Miracle-dz/UniFAR-FTUs huggingface dataset:
Origin of Large Igneous Provinces: The importance of a definition

In the original defi nition of a Large Igneous Province (LIP) much emphasis was put on the “extraordinary” character of these provinces. Such emphasis might have contributed to bias the form in which these provinces are commonly visualized, and consequently has contributed to the selective acceptance of genetic models. To avoid such bias, in this chapter the various available defi nitions are examined, taking into consideration the rules of logic that help us to avoid fallacies. From these defi nitions, the most critical parameters are identifi ed, and an alternative model of formation of LIPs is advanced. The model developed here envisages LIPs as an extreme of a continuum in volcano-magmatic processes that are produced by essentially the same underlying processes. The differences between LIPs and non-LIPs are conceived as the result of different conditions present in a particular region, but that nonetheless have nothing extraordinary. Although the model developed here is one of several possible alternatives, by having identifi ed the most common fallacies surrounding a LIP, even from its very defi nition, it might be possible to assess those alternative models in a more equilibrated form in future works.
Effects of the agricultural food security pack programme in Zambia: the case of Mpulungu District

Agricultural food programmes are one of the means to improve household food security for vulnerable small-scale farmers in sub-Saharan Africa. In Zambia, household food insecurity is entrenched among small-scale farmers. Despite the implementation of the food security pack programme by the Zambian government, there is scanty scientific information on the performance of the programme. The study reviewed the effects of the food security pack programme on land cultivation and maize crop productivity in Mpulungu district using a mixed-methods design. Using a simple random sampling and Slovin’s Formula, 147 beneficiaries and 152 non-beneficiaries were selected as questionnaire respondents. The study purposely selected two government officials, one traditional leader, and five focus groups for interviews and focus group discussions. Descriptive data were generated using SPSS and content analysis. The study revealed that 66% of the beneficiaries, cultivated between a quarter (0.25) and half (0.50) a hectare compared to the non-beneficiaries, whose 61% cultivated less than a quarter (<0.25) hectare. Similarly, 70.1% of the beneficiaries, harvested more than 20 (50kg) bags of maize grain on average, per 0.25 hectares of land compared to 8% of the non-beneficiaries for three farming seasons reviewed. The land cultivated by the beneficiaries had a larger mean (M ₌ 2.00) than the land cultivated by the non-beneficiaries (M ₌ 1.59). Maize crop productivity by the beneficiaries had a larger mean (M ₌ 4.25) than the non-beneficiaries (M ₌ 2.45). There was a statistically significant difference in land cultivation and maize crop productivity between the beneficiaries and non-beneficiaries, with the former having more land cultivated and higher maize crop productivity than the latter. Administrative challenges in programme implementation were noticed. Farming inputs were received late and outside the planting period due to the centralised purchase system despite the beneficiaries performing better than the non-beneficiaries. Funds for the purchase of agricultural inputs were released late by the Zambian government. The study concluded that the food security pack programme had a significant positive effect on land cultivation and maize crop production for benefiting households. The study recommends decentralisation of the supply of farming inputs to the districts for timely delivery to the beneficiaries, increasing the number of beneficiaries, and timely release of funds for the purchase of farming inputs by the Zambian government. Key words: Agriculture, food security, small-scale farmer, empowerment, vulnerable farmers
Integrated geospatial evaluation of manual cadastral mapping: a case study of Pakistan

Cadastral mapping in Pakistan is often sketched on paper or cloth and generally falls below cartographic standards, lacking details on coordinate systems, datum and directional information of parcel lines. Survey numbers for parcel identification also lack digital interoperability. Parcel measurements and ownership information are manually recorded in multiple separate registers. The objective of this study is to leverage geospatial technology for automation, auditing and validation of present manual cadastral mapping in Pakistan. Only 62% of the parcel geometry could be automated due to irregular parcel shapes. However, the process revealed some interesting discrepancies in cadastral datasets. Geospatially calculated areas and rectangular base areas are approximately eight acres less than the officially notified estate areas recorded in the field book. This study advocates using geospatial technology to update manual cadastral mapping practices to help avoid such errors when validating existing datasets.
HYBRID DEEP LEARNING APPROACH FOR VEHICLE’S RELATIVE ATTITUDE ESTIMATION USING MONOCULAR CAMERA

Abstract. Relative pose estimation using a monocular camera is one of the most common approaches for aiding vehicle’s navigation. It involves determining the position and orientation of a vehicle relative to its surroundings using only a single camera. This can be achieved through four main steps: feature detection and matching, motion estimation, filtering and optimization, and scale estimation. Feature tracking involves detecting and tracking distinctive visual features in the environment, such as corners or edges, and using their relative motion to estimate the camera's movement. This approach can be prone to errors due to feature detection and tracking difficulties, as well as issues with moving objects, occlusions, and changes in lighting conditions. These typical computer vision approaches are computationally intensive and may require significant processing power as well, which limits their real time application. This paper proposes a hybrid deep neural network approach for estimating the relative attitude of a vehicle using a monocular camera to aid in vehicle navigation. The proposed neural network adopts a relatively shallow architecture to minimize the computational cost and to meet the real-time requirements of low-cost processing systems. The network is trained using the KITTI dataset and can estimate the relative attitude of the vehicle with a RMSE of relative orientation of 0.017 degrees per frame. The processing time of the proposed approach is around 28 ms per frame including both the tracking and network prediction steps, which is significantly faster than the typical estimation pipelines. The results show that the proposed approach is a viable alternative to conventional computer vision methods and can significantly reduce computational costs, deal with the confusing scenarios of the moving objects while maintaining a good accuracy in estimating ego-motion.
CONSTRUCTIVE-SYNTHESIZING MODELING OF NATURAL LANGUAGE TEXTS

Means for solving the problem of establishing the natural language texts authorship were developed. Theoretical tools consist of a constructors set was developed on the basis of structural and production modeling. These constructors are presented in this work. Some results of experimental studies based on this approach have been published in previous works by the author, the main results should be published in the next ones. Constructors developed: converter of natural language text into tagged, tagged text into a formal stochastic grammar and the authors style similarity degree establishment of two natural language works based on the coincidence of the corresponding stochastic grammars (their substitution rules). The proposed approach makes it possible to highlight the semantic features of the author's phrases construction, which is a characteristic of his speech. Working with a sentence as a unit of text to analyze its construction will allow you to more accurately determine the author's style in terms of the use of words, their sequences and characteristic language constructions. Allows not to be attached to specific parts of speech, but reveals the general logic of building phrases.
The modern trends of infrastructure development

Purpose - is to summarise and present the development of theoretical foundations of the process of integration of the national industrial infrastructure system based on logistic transformations. Methodology of research. Theoretical and methodological basis of the study are research works of domestic and foreign scholars on the integration of social and economic systems. The article used the dialectical method of cognition, as well as the following methods: a systematic and structural analysis, logical generalization - the study of the formation of scientific positions and forming the methodological foundations of the development of production infrastructure. Results. Implemented theoretical and methodological substantiation of the implementation of transformational changes infrastructural capacity in the context of sustainable development of the regional economic system. The transformation of the infrastructure capacity in the region is defined as a process of deep changes in the quantitative and qualitative characteristics of the Multisectoral infrastructure complex on the principles of sustainable development in the direction of achieving the optimum, tailored to the needs of the regional parameters of its operation, taking into account global trends and inherited experience. The authors constructed a conceptual framework based on the transformation of infrastructure transformation sector. Transport related activities have many impacts on the environment. The most important effects are contribution to climate change, to local air pollution, to noise levels, to biodiversity loss and natural resources depletion. Practical value. These findings have practical value in the development of regional strategies and programs of development in the context of the European integration vector.
Marginal and Steppic Areas as Sources for Archaeological Debate: A Case for “Active Symbiosis” of Town and Country

The division of landscapes suggested by the organisers of this conference is a striking one. Whereas the first, constituent space comprises the base, that is, the actual physical surroundings, the other two are divisions of an entirely socio-political and socio-economic nature, and the word “space” there is entirely conceptual. Into these conceptual spaces, the organisers have placed “raw topics”, providing concrete handles for the nitty-gritty, i.e. actual subjects for papers. Since the scene is set in Northern Mesopotamia and Northern Syria, the actual space we are dealing with (the constituent space) partly has a steppe character, and partly concerns a marginal area in terms of agriculture: it hovers around the 200mm isohyet. The present paper devotes itself to what is called confederate space, mainly discussing aspects of raw topics 3 and 8, i.e. “nomadism” and political structures. Archaeological analogies with present or sub-recent ethnographic datasets are famously full of pitfalls, and this goes a fortiori for studies about nomadic ways of life. Apart from such analogies, however, virtually our only source for the nomadic way of life in the ancient Near Eastern Middle Bronze Age – which is the period I am concerned with here – is the textual evidence from Mari. Unfortunately, rich as that material may be, for the purpose at hand it is not ideal. It is no secret that these texts were written with the bias of a settled urban population, who were mainly concerned with procuring the results of the cultivation of wheat and barley, and who concentrated on the sustained effort to safeguard their resources, the fields, the water and the concomitant infrastructure. The texts may therefore at least be suspected of not reflecting the situation outside the towns in a balanced way. The bias opposed the settled, urban society of kings, civil servants, soldiers, craftsmen and traders, to the other sector, the roaming tribes said to be basically inimical to the settled urban centres, the unruly “nomads” with their sheep and goats, who often had to be forced “to see reason” by the troops of the urbanites. Additionally, also our modern way of evaluating the texts is sometimes biased. Even after what Larsen wrote about perceptions induced by ancient texts,1 the latter are often still treated as if they yield direct, “positive” (= positivistic) knowledge.
A Wireless Integrated EEG–fNIRS System for Brain Function Monitoring

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have emerged as continuous monitoring techniques for neural cluster electrical activity and local cerebral hemodynamic activity, playing a crucial role in both basic scientific research and clinical applications. However, the progress of many neuroscience studies is hindered by limitations in instrument size, portability, synchronous acquisition, and mobility. To overcome these limitations, this article proposes an integrated system comprising 112 fNIRS channels and 16 EEG channels. The characteristic of this system is its support for measurements under mobile conditions, and the scalable design of the sensor cap allows for flexible configuration of EEG and fNIRS sensors in different experiments. A corresponding upper computer software was developed to monitor brain activity in real-time. Noise and drift tests demonstrate that the instrument we designed meets the requirements for physiological signal acquisition. In visual evoked experiments, the local hemodynamic changes and visual evoked potentials of the subjects show good consistency with the experimental results reported in the literature, indicating that the proposed EEG–fNIRS acquisition system can simultaneously monitor both brain electrical activity and hemodynamic changes.
Zuranolone – synthetic neurosteroid in treatment of mental disorders: narrative review

With each passing year, the number of people suffering from mental disorders grows at a disturbing speed. Neuroactive steroids are a new promising group of drugs with the potential for use in many diseases like postpartum depression, postnatal psychosis, major depression, insomnia, bipolar disorder, and Parkinson’s tremor, due to their ability to modulate the activity of GABAA receptor. Neurosteroids are progesterone metabolites that are synthesized from cholesterol or steroid hormones in various brain regions. They regulate neuronal development, regeneration, and neurotransmission. They are implicated in mood disorders, anxiety disorders, schizophrenia, PTSD, and impulsive aggression. Neurosteroids have been studied for their potential to prevent or treat neurodegenerative diseases such as Alzheimer’s disease and HIV-associated dementia. They can promote neurogenesis, neuronal survival, myelination, and memory function. They can also affect the growth and sensitivity of hormone-dependent brain tumors such as gliomas. Zuranolone, a newly registered neurosteroid drug has shown huge flexibility in both clinical and ambulatory treatment thanks to its pharmacokinetic traits, especially the possibility for oral administration, unlike its predecessor Brexanolone. Zuranolone is a synthetic positive allosteric modulator of the GABAA receptor that can be taken orally. The review aims to summarize the current knowledge on zuranolone as a novel neurosteroid drug for various mental disorders, especially for postpartum mental disorders for which this drug was meant originally. It covers studies indexed in the PubMed, Scopus, and Web of Science databases published since 2017. Keywords used in the search, as well as inclusion and exclusion criteria, are given in the aims and methodology section. The review explains the evidence for the role of neurosteroids, especially allopregnanolone, in the pathophysiology and treatment of postpartum depression. It discusses the mechanisms of neurosteroid action, the changes in neurosteroid levels during pregnancy and postpartum, and the clinical trials of brexanolone and zuranolone, two synthetic analogs of allopregnanolone, for postpartum depression. It provides an overview of the biosynthesis and metabolism of neurosteroids in the central and peripheral nervous system. Furthermore, it explains the different sources and pathways of neurosteroid production and the factors that influence their synthesis and regulation, such as stress, hormones, drugs, and genetic variations. The review also explores the potential relevance of neurosteroids for other psychiatric disorders, such as major depression, bipolar disorder, post-traumatic stress disorder (PTSD), schizophrenia, and premenstrual dysphoric disorder. Finally, it highlights the associations between neurosteroid levels and symptom severity and the effects of neurosteroid modulation on mood, cognition, and neuroplasticity.
A mesocosm analytical study on the impact of freshwater mussel (Lamellidens marginalis Lamarck) mediated bioturbation and biodeposition on some ecological factors of a freshwater lake

The biotic potential of the benthic filter feeding freshwater bivalve mollusc Lamellidens marginalis (Lamarck) influencing the nutrient dynamics of the bottom sediments of the lake by means of biodeposition and bioturbation activities were analysed using a lake mesocosm experiment. Five control as well as experimental mesocosms was maintained up to 60 days (d). The factors studied included the percentage of water content of the sediment, percentage of total nitrogen, percentage of organic matter along with the total phosphorus and humic acid content. While total phosphorus and humic acid content of the experimental mesocosoms showed gradual and significant increases from 30d of the experiment to reach the maximum levels after 60d, the percentage of organic matter registered significant increases right from 15d onwards and reached the maximum values after 60d. On the other hand, while the percentage of water content of the sediments of the experimental mesocosoms increased only up to 30d experiment, percentage of nitrogen was increased during the first half and at the fag end of the experiment. All the investigated ecological factors were found to be significantly influenced by the presence of L. marginalis in the experimental mesocosms. The study indicated that the mussel influence the nutrient dynamics of the inhabitant ecosystem through the processes of excretion, biodeposition of pseudofaeces and faeces, along with the bioturbation of the sediments brought about by their ploughing movements. KEYWORDS: freshwater mussel, Lamellidens marginalis, bioturbation, biodeposition, mesocosms.
A variable mineralization time and solution concentration intervene in the microstructure of biomimetic mineralized collagen and potential osteogenic microenvironment

The absence of a conducive bone formation microenvironment between fractured ends poses a significant challenge in repairing large bone defects. A promising solution is to construct a bone formation microenvironment that mimics natural bone tissue. Biomimetic mineralized collagen possesses a chemical composition and microstructure highly similar to the natural bone matrix, making it an ideal biomimetic bone substitute material. The microstructure of biomimetic mineralized collagen is influenced by various factors, and its biomineralization and microstructure, in turn, affect its physicochemical properties and biological activity. We aimed to utilize mineralization time and solution concentration as variables and employed the polymer-induced liquid precursor strategy to fabricate mineralized collagen with diverse microstructures, to shed light on how mineralization parameters impact the material microstructure and physicochemical properties. We also investigated the influence of microstructure and physicochemical properties on cell biocompatibility and the bone-forming microenvironment. Through comprehensive characterization, we examined the physical and chemical properties of I-EMC under various mineralization conditions and assessed the in vitro and in vivo biocompatibility and osteogenic performance. By investigating the relationship between mineralization parameters, material physicochemical properties, and osteogenic performance, we revealed how microstructures influence cellular behaviors like biocompatibility and osteogenic microenvironment. Encouragingly, mineralization solutions with varying concentrations, stabilized by polyacrylic acid, successfully produced intrafibrillar and extrafibrillar mineralized collagen. Compared to non-mineralized collagen, all mineralized samples demonstrated improved bone-forming performance. Notably, samples prepared with a 1× mineralization solution exhibited relatively smooth surfaces with even mineralization. Extending the mineralization time enhanced the degree of mineralization and osteogenic performance. Conversely, samples prepared with a 2× mineralization solution had rough surfaces with large calcium phosphate particles, indicating non-uniform mineralization. Overall, our research advances the potential for commercial production of mineralized collagen protein products, characterized by dual biomimetic properties, and their application in treating various types of bone defects.
Parallelization of Recurrent Neural Network-Based Equalizer for Coherent Optical Systems via Knowledge Distillation

The recurrent neural network (RNN)-based equalizers, especially the bidirectional long-short-term memory (biLSTM) structure, have already been proven to outperform the feed-forward NNs in nonlinear mitigation in coherent optical systems. However, the recurrent connections still prevent the computation from being fully parallelizable. To circumvent the non-parallelizability of recurrent-based equalizers, we propose, for the first time, knowledge distillation (KD) to recast the biLSTM into a parallelizable feed-forward 1D-convolutional NN structure. In this work, we applied KD to the cross-architecture regression problem, which is still in its infancy. We highlight how the KD helps the student's learning from the teacher in the regression problem. Additionally, we provide a comparative study of the performance of the NN-based equalizers for both the teacher and the students with different NN architectures. The performance comparison was carried out in terms of the Q-factor, inference speed, and computational complexity. The equalization performance was evaluated using both simulated and experimental data. The 1D-CNN outperformed other NN types as a student model with respect to the Q-factor. The proposed 1D-CNN showed a significant reduction in the inference time compared to the biLSTM while maintaining comparable performance in the experimental data and experiencing only a slight degradation in the Q-factor in the simulated data.