Miracle-dz/UniFAR-FTUs huggingface dataset:
The Mosaic Legacy of Sigmund Freud: How to Read Moses and Monotheism in the Twenty-First Century. On Gilad Sharvit and Karen S. Feldman (eds), Freud and Monotheism: Moses and the Violent Origins of Religion

Sigmund Freud, faced with the coming to power of Hitler in 1933, the burning of his books in Berlin, the 1938 Anschluss, followed by his exile to London for just one year before he died, worked throughout the 1930s on his last controversial thesis: the biblical Moses, the founder of the Jewish people, was actually an Egyptian prince, he argued. Published in 1939, Moses and Monotheism, an ‘infamously unedited text’ (2018, p. 116), as one contributor to this volume describes it, presents the quite unfounded hypothesis that, as a prince, Moses served under the proto-monotheistic Egyptian pharaoh, Akhenaten. When the latter’s regime fell, Moses joined the marginalized Israelite people and imposed his proto-monotheistic views for creating what eventually would be known as the Jewish people. In line with his earlier work Totem and Taboo, Freud suggested that the new monotheistic religion was so prohibitive that the Israelite people decided to murder their founding father, Moses, in order to allow themselves a more permissive pleasure principle than the one that was offered to them by him. But a period of ‘latency’ – so central to Freudian developmental theory – can also play a role in the life of nations: the ‘returned of the repressed’, in the case of the people of Israel, was the emergence of a new Moses, this time to impose monotheism
Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method

: Protein can be classified in different classes. A lot of research is being performed for analyzing the structure and classes of protein. There are many problems associated with protein structure. Some of them are folding problem and protein structure prediction (PSP) etc. PSP is the most considerable open problem in field of biology. In the present work different algorithms like particle swarm optimization (PSO), gravitational search algorithm (GSA) and K-Mean clustering algorithms are used to classify different structures of protein. A random forest (RF) classifier is proposed for analyzing and comparing different protein classes in terms of other conventionally available algorithms in terms of various performance parameters like accuracy, recall, precision and specificity. The proposed classifier proved better than other classifiers in terms of accuracy and can be helpful in predicting the protein structures. A hybrid PSO-GSA algorithm is also proposed which provided improved performance as compared to single algorithms and can be utilized for analysis of protein structure.
Monolayer MoS2 on sapphire: an azimuthal reflection high-energy electron diffraction perspective

Molybdenum disulfide (MoS2) on the c-plane sapphire has been a very popular system to study in the two-dimensional (2D) materials community. Bottom-up synthesis of monolayer (ML) MoS2 with excellent electrical properties has been achieved on sapphire by various methods, making it a very promising candidate to be used in the next generation nano-electronic devices. However, large-area ML MoS2 with comparable quality as the relatively small size exfoliated ML remains quite a challenge. To overcome this bottle neck, a comprehensive understanding of the structure of the as-grown ML material is an essential first step. Here, we report a detailed structural characterization of wafer-scale continuous epitaxial ML MoS2 grown by metalorganic chemical vapor deposition on sapphire using an azimuthal reflection high-energy electron diffraction (ARHEED) technique. With ARHEED we can map not only 2D but also 3D reciprocal space structure of the ML statistically. From the oscillation in the ARHEED intensity profile along the vertical direction of the ML, we derived a real space distance of ~3 Å at the interface of ML and sapphire. Quantitative diffraction spot broadening analyses of the 3D reciprocal space map reveals low density defects and a small angular misalignment of orientation domains in ML MoS2. Based on atomic force microscopy height distribution analysis, cross-section scanning transmission electron microscopy, and density functional theory calculations, we suggest that there exists a passivation layer between MoS2 ML and sapphire substrate. This ARHEED methodology also has been applied to ML WS2 and is expected to be applicable to other ML transition metal dichalcogenides on arbitrary crystalline or non-crystalline substrates.
Pine wilt disease spreading prevention system using semantic segmentation

Pine wilt disease is a disease that affects ecosystems by rapidly killing trees in a short period of time due to the close interaction between three factors such as trees, mediates, and pathogens. There is no 100% mortality infectious forest pests. According to the Korea Forest Service survey, as of April 2019, the damage of pine re-nematode disease was about 490,000 dead trees in 117 cities, counties and wards across the country. It's a fatal condition. In order to prevent this problem, this paper proposes a system that detects dead trees, early infection trees, and the like, using deep learning-based semantic segmentation. In addition, drones were used to photograph the area of the forest, and a separate pixel segmentation label could be used to identify three levels of transmission information: Suspicion, attention, and confirmation. This allows the user to grasp information such as area, location, and alarm to prevent the spread of re-nematode disease.
Clinical Experience of Granulocyte Transfusion Therapy in Pediatric Patients for Management of Neutropenia-related Infections in a Tertiary Care Center in India

A bstrAct Introduction: In neutropenic patients bacterial and fungal infections are a major cause of morbidity and mortality, especially in hematological malignancies and post-hematopoietic stem cell transplantation. We present here a single institution experience with the use of granulocyte transfusions in children with severe neutropenic sepsis. Material and methods: This is a retrospective analysis of 48 children who received a total of 120 granulocyte transfusions following mobilization with colony-stimulating growth factor (G-CSF) and dexamethasone. Results: Favorable response was seen in 41.6% of the children without any major adverse effects in donor or recipient. Conclusion and clinical significance: Granulocyte transfusions hence may be a useful adjunct to antimicrobials and growth factors in neutropenic sepsis refractory to conventional antimicrobials.
Infrared Spectroscopy with an Atomic Force Microscope

An atomic force microscope (AFM) has been used to measure the modulated photothermal displacement of a surface, thus acting as a local detector. This was demonstrated with Fourier transform infrared (FT-IR) and filter spectrometers focused on various samples. Similarly, surface layers were removed by an AFM and analyzed by the photothermal deformation of the coated cantilever. This work shows that the AFM can function as both an infrared detector and a precise surface separation device for spectroscopic analysis. The AFM combined with an FT-IR has the potential to enhance the sensitivity, selectivity, and spatial resolution of infrared spectroscopy.
Rotating and charged Gauss–Bonnet BTZ black holes

We obtain charged and rotating black hole solutions to the novel 3D Gauss–Bonnet theory of gravity recently proposed, both of which generalize the Banados–Teitelboim–Zanelli (BTZ) metric. The charged solutions are obtained in the Maxwell and Born–Infeld theories and feature ‘universal thermodynamics’—identical to the thermodynamics of their Einstein cousins. The rotating Gauss–Bonnet BTZ black holes are quite exceptional and are not of constant curvature. They possess an ergoregion and outer horizon, but do not have an inner horizon. We present their basic properties and show that they break the universality of thermodynamics present for their static charged counterparts. Extending our considerations to higher dimensions, we also obtain novel 4D Gauss–Bonnet rotating black strings.
Aplicação de adsorção para remover amônia de efluentes suinícolas pré-tratados

+that remains in effluents from swine facilities which were submitted to physico-chemical and biological treatments. Experiments were made in batch made adding 5% (w/w) of adsorbent (0.6-1.3 and 3.0-8.0 mm) to synthetic and real swine facilities effluents. The results show that ammonium removal is influenced by adsorbent particle size and the presence of other ions in the effluent. The adsorption equilibrium was described by Langmuir as well as Freundlich isotherms and the kinetic data fitted well a pseudo-second order model.
Total ammonia and N2O emission characteristics from Alcaligenes sp. LS2T cultures and its application on laying hen manure associated with different pH conditions

: The main objective of this research was to investigate the Alcaligenes sp. LS2T characteristics in total ammonia and N 2 O emission under different carbon sources and C/N ratios in the synthetic media. Observation of the strain application potential to suppress ammonia emission was also performed on laying hen manure with different initial pH conditions. The total ammonia concentration was observed by Nessler’s reagent photometry method followed by Lide and Frederikse equation, while the N 2 O emission was measured by gas chromatography. The result showed that the least total ammonia concentration (12.77 ± 2.61 ppm) was seen in acetate C/N 28 medium. The highest N 2 O emission was seen in citrate C/N 14 medium, which emitted 377.13 ± 20.11 ppb N 2 O. The least emitted ammonia in the manure media was seen in an acid medium (116.92 ± 8.34 ppm ammonia). The results showed the Alcaligenes sp. LS2T capabilities to remove ammonia under aerobic condition.
A Deep Reinforcement Learning Approach for Active SLAM

In this paper, we formulate the active SLAM paradigm in terms of model-free Deep Reinforcement Learning, embedding the traditional utility functions based on the Theory of Optimal Experimental Design in rewards, and therefore relaxing the intensive computations of classical approaches. We validate such formulation in a complex simulation environment, using a state-of-the-art deep Q-learning architecture with laser measurements as network inputs. Trained agents become capable not only to learn a policy to navigate and explore in the absence of an environment model but also to transfer their knowledge to previously unseen maps, which is a key requirement in robotic exploration.
A Contrarian View

Contact: fayw@missouri.edu 3-Hydroxy-3-methyl-glutarylCoA reductase inhibitors, or statins, are a mainstay in the treatment of patients with established coronary artery disease (CAD) because of their proven effi cacy in reducing cardiovascular death, myocardial infarction, and coronary revascularization procedures in this patient population. Statin therapy has also proven successful in the primary prevention of CAD. However, the absolute reduction in cardiovascular events is lower in primary prevention than in secondary prevention trials, and many of the primary prevention trials enrolled a significant number of patients with established cardiovascular disease and/or other high-risk features, such as diabetes mellitus. For these reasons we do not recommend widespread treatment of the general adult population with a statin. Rather, we advocate a strategy which involves collection of standard clinical data and the use of validated risk-prediction tools to stratify patient risk and limit initiation of a statin to those who are more likely to benefit from such therapy.
High-temperature annealing of AlN films grown on 4H–SiC

The effect of high-temperature annealing (HTA) at 1700 °C on AlN films grown on 4H–SiC substrates by metalorganic vapor phase epitaxy has been studied. It is shown that the structural quality of the AlN layers improves significantly after HTA similar to what has been demonstrated for AlN grown on sapphire. Dislocation densities reduce by one order of magnitude resulting in 8 × 108 cm−2 for a-type and 1 × 108 cm−2 for c-type dislocations. The high-temperature treatment removes pits from the surface by dissolving nanotubes and dislocations in the material. XRD measurements prove that the residual strain in AlN/4H–SiC is further relaxed after annealing. AlN films grown at higher temperature resulting in a lower as-grown defect density show only a marginal reduction in dislocation density after annealing. Secondary ion mass spectrometry investigation of impurity concentrations reveals an increase of Si after HTA probably due to in-diffusion from the SiC substrate. However, C concentration reduces considerably with HTA that points to an efficient carbon removal process (i.e., CO formation).
Potential of Selected Indian Herbs for COVID-19

Many environmental risk factors are associated with some form of chronic inflammation. The spread of COVID-19 across the world has impacted every one of us. The first case of coronavirus was reported on 30 January 2020 in India originating from China. India has a tremendous capacity to deal with the coronavirus outbreak because of its high immunity and climatic conditions. Maintaining social distancing and hand washing is not a sufficient step for preventing COVID-19. Indian system of traditional medicine has a potential worth to enhance immunity, which can resist a novel coronavirus. A detailed study was carried out by analyzing national and international scientific databases (PubMed, SciFinder, ScienceDirect, Scopus, and Web of Science, Mendeley), thesis, and recognized books. Only Indian herbs with high immunity resistant power were analyzed. Epidemiologic studies with information on COVID-19 risk factors and precautions also considered for study purposes. Some herbs like Ocimum tenuiflorum (Tulsi), Glycyrrhiza glabra (Liquorice), Curcuma domestica Vahl (Turmeric), Tinospora cordifolia (Giloy), Withania somnifera (Ashwagandha), Cinnamon (Dalchini), Shoot of Triticumaestivum Linn. (Wheatgrass), Andrographis paniculata (Kalmegh), can help in boosting immunity for COVID-19 disease. Despite the shreds of evidence for the efficacy of these herbs in treating coronavirus induced infections; the proper dose with ideal timing for such interventions needs to verify in clinical trials. Researchers must have to take the privilege to explore the potential of herbs to reduce such epidemics of environmental threats.
Letter to the editor: updated toxicological profile for mercury

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Nitrogen-doped carbon nanotubes derived from Zn–Fe-ZIF nanospheres and their application as efficient oxygen reduction electrocatalysts with in situ generated iron species

Nitrogen-doped carbon nanotubes (NCNTs) have been successfully synthesized via the direct solid pyrolysis of Zn–Fe-ZIF and the N content, N doped state, diameter and formation temperature of the NCNTs can be finely tuned by mixing Zn–Fe-ZIF with proper amounts of dicyandiamide (DCDA). DCDA serves as the extra nitrogen supplier and favors the formation of NCNTs at relatively low temperature due to its inducing effect for graphitic structure. The synthesized NCNTs, with iron species and high amounts of graphitic N, exhibit higher catalytic activity than commercial Pt/C as oxygen reduction electrocatalysts in alkaline solution.
The relationship among repeated sprint and change of direction abilities in football players with cerebral palsy

This study aimed to describe and determine relationships between repeated sprint and change of direction abilities in football players with cerebral palsy according to four sport classes (FT5 to FT8). Seventeen male football players with cerebral palsy took part in this study (23.0±4.7 years, 65.9±9.5 kg, 168.8±5.9 cm). The repeated sprint ability (6×40-m sprints with a 20-second recovery) was evaluated to determine the best sprint time, mean sprint time, and percentage of sprint decrement. The difference in lactate concentration was determined using blood samples taken three minutes before and after testing. The Illinois Agility Test (IAT) was also used to assess players’ change of direction ability. The FT8 players had better performance (p<.01) in the best sprint time, mean sprint time and in the IAT scores compared to the players of the sport classes FT5/6. Players of the sport class FT7 also reached higher performance in the IAT compared to the players of the sport classes FT5/6 (p<.05). A significant correlation was found between the best sprint time and mean sprint time (r=.94, p<.01), the best sprint time and the IAT (r=.62, p<.01), and between the best sprint time and the difference in lactate concentration (r=-.51, p<.05). The relationships between repeated sprint and change of direction abilities demonstrate the performance profile of para-footballers with cerebral palsy in those variables according to their sport classes, exhibiting lower performance than the values reported for regular football players.Keywords: physical performance, para-sport, brain impairment, Paralympic sport
Green’s problem on additive complements of the squares

Let A and B be two subsets of the nonnegative integers. We call A and B additive complements if all sufficiently large integers n can be written as a +b, where a ∈ A and b ∈ B . Let S = {12,22,32, · · ·} be the set of all square numbers. Ben Green was interested in the additive complement of S. He asked whether there is an additive complement B = {bn }n=1 ⊆Nwhich satisfies bn = π 2 16 n 2+o(n2). Recently, Chen and Fang proved that if B is such an additive complement, then limsup n→∞ π2 16 n 2 −bn n1/2 logn ≥ √ 2 π 1 log4 . They further conjectured that limsup n→∞ π2 16 n 2 −bn n1/2 logn =+∞. In this paper, we confirm this conjecture by giving a much more stronger result, i.e., limsup n→∞ π2 16 n 2 −bn n ≥ π 4 . 2020 Mathematics Subject Classification. 11B13, 11B75. Manuscript received 3rd August 2020, revised 19th August 2020, accepted 20th August 2020.
A Conceptual Cyber-Risk Assessment of Port Infastructure

Cyber-security is a growing issue globally; however, increasing concerns are being directed at ports, as they are a hub for multiple transport operations. Ransomware has shown its potential effects in recent events, infecting logistic infrastructure at Maersk and United States of America oil pipelines. As a part of a European Union Project called Cyber-MAR, researchers have been given data from several ports on their facilities’ cyber-environment. The main goal is to raise awareness of cyber-risks in ports and potential mitigations with the novel application of a dynamic risk assessment tool (Maritime Cyber Risk Assessment or MaCRA) to ports. MaCRA methodology uses a dynamic risk model to analyse maritime risks specifically, as cyber-attacks on ships and at the ports can have hard implications in both the cyber and real world. This paper uses generalised port data to create a preliminary, conceptual cyber risk assessment of ports, to raise awareness by building general risk profiles without revealing real port vulnerabilities. From this risk assessment, the authors expect to find several high-level cyber-risks that ports may need to address, as well as some scenarios that could increase or decrease those risks. This research’s limitation is the availability of data, which is somewhat mitigated by Cyber-MAR port partners. The main goal is to raise awareness of cyber-risks in ports and potential mitigation measures with the novel application of a dynamic risk assessment tool (MaCRA) to ports. This also provides a basis for further research in Cyber-MAR, as the authors will be using simulation and more real-world data to enhance the findings in this conceptual paper.