Miracle-dz/UniFAR-FTUs huggingface dataset:
IMPROVED ADAPTIVE NONLINEAR CONTROL FOR VARIABLE SPEED WIND-TURBINE FED BY DIRECT MATRIX CONVERTER

This paper proposes a robust decoupling power algorithm based on a doubly fed induction generator (DFIG) for variable speed wind-turbine (WT). The DFIG rotor circuit is fed by the direct matrix converter (DMC), which presents several features such as no need to the dc-bus voltage, sinusoidal supply, rotor side waveforms, bidirectional power flow, and adjustable input power factor. The 18 bidirectional switches are controlled using the Venturini modulation technique. On the other hand, the DFIG stator circuit is connected directly to the grid. The nonlinear control strategy based on feedback linearization is applied to control the stator power (Ps and Qs) independently using the rotor quadrature and direct currents (irq and ird), which present the images of the previous stator powers. Some limitations appear in the power algorithm using the conventional pi controller, especially in power tracking, error, and quality. In this context, the model reference adaptive controller (MRAC) presents an alternative solution, a robust and efficient controller proposed instead of the pi controllers to control stator powers. Finally, the simulation results confirm that the proposed algorithm could work under hard conditions and demonstrate that the wind energy conversion system (WECS) provides enhanced dynamic responses in transient and steady states and good power quality delivered to the grid.
A New Anomaly-Based Intrusion Detection System for MIL-STD-1553

MIL-STD-1553 is a communication standard developed by the US DoD in 1975 and used in military aircraft, land, and space vehicles. It enables computers and devices to interact with each other. MIL-STD-1553 is used in safety-critical systems due to its dual redundant bus structure, high reliability, and low fault rate. While the standard was considered to be secure when it was developed, MIL-STD-1553-based systems have become vulnerable and they are an easy target for attackers. In this research, we propose a new anomaly-based intrusion detection system for MIL-STD-1553 that uses machine learning for classification purposes. We experimentally evaluated the proposed system against cyber attacks. We observed that Stochastic Gradient Descent provides adequate results for the detection of intrusions on the MIL-STD-1553 bus. Overall experimental results show that the proposed system can be used to detect intrusions on MIL-STD-1553-based communications.
A naturalist's guide to the birds of Malaysia and Singapore

High quality photographs from some of Malaysia's top nature photographers are accompanied in this title by detailed species descriptions, which include nomenclature, length, plumage, distribution, habits and habitat. The user-friendly introduction covers climate, vegetation, biogeography, and the main bird watching sites. This is the only regional bird guide to include Mann's complete checklist of the birds of Malaysia, the definitive reference to Malaysian birds.
Whole-genome CpG-resolution DNA Methylation Profiling of HNSCC Reveals Distinct Mechanisms of Carcinogenesis for Fine-scale HPV+ Cancer Subtypes

DNA methylation is a vital early step in carcinogenesis. Most findings of aberrant DNA methylation in head and neck squamous cell carcinomas (HNSCC) are array based with limited coverage and resolution, and mainly explored by human papillomavirus (HPV) status, ignoring the high heterogeneity of this disease. In this study, we performed whole-genome bisulfite sequencing on a well-studied HNSCC cohort (n = 36) and investigated the methylation changes between fine-scaled HNSCC subtypes in relation to genomic instability, repetitive elements, gene expression, and key carcinogenic pathways. The previously observed hypermethylation phenotype in HPV-positive (HPV+) tumors compared with HPV-negative tumors was robustly present in the immune-strong (IMU) HPV+ subtype but absent in the highly keratinized (KRT) HPV+ subtype. Methylation levels of IMU tumors were significantly higher in repetitive elements, and methylation showed a significant correlation with genomic stability, consistent with the IMU subtype having more genomic stability and better prognosis. Expression quantitative trait methylation (cis-eQTM) analysis revealed extensive functionally-relevant differences, and differential methylation pathway analysis recapitulated gene expression pathway differences between subtypes. Consistent with their characteristics, KRT and HPV-negative tumors had high regulatory potential for multiple regulators of keratinocyte differentiation, which positively correlated with an expression-based keratinization score. Together, our findings revealed distinct mechanisms of carcinogenesis between subtypes in HPV+ HNSCC and uncovered previously ignored epigenomic differences and clinical implications, illustrating the importance of fine-scale subtype analysis in cancer. Significance: This study revealed that the previously observed hypermethylation of HPV(+) HNSCC is due solely to the IMU subtype, illustrating the importance of fine-scale subtype analysis in such a heterogeneous disease. Particularly, IMU has significantly higher methylation of transposable elements, which can be tested as a prognosis biomarker in future translational studies.
Évolution des mouvements verticaux néogènes de la chaîne du Rif (Nord-Maroc) : apports d’une analyse structurale et thermochronologique

La chaine du Rif (Nord du Maroc) constitue, avec les Cordilleres des Betiques (Sud de l’Espagne), la terminaison occidentale de la ceinture alpine. C’est un secteur cle pour la comprehension des mouvements verticaux associes aux processus orogeniques. Jusqu’a present, aucune etude n’a permis de contraindre les mouvements verticaux posterieurs au Miocene inferieur, malgre la presence de depots marins pliocenes sureleves. L’objectif de ce travail est d’apporter des arguments permettant de discuter des mecanismes geochronologiques et cinematiques impliques dans les mouvements verticaux de la marge du Rif depuis le Neogene. Une comparaison des deplacements identifies dans les zones internes, a pu etre effectuee, avec ceux estimes dans le domaine des flyschs (Sud de l’accident de Jebha), grâce aux donnees AHe. Les correlations entre mouvements verticaux et evolution du champ de deformation mettent en evidence le lien existant entre les periodes de mouvements verticaux majeurs et les phases d’extension radiale. 1-Les derniers stades d’exhumation des unites metamorphiques, depuis pres de 12-10 km de profondeur, resultent d’un stade d’extension radiale affectant ces formations. Le domaine de collapse s’etend depuis le facies Schiste Vert jusqu’au domaine fragile durant l’Aquitano-Burdigalien. Les mouvements extensifs sont limites aux parties superficielles de l’orogene tandis que les parties plus profondes et situees en avant-chaine sont en compression. 2-Une periode de surrection lente associee a de l’extension radiale, affecte l’integralite des zones internes, au moins depuis le Pliocene inferieur. La zone des flyschs se sureleve a plus grande vitesse.
Training Low-Latency Spiking Neural Network with Orthogonal Spiking Neurons

Spiking Neural Networks (SNNs) as a biology-inspired method mimicking the signal transmission of brain neurons can be managed in an event-driven manner, and generate binary signals that are computing-friendly to hardware by their recurrent time window. However, training high-performing SNNs from scratch emerges intrinsic defects, a large number of time steps (>100) is unable to balance the performance with latency. To overcome this issue, we show that SNNs can be trained in fewer time steps (<4) through the proposed Alterable Space-Time LIF (AST-LIF) block, which transforms partial time steps into the space domain. AST-LIF iterates the signals in horizontal and vertical directions in a time step unit, and utilizes the global dependency as Long short-term memory (LSTM) model in a space step unit. Our approach aims to significantly reduce SNNs latency while ensuring high performance. For proof-of-concept, extensive experiments show that balanced spatio-temporal architecture can maintain the performance of SNNs with smaller time steps $(t=2)$.
Intercropping with alfalfa and co-inoculation of AMF and PGPR improve growth, yield, grain bioactive quality, and soil fertility of barley

ABSTRACT The use of intercropping systems and beneficial microorganisms to improve the performance of crops constitutes a promising strategy. In this context, a pot experiment was conducted to evaluate the effects of intercropping and inoculation with arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) on the performance of barley and alfalfa plants and soil health. Three inoculation treatments (for both monocropped and intercropped plants) and the control were used: (1) AMF-inoculated plants; (2) PGPR-inoculated plants; (3) AMF+PGPR co-inoculated plants. Combining intercropping and AMF+PGPR co-inoculation improved shoot and root dry weight by 167% and 300% in barley and by 712% and 617% in alfalfa, respectively, compared to the controls. Similarly, in barley intercropped and inoculated with AMF+PGPR, the number of grains per spike and the thousand-grain weight were enhanced by 124% and 122%, respectively. Applying intercropping and co-inoculation of AMF+PGPR increased the protein, total phenolic, and flavonoid contents of barley grains by 99%, 132%, and 343%, respectively. The contents of soil nitrogen and phosphorus were improved by 387% and 270% in barley soil and by 359% and 212% in alfalfa soil, respectively, compared to monocultures.
The Inquiry Collaborative Learning Design Virtual Laboratory Based And Remote Virtual

This study investigated the design of learning in a virtual laboratory through collaborative inquiry and its effect on student knowledge. Learning design produces learning models that are measured based on validity, practicality, and effectiveness. The research method uses research and development that produces products and product effectiveness. The trial results were conducted on a small scale on eight students to measure the quality of student learning. To test the validity of the product through expert assistance, all the answers of the validator were calculated using Aiken's V validity coefficient. Further findings implied that students have begun to accept technology as a learning tool and provided opportunities for universities in learning development.
Wireless Communication Using Autoencoder

Wireless communication is a widely used technology for transmitting information over long distances without the use of physical connections. Various environmental factors make wireless communication challenging. However, current trends in deep learning have made it possible to jointly optimize the transmitter and receiver. Autoencoder is a type of deep neural network which aims at deriving features useful to reconstruct the input data. This work aims at developing end to end communication systems with different channel models using basic deep neural network and autoencoder. Simulations are carried out with modulation techniques for AWGN and Rayleigh channel models. The developed systems are evaluated by transmitting random bits, text and image data. Evaluation metrics include bit error rate, number of characters in error and structured similarity index for random bits, text and image data respectively. Results show that autoencoder is able to recover back both text and Image data more efficiently than the baseline deep learning model.
Prevalence of Premenstrual Syndrome In Females of Gujranwala Division And Its Associated Risk Factors

Introduction: Premenstrual syndrome (PMS) is characterized by cyclic reoccurrence of distressing somatic and psychological manifestations, during luteal phase of menstrual cycle. Present research work aims to investigate prevalence of PMS in females of Gujranwala division Pakistan and to explore various risk factors associated with this syndrome. Methods: The study included self-administered questionnaire, for diagnosis of PMS and PMDD. Participants were analysed for socio-demographic characteristics and menstrual history, serum cholesterol and haemoglobin levels of patients and control were measured. Results: In the present study, 56% females were screened positive for PMS while Prevalence PMDD was 18%. Most common physical symptoms of PMS were abdominal bloating (63.2%), muscle pain (71.73%), lack of energy (85.85%) and appetite change (79.15%) whereas major distressing psychological were Irritability (82.32%), anger (74.55%), depression (49%) and anxiety (63.2%). Prevalence of PMS was 22.6% in underweight, 50.1% in participants having normal weight, 15.5% in overweight individuals and 11.6% in obese. Anaemia (P = 0.00), fatigue (P = 0.00), dysmenorrhea (P = 0.00), family history of PMS (P = 0.00) and residential area (P = 0.047) were major risk factors for development of different symptoms of PMS. Conclusion: Statistically significant association was not confirmed between PMS, obesity and blood cholesterol level. PMS is a common menstrual disorder among reproductive females of Gujranwala division, Pakistan. Findings of the study revealed that anemic females were at risk to develop PMS symptoms.
Design of Unmanned Aerial Vehicle for Stability

For Unmanned Aerial Vehicles (UAV), electric power is a popular choice for its propulsion. As a result, the use of UAVs is growing rapidly in defense and commercial applications. Electric UAVs have many benefits due to their compact design, lightweight construction, and advanced control and communication systems, making them an ideal choice for small-scale operations. This paper presents a mathematical model for quadcopter stability during external disturbances. A hardware prototype was designed to measure the environmental disturbances using sensors such as a barometer, magnetometer, smoke, and ultrasonic sensors and integrating them with the MSP430 microprocessor. Based on sensor input, a joystick was used to control the pitch, roll, and yaw of a UAV. Later, PID controllers were simulated to control a quadrotor electric UAV's attitude stability and measure deviation from the reference position using the sensor's input.
Analisis kebutuhan pelatihan karya tulis ilmiah untuk guru sebagai upaya pengembangan keprofesian berkelanjutan

Pengembangan keprofesian berkelanjutan bagi guru merupakan suatu keharusan. Salah satu aspek dari pengembangan tersebut adalah publikasi ilmiah, yang dilakukan oleh guru melalui penulisan karya tulis ilmiah. Hal ini merupakan salah satu karakteristik dari guru profesional, yang ditunjukkan melalui kebiasaan menulis dan melakukan penelitian. Penelitian ini bertujuan untuk menganalisis kebutuhan pengembangan keprofesian berkelanjutan guru melalui publikasi ilmiah. Metode kualitatif dengan pendekatan deskriptif digunakan dalam penelitian ini, yang difokuskan pada analisis kebutuhan pelatihan publikasi ilmiah bagi guru sekolah menengah kejuruan (SMK) di Kota Palembang. Subjek penelitian terdiri dari 37 guru SMK negeri dan swasta, yang dipilih secara purposive. Data penelitian dikumpulkan melalui kuesioner, observasi, wawancara, dan dokumentasi. Selanjutnya, analisis data dilakukan dengan menggunakan teknik triangulasi. Hasil penelitian menunjukkan bahwa guru SMK di Kota Palembang memiliki motivasi dan kemauan yang tinggi untuk menyusun karya tulis ilmiah. Namun, jumlah publikasi ilmiah berbasis hasil penelitian di jurnal masih tergolong minim. Kesimpulan dari penelitian ini adalah kebutuhan pelatihan karya tulis ilmiah perlu difokuskan pada pengembangan pengetahuan dan keterampilan guru dalam melakukan penelitian, serta guru memerlukan pendampingan untuk dapat mempublikasikannya ke jurnal ilmiah.
Progress in understanding and treating idiopathic pulmonary fibrosis: recent insights and emerging therapies

Idiopathic pulmonary fibrosis (IPF) is a long-lasting, continuously advancing, and irrevocable interstitial lung disorder with an obscure origin and inadequately comprehended pathological mechanisms. Despite the intricate and uncharted causes and pathways of IPF, the scholarly consensus upholds that the transformation of fibroblasts into myofibroblasts—instigated by injury to the alveolar epithelial cells—and the disproportionate accumulation of extracellular matrix (ECM) components, such as collagen, are integral to IPF’s progression. The introduction of two novel anti-fibrotic medications, pirfenidone and nintedanib, have exhibited efficacy in decelerating the ongoing degradation of lung function, lessening hospitalization risk, and postponing exacerbations among IPF patients. Nonetheless, these pharmacological interventions do not present a definitive solution to IPF, positioning lung transplantation as the solitary potential curative measure in contemporary medical practice. A host of innovative therapeutic strategies are presently under rigorous scrutiny. This comprehensive review encapsulates the recent advancements in IPF research, spanning from diagnosis and etiology to pathological mechanisms, and introduces a discussion on nascent therapeutic methodologies currently in the pipeline.
Advancements and Challenges in 5G Networks

Fifth generation (5G) wireless communication technology in wireless networks, has the ability to dramatically transform how, we connect to the internet and interact. In this essay, we examine the most recent developments in 5G wireless transmission technologies as well as their uses. We give a quick overview of the development of wireless transmission networks towards 5G throughout history. The technical aspects of 5G networks, such as the underlying design, radio access technologies, and spectrum allocation, are then covered in depth. The possible uses of 5G networks, including those for smart cities, autonomous vehicles, virtual and augmented reality, and health care, are further examined in the paper. Significant advantages from these applications include increased energy efficiency, reduced latency, faster data transfer rates, and better network dependability. The paper also emphasizes the issues that must be resolved in order to completely utilize the potential of 5G networks. These include worries about security and privacy as well as problems with network penetration. This review paper offers a thorough grasp of 5G wireless communication technologies and potential uses for them. According to the research presented in this paper, 5G networks have the potential to revolutionize a wide range of industries and enhance people's quality of life all over the globe. However, overcoming the obstacles and restrictions related to 5G will be essential for its effective application.
Intercropping Perennial Fruit Trees and Annual Field Crops with Aromatic and Medicinal Plants (MAPs) in the Mediterranean Basin

The Mediterranean basin (MB), a “climate hotspot”, is experiencing faster than average increases in global temperature and water deficit, as well as soil degradation, with detrimental impacts on food crop yield and pest/pathogen incidence. Hence, there is an urgent requisite for sustainable crop diversification strategies to promote crop resilience, soil quality conservation and pest/pathogen control. Intercropping is a strategy that has yet to be widely adopted. Presently, cereal–legume combinations represent the most common intercrops. Of relevance, a large number of medicinal and aromatic plants (MAPs), native to the MB, serve as potentially profitable indigenous resources for intercropping with food crops. Environmentally sustainable benefits of MB MAP intercropping with food crops have ironically been reported largely from research outside the MB. The present study aims to review the published literature from 2003 to 2023 on MAP intercropping with perennial nut/fruit crops and annual field crops in the MB. Published research is scarce but shows a promising upward trend, with 70% and 47% of intercropping studies with perennials and annual field crops, respectively, dated between 2020 and 2023. MAP intercropping shows potential in augmenting yield, pest/pathogen and weed control, soil health and cash crop quality, warranting further research with more widespread adoption in the MB.
Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2

The potential low-energy feature of the spiking neural network (SNN) engages the attention of the AI community. Only CPU-involved SNN processing inevitably results in an inherently long temporal span in the cases of large models and massive datasets. This study introduces the MAC array, a parallel architecture on each processing element (PE) of SpiNNaker 2, into the computational process of SNN inference. Based on the work of single-core optimization algorithms, we investigate the parallel acceleration algorithms for collaborating with multi-core MAC arrays. The proposed Echelon Reorder model information densification algorithm, along with the adapted multi-core two-stage splitting and authorization deployment strategies, achieves efficient spatio-temporal load balancing and optimization performance. We evaluate the performance by benchmarking a wide range of constructed SNN models to research on the influence degree of different factors. We also benchmark with two actual SNN models (the gesture recognition model of the real-world application and balanced random cortex-like network from neuroscience) on the neuromorphic multi-core hardware SpiNNaker 2. The echelon optimization algorithm with mixed processors realizes 74.28% and 85.78% memory footprint of the original MAC calculation on these two models, respectively. The execution time of echelon algorithms using only MAC or mixed processors accounts for ≤ 24.56% of the serial ARM baseline. Accelerating SNN inference with algorithms in this study is essentially the general sparse matrix-matrix multiplication (SpGEMM) problem. This article explicitly expands the application field of the SpGEMM issue to SNN, developing novel SpGEMM optimization algorithms fitting the SNN feature and MAC array.
Evaluation of a proximal vision data acquisition system for measuring spatial variability in lettuce growth

[Abstract]: In-field crop mapping provides the growth and yield data required to spatially manage inputs such as irrigation water and fertiliser. This study evaluated the potential to use low cost cameras as proximal sensors to spatially map lettuce growth throughout a growing season. Two 9 x 11 m measurement plots of 42 sampling points each were established within a sprinkler irrigated lettuce crop. Ten non-uniform irrigations were applied during the season. After each irrigation, the canopy and head diameter of two plants at each sampling point were physically measured. Colour digital cameras were also used to capture images of the lettuces from either 1.15 m or 10 m above the ground surface. Image processing software was then used to calculate the individual plant canopy area and lettuce head diameter. The lettuce growth measurements obtained using the 1.15 m camera were generally well correlated (R2 = 0.73-0.89) with the physical measurements 23 days after transplanting. Weaker correlations (R2 = 0.35-0.74) were observed at earlier dates possibly due to physical measurement errors of plant size early in the season. The correlations between the canopy measurements obtained using the 10 m camera and the physical measurements were generally 0.1 to 0.2 lower than those obtained using the 1.15 m camera, presumably due to lower pixel resolution. Correlations between the head diameter obtained using the 1.15 m camera and the physical measurements ranged from 0.83 to 0.92