Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

In this paper, we have developed the SEMAR (Smart Environmental Monitoring and Analytics in Real-Time) IoT application server platform for fast deployments of IoT application systems. It provides various integration capabilities for the collection, display, and analysis of sensor data on a single platform. Recently, Artificial Intelligence (AI) has become very popular and widely used in various applications including IoT. To support this growth, the integration of AI into SEMAR is essential to enhance its capabilities after identifying the current trends of applicable AI technologies in IoT applications. In this paper, we first provide a comprehensive review of IoT applications using AI techniques in the literature. They cover predictive analytics, image classification, object detection, text spotting, auditory perception, Natural Language Processing (NLP), and collaborative AI. Next, we identify the characteristics of each technique by considering the key parameters, such as software requirements, input/output (I/O) data types, processing methods, and computations. Third, we design the integration of AI techniques into SEMAR based on the findings. Finally, we discuss use cases of SEMAR for IoT applications with AI techniques. The implementation of the proposed design in SEMAR and its use to IoT applications will be in future works.
World Journal of Critical Care Medicine

BACKGROUND The increase in severe traumatic brain injury (sTBI) incidence is a worldwide phenomenon, resulting in a heavy disease burden in the public health systems, specifically in emerging countries. The shock index (SI) is a physiological parameter that indicates cardiovascular status and has been used as a tool to assess the presence and severity of shock, which is increased in sTBI. Considering the high mortality of sTBI, scrutinizing the predictive potential of SI and its variants is vital.
from a Literature Review in the Software Engineering Domain

Autistic individuals possess many unique skills that are beneﬁcial to the workforce, especially the technology industry. However, research shows the unemployment rate is still considerably high among the autistic population compared to their neurotypical peers. It has been suggested that some autistic individuals may excel in software engineering roles. This paper presents a Multi-vocal Literature Review (MLR) to highlight the cognitive style and talents of individuals with Autism Spectrum Disorder (ASD). An analysis is carried out to fully understand the challenges faced by autistic individuals transitioning into the workplace while also highlighting the challenges faced in their day to day working life. These challenges include workplace environments as well as workplace ceremonies, including, for example, daily stand-up meetings. Many neurotypical software engineers, software engineering ﬁrms and academics can beneﬁt from thisinformationastheyworktowardsamoreinclusiveandmoreeffectivesoftwareengineeringcommunity.
CHARACTERIZATION OF STOMATAL DENSITY AND SIZE OF DIFFERENT VITIS VINIFERA

The stomatal traits of 13 red and white grapevine cultivars of Vitis vinifera L. established in a cultivar collection garden in central Chile were characterized in this study. The cultivars examined were 'Cabernet Franc', 'Cabernet Sauvignon', 'Carmenere', 'Cot', 'Grenache', 'Merlot', 'Mourvedre', 'Pinot Noir', 'Syrah', 'Chardonnay', 'Marzanne', '
Discrete Shearlet Transform and Lempel-Ziv Welch Coding for Lossless Fingerprint Image Compression

: Image compression is a crucial task in image processing and in the process of sending and receiving files. There is a need for effective techniques for image compression as the raw images require large amounts of disk space to defect during transportation and storage operations. The most important objective of image compression is to decrease the redundancy of the image which helps in increasing the storage capacity and then efficient transmission. This study introduces a system for lossless image compression that is built to work on fingerprint image compression. It uses lossless compression to take care of the first image during processing. However, there is a serious problem which is the low ratio of compression. In order to make the ratio higher, there are five lossless compression techniques used in this study which are Elias Gamma Coding (EGC), Huffman Coding (HC), Arithmetic Coding (AC), Run-Length Encoding (RLE) and Lempel Ziv Welch (LZW). With these techniques, there are three types of transforms are used; they are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Discrete Shearlet Transform (DST). The results conclude that discrete shearlet transform with the Lempel-Ziv Welch coding technique outperforms the other lossless compression techniques and its Compression Ratio (CR) is 3.678023.
The recognition of emotions conveyed by emoticons and emojis: A systematic literature review.

The growing interest for emoticons and emojis has recently led to research examining their use and impact on various behaviors. As emoticonsandemojismayleadtomisinterpretationsandmisunderstandingsbetweensendersandrecipientsinonlinecommunication,itisnecessarytoexaminewhetheremotionsconveyedbythesesymbolsarewellrecognizedbyindividuals.Inthisperspective,a systematicreviewfrom2001to2021usingthePreferredReportingofItemsforSystematicreviewsandMeta-Analyses(PRISMA) method was conducted to determine which emoticons and emojis can help individuals to recognize emotions, and how the recognition of emotions based on emoticons and emojis is studied. A total of 501 articles were screened from three major databases in psychology, and 23 articles met the prede ﬁ ned inclusion criteria. The results suggest that the recognition of emotions should be examined before using emoticons in larger studies. They also revealed that the recognition varied according to the methods used to assess the valence of emoticons or to attribute a speci ﬁ c emotion to them (self-report, free expression, or categorization). Finally, a summary Table of the emotions conveyed by emoticons and emojis is proposed in this review.
E-MuLA: An Ensemble Multi-Localized Attention Feature Extraction Network for Viral Protein Subcellular Localization

Accurate prediction of subcellular localization of viral proteins is crucial for understanding their functions and developing effective antiviral drugs. However, this task poses a significant challenge, especially when relying on expensive and time-consuming classical biological experiments. In this study, we introduced a computational model called E-MuLA, based on a deep learning network that combines multiple local attention modules to enhance feature extraction from protein sequences. The superior performance of the E-MuLA has been demonstrated through extensive comparisons with LSTM, CNN, AdaBoost, decision trees, KNN, and other state-of-the-art methods. It is noteworthy that the E-MuLA achieved an accuracy of 94.87%, specificity of 98.81%, and sensitivity of 84.18%, indicating that E-MuLA has the potential to become an effective tool for predicting virus subcellular localization.
Design of a Compact Tunable Microstrip Rectenna at 2.45 GHz

Microwave wireless power transmission (MWPT) is an important direction in the microwave engineering applications. As the core of the MWPT system, how to miniaturize the rectenna size and improve its efficiency is the goal of rectenna design. So far, there are a lot of progress in rectenna research. For example, a dipole antenna is fed with a direct integrated rectifier to reduce the rectenna size [1] . Method of improving efficiency of the rectenna is based on the harmonic recycling theory [2] . This paper utilizes an air layer to improve the bandwidth of a patch antenna, and designs a rectifier in the air layer to realize the miniaturization of the rectenna. Moreover, a slider is introduced to tune the impedance matching between the antenna and rectifying circuit. The proposed rectenna is designed and fabricated. The structure of the proposed rectenna and the measurement results are shown in Figure 1. From measurement results, it can be known that the highest measured rectifying efficiency reaches 72.4 % when the input power is 20 dBm. Compared with the work in reference [3], the rectenna size is reduced and the rectifying efficiency is improved. Compared with reference [4], the overall size of the rectenna has been increased, however the rectifying efficiency has been improved by 3.1%. Compared with the reference [5], the highest rectifying efficiency is close, while the size is decreased by 11%. The novel rectenna has a compact size with the dimension of 70 mm × 70 mm × 1mm, which can be well integrated to the microwave wireless power transmission engineering systems.
Exploring the Role of Mangroves in Mitigating Food System Emissions: Bridging Global Experiences and Local Action

This comprehensive report delves into mangrove afforestation programs worldwide, exploring the drivers and enablers of scaling. The first section of the report provides an overview of mangrove coverage, historical trends, and the factors contributing to mangrove deforestation. The subsequent section shifts the focus to global mangrove afforestation programs and examines their role in climate change mitigation and adaptation. It delves into various types of afforestation programs, the approaches employed, the stakeholders involved, and an assessment of the governance and institutional framework of these programs. The third section presents a case study of Vietnam, reviewing the country's efforts to afforestation programs and identifying opportunities for the development of new governance and institutional models. The last section concludes with lessons on the factors supporting successful mangrove restoration programs for Low Emission Food Systems.
Everything is Good for Something: Counterexample-Guided Directed Fuzzing via Likely Invariant Inference

—Directed fuzzing demonstrates the potential to re-produce bug reports, verify patches, and debug vulnerabilities. State-of-the-art directed fuzzers prioritize inputs that are more likely to trigger the target vulnerability or filter irrelevant inputs unrelated to the targets. Despite these efforts, existing approaches struggle to reproduce specific vulnerabilities as most generated inputs are irrelevant. For instance, in the Magma benchmark, more than 94% of generated inputs miss the target vulnerability. We call this challenge the indirect input generation problem. We propose to increase the yield of inputs that reach the target location by restraining input generation. Our key insight is to infer likely invariants from both reachable and unreachable executed inputs to constrain the search space of the subsequent input generation and produce more reachable inputs. Moreover, we propose two selection strategies to minimize the fraction of unnecessary inputs for efficient invariant inference and deprioritize imprecise invariants for effective input generation. Halo, our prototype implementation, outperforms state-of-the-art directed fuzzers with a 15.3x speedup in reproducing target vulnerabilities by generating 6.2x more reachable inputs. During our evaluation, we also detected ten previously unknown bugs involving seven incomplete fixes in the latest versions of well-fuzzed targets.
DE LA FACULTÉ DES SCIENCES Mathématiques

R ÉSUMÉ . — On propose une approche du type Mellin pour l’approximation des courants d’intégration ou la réalisation eﬀective de courants de Green normalisés associés à un cycle V m 1 [div( s j )], où s j est une section méromorphe d’un ﬁbré en droites L j → U au-dessus d’un ouvert U d’un bon espace de Berkovich, lorsque chaque L j est équipé d’une métrique lisse et que codim U ( T j ∈ J Supp[div( s j )]) (cid:62) # J pour tout ensemble J ⊂ { 1 ,. ,p } . On étudie aussi la transposition au cadre non archimédien des formules de Crofton et de King, en particulier la réalisation approchée de courants de Vogel et de Segre. A BSTRACT . — We propose an approach of Mellin type for the approximation of integration currents or the eﬀective realization of normalized Green currents associated with a cycle V m 1 [div( s j )], where s j is a meromorphic section of a line bundle L j → U over an open U in a good Berkovich space when each L j has a smooth metric and codim U ( T j ∈ J Supp[div( s j )]) (cid:62) # J for every set J ⊂ { 1 ,. ,p } . We also study the transposition to the non archimedean context of Crofton and King formulas, particularly the approximate realization of Vogel and Segre currents.
Geochemical Processes During Managed Aquifer Recharge With Desalinated Seawater

We study geochemical processes along the variably‐saturated zone during managed aquifer recharge (MAR) with reverse‐osmosis desalinated seawater (DSW). The DSW, post‐treated at the desalination plant by calcite dissolution (remineralization) to meet the Israeli water quality standards, is recharged into the Israeli Coastal Aquifer through an infiltration pond. Water quality monitoring during two MAR events using suction cups and wells inside the pond indicates that cation exchange is the dominant subsurface reaction, driven by the high Ca2+ concentration in the post‐treated DSW. Stable isotope analysis shows that the shallow groundwater composition is similar to the recharged DSW, except for enrichment of Mg2+, Na+, Ca2+, and HCO3– . A calibrated variably‐saturated reactive transport model is used to predict the geochemical evolution during 50 years of MAR for two water quality scenarios: (i) post‐treated DSW (current practice) and (ii) soft DSW (lacking the remineralization post‐treatment process). The latter scenario was aimed to test soil‐aquifer‐treatment (SAT) as an alternative post‐treatment technique. Both scenarios provide an enrichment of ∼2.5 mg L−1 in Mg2+ due to cation exchange, compared to practically zero Mg2+ currently found in the Israeli DSW. Simulations of the alternative SAT scenario provide Ca2+ and HCO3– remineralization due to calcite dissolution at levels that meet the Israeli standard for DSW. The simulated calcite content reduction in the sediments below the infiltration pond after 50 years of MAR was low (<1%). Our findings suggest that remineralization using SAT for DSW is a potentially sustainable practice at MAR sites overlying calcareous sandy aquifers.
Detect with Style: A Contrastive Learning Framework for Detecting Computer-Generated Images

The detection of computer-generated (CG) multimedia content has become of utmost importance due to the advances in digital image processing and computer graphics. Realistic CG images could be used for fraudulent purposes due to the deceiving recognition capabilities of human eyes. So, there is a need to deploy algorithmic tools for distinguishing CG images from natural ones within multimedia forensics. Here, an end-to-end framework is proposed to tackle the problem of distinguishing CG images from natural ones by utilizing supervised contrastive learning and arbitrary style transfer by means of a two-stage deep neural network architecture. This architecture enables discrimination by leveraging per-class embeddings and generating multiple training samples to increase model capacity without the need for a vast amount of initial data. Stochastic weight averaging (SWA) is also employed to improve the generalization and stability of the proposed framework. Extensive experiments are conducted to investigate the impact of various noise conditions on the classification accuracy and the proposed framework’s generalization ability. The conducted experiments demonstrate superior performance over the existing state-of-the-art methodologies on the public DSTok, Rahmouni, and LSCGB benchmark datasets. Hypothesis testing asserts that the improvements in detection accuracy are statistically significant.
Environmental assessment of the greenhouse gases emission from poultry production in Russia’s central region

With an estimated rise in poultry production and consumption of chicken meat in Russia by 9% up to 2022, as well as development of selfsustainable poultry production, the need has arisen for environmental assessment of this production, and within it especially greenhouse gases (GHGs) emission assessment. The goal of this work is to show a calculation procedure for obtaining estimations for the carbon footprint of the 1 kg of live chicken at the farm gate, taking into account regional typological features of agricultural production in agroecosystems. The methodology of carbon footprint (CF) calculation is based on the life cycle assessment (LCA) methodology, and on IAGRICO2 calculator, developed for agriculture products. Results have shown that in modern technology of poultry farming, 5.79 kg CO2 е was emitted on average per kg of body mass, and that about 47% of emission was from manure, around 27.5% from crop production (fuel and fertiliser) and 25.5% from fuel and energy needed for heating, sanitation and feeding of chickens. The main distinction of Central Russia is low efficiency of the fertiliser application on crop fields and manure management, storage and utilisation, which has as a result high emissions of the nitrous oxide. This is the field where the implementation of the intensive technologies of precise farming, manure handling, utilisation and management will significantly decrease GHG emission, with preserving yield of crops and quantity and quality of chicken meat.
Reclaiming the Rotten: Understanding Food Fermentation in the Neolithic and Beyond

ABSTRACT People have harnessed beneficial microbes to preserve, protect, and improve food for thousands of years. However, the significance and techniques of food fermentation are poorly understood in prehistoric archaeology. This paper explains what food fermentation is and discusses its relevance in an early farming context. It sets out the beginnings of a theoretical and material framework that can be drawn upon for further study of this crucial but overlooked aspect of prehistoric food cultures. Focus is on the British Neolithic, but the central concepts are applicable in other periods and places.
A Gourd-Shape Architecture of HTS Coil With Functions of Flux Density Amplification and Flux Accumulation

This paper presents a gourd-shape closed loop with double circular configurations at different diameters, which is arranged by slitting second-generation high-temperature superconducting (2G HTS) tape along its length direction. The flux density amplification and flux accumulation mechanisms of this architecture with closed-loop HTS coils using both experimental and numerical methods were performed. Flux density amplification and flux accumulation in small circular configuration was observed by using field-cooling (FC) method in LN2 temperature. The mechanisms of flux density amplification and flux accumulation can be understood by the flux conservation law in superconducting closed loop. Three types of arrangements were carried out to confirm the principles of flux density amplification and flux accumulation. Compared with existing HTS magnetic magnets by winding on former, this gourd-shape HTS coil is more compact and operates in persistent current mode (PCM). Besides, it can be particularly generalized to big dimensional size permanent HTS magnet by stacking gourd coils if 2G tape with large width can be prepared for industrial application. Our results show that the proposed gourd-shape HTS coil is very promising in full HTS magnet with higher magnetic field in low temperature and has the potential to provide much stronger magnetic fields relative to existing permanent magnets.
Towards True In-situ Temperature Compensation Utilizing Multiple Parameter Decoupling for Resonant MEMS Sensors Subject to Blue Sideband Excitation

This letter conducts a thorough comparison between two temperature compensation methods for resonant micro-electro-mechanical-system (MEMS) sensors, i.e., 1) a newly proposed in-situ temperature compensation technique based on a multiple parameter decoupling (MPD) using a single resonant MEMS sensor subject to blue-sideband excitation, and 2) the prevailing method utilizing a temperature sensor, which, in this letter, is a resonant thermometer in close vicinity of the sensor. Experimental results show that the MPD-based in-situ temperature compensation method offers better noise performance, long-term stability (fourfold at 1000s integration time) and application simplicity, compared with the compensation method using an additional thermometer, affirming that the proposed subject is of considerable potential for true in-situ temperature compensation for high-precision resonant MEMS sensors.
Cellulose Sulfate Nanofibers for Enhanced Ammonium Removal

In this study, a sulfonation approach using chlorosulfonic acid (CSA) to prepare cellulose sulfate nanofibers (CSNFs) from raw jute fibers is demonstrated. Both elemental sulfur content and zeta potential in the CSNFs are found to increase with increasing CSA content used. However, the corresponding crystallinity in the CSNFs decreases with the increasing amount of CSA used due to degradation of cellulose chains under harsh acidic conditions. The ammonium adsorption results from the CSNFs with varying degrees of sulfonation were analyzed using the Langmuir isotherm model, and the analysis showed a very high maximum ammonium adsorption capacity (41.1 mg/g) under neutral pH, comparable to the best value from a synthetic hydrogel in the literature. The high ammonium adsorption capacity of the CSNFs was found to be maintained in a broad acidic range (pH = 2.5 to 6.5).
Mass balance characterisation of Al-7Si-Mg alloy microstructures as a function of solution treatment time

Mass balance calculations were performed to model the effect of solution treatment time on A356 and A357 alloy microstructures. Image analysis and electron probe microanalysis were used to characterise microstructures and confirm model predictions. In as-cast microstructures, up to 8 times more Mg is tied up in the π-phase than in Mg2Si. The dissolution of π is accompanied by a corresponding increase in the amount of β-phase. This causes the rate of π dissolution to be limited by the rate of β formation. It is predicted that solution treatments of the order of tens of minutes at 540 °C produce near-maximum T6 yield strengths, and that Mg contents in excess of 0.52 wt% have no advantage.