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Speech Emotion Recognition (SER) is a rapidly evolving field of research aimed at identifying and categorizing emotional states through the analysis of speech signals. As SER holds significant socio-cultural and commercial importance, researchers are increasingly leveraging machine learning and deep learning techniques to drive advancements in this domain. A high-quality dataset is an essential resource for SER studies in any language. Despite Urdu being the 10th most spoken language globally, there is a significant lack of robust SER datasets, creating a research gap. Existing Urdu SER datasets are often limited by their small size, narrow emotional range, and repetitive content, reducing their applicability in real-world scenarios. To address this gap, the Urdu Speech Emotion Corpus (UrSEC) was developed. This comprehensive dataset includes 3500 Urdu speech signals sourced from 10 professional actors, with an equal representation of male and female speakers from diverse age groups. The dataset encompasses seven emotional states: Angry, Fear, Boredom, Disgust, Happy, Neutral, and Sad. The speech samples were curated from a wide collection of Pakistani Urdu drama serials and telefilms available on YouTube, ensuring diversity and natural delivery. Unlike conventional datasets, which rely on predefined dialogs recorded in controlled environments, UrSEC features unique and contextually varied utterances, making it more realistic and applicable for practical applications. To ensure balance and consistency, the dataset contains 500 samples per emotional class, with 50 samples contributed by each actor for each emotion. Additionally, an accompanying Excel file provides detailed metadata for each recording, including the file name, duration, format, sample rate, actor details, emotional state, and corresponding Urdu dialog. This metadata enables researchers to efficiently organize and utilize the dataset for their specific needs. The UrSEC dataset underwent rigorous validation, integrating expert evaluation and model-based validation to ensure its reliability, accuracy, and overall suitability for advancing research and development in Urdu Speech Emotion Recognition.

Supplementary files for “Modeling clinical radioiodine uptake by using organoids derived from differentiated thyroid cancer"

CAMP version used for the CPU-GPU measurements on MONARCH Marenostrum 5, including a small automatic load balance algorithm. Latest developments at https://github.com/open-atmos/camp

This metabolite dataset consists of untargeted metabolites collected at enrollment from 389 healthy first-degree relatives of Crohn's disease patients in the GEM project.

Two supplemental figures for the manuscript entitled "Superficial X-ray Therapy (SXRT) and CO2 Laser Manual Fractional Technology (MFT) Combination for Mandibular Keloids：A Case Series"

Endotoxemia is a significant cause of morbidity and mortality in equids [1,2] due to perfusion impairment and possible destruction of the glycocalyx [3]. In a prospective, randomized, controlled experimental trial, endotoxemia was induced with E. coli B55:O5 LPS 30 ng kg-1 over 30 minutes IV in six healthy adult horses ventilated with isoflurane in oxygen. Standard cardiovascular variables were recorded and calculated and leucocyte counts, lactate, heparan sulphate and syndecan-1, were determined at baseline (B) before endotoxin and at 0, 30, 60, 120 minutes after endotoxin. Data were analysed by a mixed model variance analysis and adjusted by Tukey-Kramer (SAS Enterprise Guide Software 7.1). After endotoxin (120 minutes), a significant increase (p ≤ 0.05) in cardiac index (43 ± 9 vs. 80 ± 15 ml kg-1 min-1, p < 0.01 ), in oxygen delivery index (8 ± 3 vs. 17 ± 4 ml min-1 kg-1, p <0.001), in pulse pressure variation (8 ± 3 vs. 17 ± 4, p < 0.01 and in lactate (1.55 ± 0,9 vs. 4.4 ± 0.52 mmol L-1, p < 0.0001) occurred with a decrease in systemic vascular resistance index (247 ± 87 vs. 83 ± 20 dynes s-1 cm-5, p <0.001), diastolic arterial blood pressure (69 ± 14 vs 38 ± 5 mmHg; p <0.001), and leukocyte counts (5.6 ± 1.3 vs. 1.5 ± 0.3 G l-1, p < 0.0001). No changes in the glycocalyx degradation products could be found. Short-term experimental endotoxemia under isoflurane induced anticipated cardiovascular changes, but did not alter glycocalyx shedding products in this study.

This data was generated from randomly selected square patches from the extents of a high-resolution Worldview3 satellite image (2023) for the Ashaiman district, Accra, Ghana. The patches were digitised by an expert in the fields of cartography, surveying, and GIS. This purpose of creating this dataset is to have a representative sample of patches, which was used for subsequent on-screen digitising of 2803 buildings polygons.

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We explored the effects of incorporating crop rotation on digital mapping of soil pH. Facing the challenge of quantifying the extent to which crop rotation affects soil pH mapping accuracy, we introduced the soil sample grouping strategy. We hypothesized that grouping soil samples by crop rotation could built optimized sub-models for different rotations and achieve a higher accuracy than simply incorporating crop rotation. To test this hypothesis, we selected a typical acidic soil region in Southern China where the agricultural landscape is highly heterogeneous due to intensive and diversified cropping systems. Specifically, the objectives of this study are (1) to explore the effectiveness of simply incorporating crop rotation in mapping soil pH and (2) to verify whether and to what extent the soil sample grouping strategy and separate modeling for different crop rotations could further improve digital mapping of soil pH.

This is the replication package for Banking Complexity in the Global Economy