IRRs of 14% and 48% in captured fishing and aquaculture models, respectively, with positive NPV. However, simulations for C. nigrescens and C. medius were not economically viable. We conclude that, according to the aquaculture model, the most financially feasible species to farm in the north of Sinaloa is C. viridis, which showed the highest growth based on fishery data compared to those for C. nigrescens and C. medius.