Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Design of Slim Mould Optimizer for the Solution of Optimal Power Flow Problems Incorporating Intermittent Sources: A Case Study of Algerian Electricity Grid

Nowadays, electrical power grids are facing increased penetration of renewable energy sources (RES), which result in increasing level of randomness and uncertainties for its operational quality. In addition, emerging need for efficient solutions to stochastic optimal power flow (OPF) problem has attracted considerable attention to ensure optimal and reliable grid operations in the presence of generation uncertainty and increasing demand. Therefore, this paper proposes an efficient Slime Mould-inspired Algorithm (SMA) that aims to minimize overall operating cost of main grid by managing the power flow among different generating resources. The problem is formulated as large-scale constrained optimization problem with non-linear characteristics. Its degree of complexity increases with incorporation of intermittent energy sources, making it harder to be solved using conventional optimization techniques. However, could be efficiently resolved by nature-inspired optimization techniques without any modification or approximation into the original-formulation. The objective function is the overall cost of system, including reserve cost for over-estimation and penalty cost for under-estimation of both PV-solar and wind energy. The SMA performance is evaluated on the IEEE 30-bus test system and Algerian power system, DZA 114-bus. The SMA is compared with four optimization algorithms: i) The well-studied meta-heuristics, i.e., Gorilla troops optimizer (GTO), and Orca predation algorithm (OPA), ii) Recently developed meta-heuristics, i.e., Artificial ecosystem optimizer (AEO), Hunger games search (HGS), and Jellyfish search (JS) optimizer, iii) ad high-performance meta-heuristics, Success-History based parameter adaptation for differential evolution method. The overall simulation results reveal that the SMA ranked first among the compared algorithms, and so, over and so, over different function landscapes.
The Water Paradox: Overcoming the Global Crisis in Water Management

Israel/Palestine. Indeed, it seems as though the four preceding case studies are set up to culminate in a routine critique of Israel, which the study seems geared towards from the outset. While Nazism and Zionism are mentioned in the same sentence twice by the fourth page, suggesting a kind of performativity indicative of much anti-Zionist analysis, the Nazi and Zionist projects are diametrically opposed in their respective inherent logics. Zionism constitutes (in its secular aspects) a nationalist movement of self-preservation in the historical context of centuries of pogroms and, ultimately, Holocaust, whereas what Hannah Arendt described as the totalitarian nature of Nazism is predicated on perpetual conquest and annihilation. In the end, though, it is Mamdani’s argument about why a genuine process of decolonisation has proven elusive, but also how it might be attained (South Africa providing the hopeful, if qualified, example among the cases included in this study), that constitutes the most valuable contribution of this book. Ultimately, decolonisation does not merely require the end of colonial rule, but also an end to tribal self-determination and indigeneity (p. 249). This latter requirement might seem counterintuitive given a propensity in much of the existing literature to focus on the agency of (former) colonial powers at the expense of the (formerly) colonised. This conclusion also poses a major challenge to mainstream post-colonial scholarship, much of which has remained endeared to tribal claims to authenticity and the concept (and political agenda) of indigeneity. Thus, what Mamdani’s study demonstrates quite clearly is the resilience of the Western concept of the nation-state in post-colonial settings, and the elusiveness of decolonisation.
Event-based S-transform approach for nonintrusive load monitoring

In this study, a nonintrusive load monitoring system is developed by analyzing the power signal obtained from a single point of power meter installation to detect ON/OFF load activities. A mathematically designed model with backpropagation neural network is utilized in load pattern recognition to decompose the load operation. Leveraging its unique load signature profile, the S-transform approach is employed to extract the features from the aggregate power signal and analyze the detection of load start-up transient from signal processing. To improve the accuracy of load identification for unknown data, the power factor is used as an additive feature with 99.32% load recognition accuracy.
Structure and Trajectory Planning of A Novel Flipping Robot

A novel type of planar one legged robot was proposed. Unlike previous one legged robot with springy legs, it consists of three revolute joints, two links and two feet. A cyclic flipping gait was designed for this robot. A complete flipping gait cycle is composed of four phases: two stance phases and two flight phases. During the flight phases, the torque of the knee joint is zero, the total angular momentum with respect to the center of mass of the system is conserved, the rotational motion and translational motion are decoupled from each other. The trajectory planning of the four phases is formulized as a problem of numerical optimization subject to the nonlinear constraints such as positive reaction force of ground and finite torque of the joints. The energy injected into the robot in a gait cycle is chosen as a criterion of optimization in the simulation.
Bilingual switching practices have distinct effects on the volumes of the caudate nucleus and the thalamus

Bilingualism impacts brain structure, especially in regions involved in language control and processing. However, bilingual experiences are complex and the relation of brain structural changes to key aspects of bilingual language use are thus far poorly understood. Here we used structural MRI and non-linear correlational analysis in Czech-English bilinguals to investigate the effects of habitual code-switching practices on brain structure. We studied the effects of usage frequency of various code-switching types on the volumes of the caudate nucleus and the thalamus, two prominent subcortical structures subserving code-switching. Overall code-switching frequency was measured as well as extent of engagement in various code-switching types. These types were categorised by directionality (L1-L2 or L2-L1) and the level of separation of the two languages. Caudate volumes were positively correlated with overall code-switching frequency, irrespective of code-switching type or directionality, although stronger effects were found for L1-L2 switches. Thalamic volumes were positively correlated with engagement in forms of CS for which the two languages are kept more separate, with stronger effects observed in L2-L1 switches. This pattern of results underscores the theoretical and methodological importance of using detailed measures of bilingual experiences when investigating the sources of bilingualism-induced neuroplasticity.
Personalized Music Recommendation Algorithm Based on Spark Platform

Aiming at the shortcomings of traditional recommendation algorithms in dealing with large-scale music data, such as low accuracy and poor real-time performance, a personalized recommendation algorithm based on the Spark platform is proposed. The algorithm is based on the Spark platform. The K-means clustering model between users and music is constructed using an AFSA (artificial fish swarm algorithm) to optimize the initial centroids of K-means to improve the clustering effect. Based on the scoring relationship between users and users and users and music attributes, the collaborative filtering algorithm is applied to calculate the correlation between users to achieve accurate recommendations. Finally, the performance of the designed recommendation model is validated by deploying the recommendation model on the Spark platform using the Yahoo Music dataset and online music platform dataset. The experimental results show that the use of improved AFSA can complete the optimization of K-means clustering centroids with good clustering results; combined with the distributed fast computing capability of Spark platform with multiple nodes, the recommendation accuracy has better performance than traditional recommendation algorithms; especially when dealing with large-scale music data, the recommendation accuracy and real-time performance are higher, which meet the current demand of personalized music recommendation.
What We Can Learn About Emotion by Talking With the Hadza

Emotions are often thought of as internal mental states centering on individuals’ subjective feelings and evaluations. This understanding is consistent with studies of emotion narratives, or the descriptions people give for experienced events that they regard as emotions. Yet these studies, and contemporary psychology more generally, often rely on observations of educated Europeans and European Americans, constraining psychological theory and methods. In this article, we present observations from an inductive, qualitative analysis of interviews conducted with the Hadza, a community of small-scale hunter-gatherers in Tanzania, and juxtapose them with a set of interviews conducted with Americans from North Carolina. Although North Carolina event descriptions largely conformed to the assumptions of eurocentric psychological theory, Hadza descriptions foregrounded action and bodily sensations, the physical environment, immediate needs, and the experiences of social others. These observations suggest that subjective feelings and internal mental states may not be the organizing principle of emotion the world around. Qualitative analysis of emotion narratives from outside of a U.S. (and western) cultural context has the potential to uncover additional diversity in meaning-making, offering a descriptive foundation on which to build a more robust and inclusive science of emotion.
LncRNA HOTAIR Promotes Tumorigenicity in Glioblastoma

Background Recently, the 2021 WHO Classification of Tumors of the Central Nervous System (fifth edition) was published. WHO CNS5 incorporates numerous molecular changes to the accurate classification of CNS neoplasms. GBM, as a special type of glioma, is confined to IDH-wildtype in WHO CNS5, which has a short medical history and poor prognosis. LncRNA HOTAIR has been found to be responsible for the poor prognosis of several human cancers in previous studies. The clinical significance, the prognostic and treatment value of HOTAIR for GBM in the new WHO CNS5 classification remain unclear.Methods We created a Random Forest-based prediction model to assess the IDH1 mutational status of patients in REMBRANDT cohorts. Then we analyzed the role and the potential mechanism of HOTAIR in TCGA, CGGA, and REMBRANDT cohorts. GSVA and GSEA analysis were used to detect the potential biological functions and signaling pathways. The infiltration of immune cells was quantified by Cibersort. The effectiveness of targeted therapy in the clinical application was sought through drug response analysis. Furthermore, we verified that HOTAIR affected the proliferative activity of that glioma cells.Results We found that HOTAIR is highly expressed in all cohorts. The patients’ samples with high HOTAIR expression have poorer overall survival. The results of the functional analysis indicated that the cell cycle and proliferation-related processes were enriched in the high HOTAIR expression group. The infiltration of immunocytes is different in the two groups. In multiple immune checkpoints, the risk score showed a strong correlation. The analysis of drug treatment response present that the high HOTAIR expression group has a better treatment response and better curative effect on the treatment of temozolomide, sorafenib, lenalidomide, bexarotene, and axitinib.ConclusionIn conclusion, We found that HOTAIR could lead to poor prognosis of GBM mainly through regulation of cell cycle and apoptosis. And HOTAIR could be used as a marker to guide chemotherapy in GBM patients rather than immunocheckpoint inhibitor therapy.
Effect of Selenium-yeast on Cognitive Performance on Pregnant Dams Exposed to Noise Stress

A total of twelve pregnant Wistar rats were used, and randomly divided into three groups (n=4). Group A (negative control), not exposed to noise stress), group B (1mL/kg of distilled water + 4h /15 days noise stress), group C (0.04 mg/kg) of selenium-yeast + 4 h/15 days noise stress). On day 18 and 19 of gestation cognitive tests were conducted using Y-maze and Novel Object Recognition Test. A significant increase (P ˂ 0.05) was observed in the percentage alternation and discrimination index in group A compared with group B. However, the percentage alternation and DI were significantly (P ˂ 0.05) decreased in group C compared with group B. In conclusion, noise stress induces cognitive deficit, this deficit can be mitigated with the administration of selenium-yeast.
Research on the Application of Power Grid Based Synthetical Regional Wind Power Measurement System

Aiming at accurate assessment of wind resource in large area and high precision prediction of wind power, the necessity of synthetical regional wind power measurement system is analyzed, and the main capability of the wind power measurement and power forecast control system is presented. With the help of this system, technical guide and support can be provided for planning of regional wind power, construction of large wind power farm and reliable operation of power grid.
Squamous Cell Carcinoma of the Vulva: A Survival and Epidemiologic Study with Focus on Surgery and Radiotherapy

Vulvar squamous cell carcinoma (SCC) is the most frequent vulvar neoplasia. While the primary role of surgery is widely accepted, large population studies are needed to compare survival between diverse treatment modalities and to identify independent prognostic factors to help council patients and guide oncological treatment. The U.S. National Cancer Index, Surveillance, Epidemiology and End Results (SEER) program data between 2000 and 2018 was screened for all squamous cell carcinoma affecting the vulva. Raw data was processed with IBM SPSS. Demographic, clinical-pathological and treatment data were studied. Overall survival (OS) was calculated using the Kaplan–Meier method and subgroups were compared using the log rank test. A multivariate cox regression was conducted to identify independent prognostic factors. A total of 11,360 patients were identified with a median age of 65. Median overall survival was 101 months. Surgery as a primary treatment is the therapeutic sequence associated with the best overall survival. Multivariate cox-regression did not meet proportional hazard assumption. Age, pathological grade, stage at diagnosis, treatment sequence and the use of chemotherapy were identified as independent prognostic factor. Surgery alone is the treatment sequence offering the best overall survival. Surgery should be offered to all eligible patients.
Green Demand Aware Fog Computing: A Prediction-Based Dynamic Resource Provisioning Approach

Fog computing could potentially cause the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to the end-user. With its close proximity to end-users and its distributed nature, fog computing can significantly reduce latency. With the appearance of more and more latency-stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to an increase in the energy footprint of the network edge and access segments. To reduce energy consumption in fog computing without compromising performance, in this paper we propose the Green-Demand-Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show that our solution can save energy up to 65% without deteriorating the delay requirement performance.
Heart Rate Variability and Sympathetic Activity Is Modulated by Very Low-Calorie Ketogenic Diet

Obesity is characterized by an energy imbalance and by the accumulation of visceral adipose tissue. The energy balance is controlled by a complex set of balanced physiological systems that provide hunger and satiety signals to the brain and regulate the body’s ability to consume energy. The central nervous system controls the metabolic state, influencing the activity of other systems and receiving information from them. Heart rate variability (HRV) is the natural variability of the heart rate in response to several factors. HRV is related to the interaction between the SNS and the parasympathetic. In the light of this evidence, the aim of this study is to investigate the possible effects of the two different dietary regimens such as very low-calorie ketogenic diet (VLCKD) vs. low caloric diet (LCD), on the functions of the nervous system, with particular attention to the autonomous control of heart rate variability (HRV). A total of 26 obese subjects underwent diet therapy in order to reduce body weight; they were also randomly divided into two groups: the VLCKD group and the LCD group. Our results showed that in both groups, there is a reduction in heart rate as an indicator of sympathetic activity; we found a statistically significant variation only in the VLCKD group. Therefore, this study supports the notion that the sympathovagal balance can be modulated by a specific diet, but further studies are needed to clarify the molecular pathway undergoing this modulation.
Bacterial Transcriptional Regulators: A Road Map for Functional, Structural, and Biophysical Characterization

The different niches through which bacteria move during their life cycle require a fast response to the many environmental queues they encounter. The sensing of these stimuli and their correct response is driven primarily by transcriptional regulators. This kind of protein is involved in sensing a wide array of chemical species, a process that ultimately leads to the regulation of gene transcription. The allosteric-coupling mechanism of sensing and regulation is a central aspect of biological systems and has become an important field of research during the last decades. In this review, we summarize the state-of-the-art techniques applied to unravel these complex mechanisms. We introduce a roadmap that may serve for experimental design, depending on the answers we seek and the initial information we have about the system of study. We also provide information on databases containing available structural information on each family of transcriptional regulators. Finally, we discuss the recent results of research about the allosteric mechanisms of sensing and regulation involving many transcriptional regulators of interest, highlighting multipronged strategies and novel experimental techniques. The aim of the experiments discussed here was to provide a better understanding at a molecular level of how bacteria adapt to the different environmental threats they face.
Secondary forests as biodiversity repositories in human-modified landscapes: insights from the Neotropics

In this essay we examine some of the processes affecting the composition and structure of tree species assemblages and, consequently, what we can expect from secondary-forest stands as an element of human-modified landscapes and as an opportunity for biodiversity persistence in this ecological context. Based on the available information, it is reasonable to predict that in some landscapes or biotas: (1) small forest remnants degenerate and support plant assemblages with attributes similar to those observed in early and intermediate-aged regenerating stands, while secondary-forest stands move from initial to more advanced successional stages; (2) collectively, remnant/stand attributes and landscape integrity define the pace through which degeneration proceeds, but also the potential for regeneration; (3) at the landscape spatial scale, remnants and stands tend to converge in terms of structure, but also in terms of taxonomic and functional composition. In other words, remnants degenerate and secondary-forest stands regenerate toward a sort of ‘climax community’, which is conditioned by the physical and biological integrity of both patch and landscape. Considering secondary forests in the conceptual, ecological and spatial framework of human-modified landscapes may help us to understand and maximize the conservation services provided by this habitat as it proliferates through human-modified landscapes.
An in vitro Assay of mRNA 3' end Using the E. coli Cell-free Expression System.

At the end of about 80% of the operon in Escherichia coli, translation termination decouples transcription, leading to Rho-dependent transcription termination (RDT). However, no in vitro or in vivo assay system has proven to be good enough to see the 3' end of the mRNA generated by RDT. Here, we present a cell-free assay system that could provide detailed information on the 3' end of a transcript RNA generated by RDT. Our protocol shows how to extract transcript RNA generated by transcription reactions from a cell-free extract, followed by an RNA oligomer ligation to the 3' end of a transcript RNA of interest. The 3' end of the RNA is amplified using RT-PCR. Its genetic location can be determined using a gene-specific primer extension reaction. The 3' ends of mRNA can be visualized and quantified by polyacrylamide gel electrophoresis. One significant advantage of a cell-free assay system is that factors involved in the generation of the 3' end, such as proteins and sRNA, can be directly assayed by exogenously adding factor(s) to the reaction. Graphic abstract: An illustration of the experimental methodology.
On the Total Reflectivity Estimation of Microwave Calibration Targets by Backscattering Measurements

Before practical usage in microwave radiometers, the calibration targets must be tested for its emissivity/total reflectivity. In this work, the authors address the issue that remains in the total reflectivity determination, which is estimating the total reflectivity based on measured backscattering in the mono-static configuration, specifically at high frequencies. Based on the efficient modeling on periodic unit of the array-shaped calibration target, the authors quantitatively evaluate the relationship between backscattering and the total reflectivity, on the common structure of coated cones and coated pyramids. It is found that, the total reflectivity estimation becomes target-specific for the coated cones, meanwhile stable compensation can be concluded for the pyramidal units, which is important for practical testing in sub-millimeter applications. Then, the disturbing effects of the geometric defects on the total reflectivity estimation are discussed, and it is inferred that wide-band measurement is vital for diagnosing those defects. Furthermore, actual test results are analyzed, showing the complex scenario in estimating the total reflectivity of a prototype with shape defects. And the numerical concluded Cg compensation is verified in the clear case of a fine prototype. The findings in this work offer direct reference for the application of microwave radiometer calibration, especially in the region of sub-millimeter waves.