Miracle-dz/UniFAR-FTUs huggingface dataset:
EightyDVec: a method for protein sequence similarity analysis using physicochemical properties of amino acids

ABSTRACT Similarity analysis of protein sequences can expose the evolutionary relationship among them. It is required to design effective computational algorithms that can compare the similarities among the colossal amount of sequences. Alignment-based approaches to this problem are often computationally expensive, especially when the number of sequences is large. This research aims to develop an efficient alignment-free tool in the field of protein sequence comparison and phylogenetic study. The proposed method, namely EightyDVec, performs a feature generation process based on the physiochemical properties of amino acids that best describe the evolutionary relationship among the species in a protein family. Using EightyDVec, protein sequences are transformed into 80-dimensional feature vectors and the comparisons between sequences are performed conveniently through these vectors. Four different datasets are used to validate the accuracy of EightyDVec, and the obtained results have shown the great effectiveness of the proposed method in the similarity analysis of protein sequences.
Plasmacytoid Dendritic Cells Facilitate Th Cell Cytokine Responses throughout Schistosoma mansoni Infection

Plasmacytoid dendritic cells (pDCs) are potent producers of type I IFN (IFN-I) during viral infection and respond to IFN-I in a positive feedback loop that promotes their function. IFN-I shapes dendritic cell responses during helminth infection, impacting their ability to support Th2 responses. However, the role of pDCs in type 2 inflammation is unclear. Previous studies have shown that pDCs are dispensable for hepatic or splenic Th2 responses during the early stages of murine infection with the trematode Schistosoma mansoni at the onset of parasite egg laying. However, during S. mansoni infection, an ongoing Th2 response against mature parasite eggs is required to protect the liver and intestine from acute damage and how pDCs participate in immune responses to eggs and adult worms in various tissues beyond acute infection remains unclear. We now show that pDCs are required for optimal Th2 cytokine production in response to S. mansoni eggs in the intestinal-draining mesenteric lymph nodes throughout infection and for egg-specific IFN-γ at later time points of infection. Further, pDC depletion at chronic stages of infection led to increased hepatic and splenic pathology as well as abrogated Th2 cell cytokine production and activation in the liver. In vitro, mesenteric lymph node pDCs supported Th2 cell responses from infection-experienced CD4+ T cells, a process dependent on pDC IFN-I responsiveness, yet independent of Ag. Together, these data highlight a previously unappreciated role for pDCs and IFN-I in maintaining and reinforcing type 2 immunity in the lymph nodes and inflamed tissue during helminth infection.
The Complex Love Numbers of Long‐Period Zonal Tides Retrieved From Global GPS Displacements: Applications for Determining Mantle Anelasticity

Long‐period zonal tidal Love numbers are more sensitive to lower‐mantle anelasticity (which is difficult to determine even from laboratory); however, the Love numbers of the zonal tides have not been adequately determined. In this study, we use the optimal sequence estimation method with the Global Positioning System (GPS) displacements to estimate the complex Love numbers of the long‐period zonal tides. For the first time, we retrieve the complex Love numbers h20 and l20 for the Msm, Msf, SN, Mstm, Mtm, Msqm, and Mqm tides from the Up‐ and North‐components of the global GPS displacements; we also re‐estimate the same complex Love numbers for the Mm (monthly) and Mf (fortnightly) tides with a higher precision. Based on the robust estimated h20 and l20 values for the nine zonal tides, we inverse their corresponding mantle anelastic parameters fr and fi, respectively. We finally obtain that the material‐dependent parameter α for the lower mantle is 0.189 ± 0.07, and find that the 18.6‐year nodal tide and the Chandler wobble, as well as the long‐period zonal tides, can be represented by a single absorption band. Our estimates for fr, fi, and α can be further used to construct attenuation and velocity models of the Earth's interior.
The Politicization of European Union Trade Policy: Radical-Left Euroskeptic Opposition to the Transatlantic Trade and Investment Partnership

This study aims to analyze the correlation between radical-left Euroskeptic (RLE) activity and European Union (EU) trade policy by focusing on the Transatlantic Trade and Investment Partnership (TTIP). At the beginning of TTIP negotiations, the agreement was not high on political agendas and was not a major concern within European society. Thus, its salience was low. This initial lack of interest stemmed from the fact that the TTIP, as an economic and technical issue, did not draw public attention. This study shows that RLEs profoundly affected public opinion on the TTIP by increasing its salience during the European parliamentary elections in 2014 in France and Germany. Second, RLEs involved social actors and non-governmental organizations in anti-TTIP campaigns and channeled European anxieties into the STOP TTIP European Citizens’ Initiative. Third, RLEs used this proposed agreement between the EU and the United States to increase polarization within European society and ideological cleavages within the European Parliament. Finally, we can assume that an anti-TTIP campaign promoted by radical-right Euroskeptics would have had different drivers. Thus, my findings have implications for understanding the correlation between RLE activity and the politicization of EU trade policy, and they suggest some avenues for future research.
Severe equestrian injuries: A seven-year review of admissions to a UK major trauma centre

Background Equestrian sports are regaining popularity in the United Kingdom. Due to horses’ considerable weight and speed, serious injuries can occur. Riding style and equipment differ between North America and the United Kingdom with previous studies focusing on the former. Objective This study aims to assess the pattern of horse-related injury admissions to a major trauma centre in the United Kingdom. Methods A retrospective study of our hospital’s trauma registry between years 2012 and 2020 was performed. Cases included those admitted for severe horse-related injuries (irrespective of age/sex) with Injury Severity Score (ISS) of ≥ 4. Demographics, injury characteristics (ISS, Glasgow Coma Scale (GCS), injury region and operations), hospital stay and Glasgow Outcome Scale (GOS) on discharge were extracted. Four groups were formed based on mechanism of injury: fall from horse, fall and horse landing on top (FL group), kicked, and fall and kicked (FK group). Comparisons in injury and outcomes were analysed between these groups. Results 301 (2.8%) eligible cases were identified from 10,911 cases. 70.8% were female with mean (± SD) age of 42.7 (± 16.5) years. Most common mechanism of injury was fall (72.8%) then kicked (14.6%) with groups FL and FK forming < 10% each. No significant difference was found between the groups initial GCS, ISS, total or ICU length of stay and GOS (p > 0.05). Most common regions of injury were orthopaedic (41.9%), spinal (26.2%), thoracic (20.1%) and head injuries (19.3%). 75% had good recovery on GOS though there were 3 fatalities relating to severe traumatic brain injury. Conclusion Orthopaedic limb injuries form the majority of horse-related injuries which contrasts the 1970s where head injury prevailed which is likely due to the widespread use of better head protection. Consideration should be given to enhanced limb safety equipment to prevent injury.
Comparison of Statistical and Quantum Numerical Methodology for Solving Energy and Momentum Equation

Statistical and Quantum numerical method are implemented in this study to solve various cases in partial differential equations (PDEs). One -dimensional with two lattices arrangements as well as two-dimensional with nine lattices arrangements are employed. The stability and the accuracy have been investigated either using statistical technique or using Euler’s method. The numerical limitations of using LBM method have been obtained and compared with those obtained by Euler’s method finite difference method. The main goal of this study is to investigate the ability of a statistical method in solving various ODEs or PDEs in energy and momentum equations and comparing them with those obtained by a classical numerical technique. The results show the ability of the statistical method for solving ODEs and PDE’s with more stable and accurate results. Consequently, statistical technique is a powerful and promising numerical technique for scientists who are struggling for solving ODEs or PDEs. The next study will be extended to cover upwind scheme technique.
Assessing Tree Drought Resistance and Climate-Growth Relationships under Different Tree Age Classes in a Pinus nigra Arn. ssp. salzmannii Forest

The magnitude of drought impact in forest ecosystems depends on which group of trees are more severely affected; greater mortality of smaller trees can modulate the trajectories of succession, while the mortality of larger trees can disproportionately offset the ecosystem’s carbon balance. Several studies have documented a greater vulnerability of large trees to extreme droughts while some other studies reported a greater growth reduction in smaller trees during droughts. We tested these hypotheses by comparing tree basal area increment (BAI), drought resistance (i.e., magnitude of growth decline during drought), and resilience (i.e., magnitude of growth recovery after drought) across five different age-classes in black pine (Pinus nigra Arn. ssp. salzmannii) forests in Spain. Our results showed that the BAI patterns, drought resistance, and resilience were strongly influenced by tree age-classes. In addition, the effect of climatic water balance (precipitation minus potential evapotranspiration) on BAI significantly varied among age-classes. The effect of water balance on BAI was lower for younger age-classes (1–39 years of age) compared to older age-classes. We observed a greater growth reduction (i.e., lower resistance) in older trees (>40 years of age) during droughts compared to younger trees (<40 years of age). However, all trees, irrespective of their ages, were able to recover the growth rates after the drought. In general, younger trees showed a greater capacity in recovering the growth rate (i.e., more resilient) than older trees. We detected no significant effects of stand basal area and stand density on BAI, drought resistance, and resilience. Overall, our results indicated that growth of older trees was more negatively affected during drought. Therefore, these older/larger trees can be selected for commercial thinning, or can be released from competition, which can minimize the potential impacts of future droughts in black pine forests in Spain.
Encoding In Social Context Enhances And Biases Long-Term Recognition Memory: Behavioral And Electrophysiological Evidence

Encoding often occurs in social contexts, yet research has hardly addressed their role in verbal memory. In three experiments, we investigated the behavioral and neural effects of encoding context on memory for positive, negative, and neutral adjectives, contrasting a social-feedback group (N=24) with an explicit verbal-learning (N=24) and a levels-of-processing group (N=24). Participants in the social-feedback group were not aware of a recognition session one week later, but their memory was better than the explicit learning or the levels-of-processing groups’. However, they also exhibited the strongest response bias, particularly for positive words. Brain event-related potentials (ERPs) revealed largest early negativities (EPN) and late positivities (LPP) in the social-feedback group. Only in the subsequent slow-wave did the explicit learning group show higher amplitudes than the other two groups, suggesting reliance on strategic rather than automatic processes. Still, context-driven incidental encoding outweighed explicit instructions, specifying a decisive role of social factors in memory.
Water-Active Titanium/Molybdenum/Mixed-Oxides: Removal Efficiency of Organic Water Pollutants by Adsorption and Photocatalysis and Toxicity Assessment

A new titanium/molybdenum/mixed-oxides (TMO) contact-type heterojunction photocatalyst was prepared by a simple, low-cost, and environmentally-friendly mixing-calcination solid-state method. A microstructural investigation by scanning electron microscopy (SEM) showsirregularly shaped agglomerated morphology of TMO that consists of firmly connected globular TiO2 and rod-like MoO3 particles. The detailed structure and optical bandgap investigation by X-ray diffraction, Raman, and UV-Vis spectroscopy revealed the TMO’s composition of ~37 wt. % rutile TiO2, ~25 wt. % of anatase TiO2, and ~38 wt. % of molybdite MoO3 phase and an absorption threshold of around 380 nm, which implies more probability of desirable higher visible light absorption. The removal efficiency of pesticides quinmerac (QUI) and tembotrione (TEM), and pharmaceuticals metoprolol (MET), amitriptyline (AMI), ciprofloxacin (CIP),and ceftriaxone (CEF) from water in the presence of starting pure TiO2, MoO3, and prepared TMO were investigated under different pH values and UV irradiation/simulated sunlight (SS). Each starting metal-oxide precursors and prepared TMO showed a different affinity for adsorption of tested pesticides and pharmaceuticals, and, in general, better photocatalytic degradation efficiency under UV irradiation than under simulated sunlight. The highest photocatalytic degradation efficiency under UV irradiation was 81.6% for TEM using TMO; using TiO2 was 65.0% for AMI, and using MoO3 was 79.3% for CEF after 135 min. However, TMO showed a very high synergic adsorption/photocatalytic under-SS efficiency in the removal of CIP of almost 80% and under UV irradiation of 90% CIP removal after 75 min. The toxicity of catalysts, starting compounds, and their intermediates formed during the removal process was assessed using a rat hepatoma cell line (H-4-II-E). The highest hepatotoxic effects were obtained by using UV irradiated QUI and MET suspension with TMO for up to 60 min.
Alphavirus-driven Interferon Gamma (IFNg) Expression Inhibits Tumour Growth in Orthotopic 4T1 Breast Cancer Model

Interferon gamma (IFNg) is a pleiotropic cytokine that can potentially reprogramme the tumour microenvironment. However, the antitumour immunomodulatory properties of IFNg still need to be validated due to variable therapeutic outcomes in preclinical and clinical studies. We developed a replication-deficient Semliki Forest virus vector expressing IFNg (SFV/IFNg) and evaluated its immunomodulatory antitumour potential in vitro in a model of 3D spheroids and in vivo in immunocompetent 4T1 mouse breast cancer model. We demonstrated that SFV-derived IFN-g stimulated bone marrow macrophages to acquire the tumoricidal M1 phenotype in 3D nonattached conditions. Coculturing SFV/IFNg-infected 4T1 spheroids with BMDMs inhibited spheroid growth. In the orthotopic 4T1 mouse model, intratumoural administration of SFV/IFNg virus particles alone or in combination with the Pam3CSK4 TLR2/1 ligand led to significant inhibition of tumour growth compared to the administration of the control SFV/Luc virus particles. Analysis of the composition of intra-tumoural lymphoid cells isolated from tumours after SFV/IFNg treatment revealed an increase in CD4+ and CD8+ and a decrease in T-reg (CD4+/CD25+/FoxP3+) cell populations. Furthermore, a significant decrease in the populations of cells bearing myeloid cell markers CD11b, CD38 and CD206 was observed. In conclusion, the SFV/IFNg vector induces a therapeutic antitumour T-cell response and inhibits myeloid cell infiltration in treated tumours.
Warming‐Induced Northwestward Migration of the Asian Summer Monsoon in the Geological Past: Evidence From Climate Simulations and Geological Reconstructions

The cold and warm intervals during the Plio‐Pleistocene provide an opportunity to assess the response of the Asian summer monsoon (ASM) to different levels of global warming. In this study, the northern edge of the ASM, a sensitive indicator of the advance and retreat of the ASM rain belt, was analyzed using climate outputs from PMIP3 and PlioMIP1, for the Last Glacial Maximum (LGM, ∼21,000 yr BP), the preindustrial, the mid‐Holocene (∼6,000 yr BP), and the mid‐Pliocene (∼3.3–3.0 Ma), among which the global temperature increased sequentially. The results show that the northern edge of the ASM migrated northwestward by ∼200 km, ∼50 km, and ∼50 km with global warming from the LGM to preindustrial, from the preindustrial to mid‐Holocene, and from the mid‐Holocene to mid‐Pliocene, respectively. These results are generally consistent with geological records. The simulations show that the western Pacific subtropical high (WPSH) intensified and expanded geographically, and the intertropical convergence zone (ITCZ) migrated northward over the Indian Ocean and was shifted southward over the western Pacific. This led to a northwestward shift of the Asian monsoonal rain belt, and consequently to wetter conditions in India and northern China. During the mid‐Pliocene, pronounced warming substantially intensified the WPSH, leading to the suppression of moisture transport from the Indian Ocean to southern China and the Indo‐China Peninsula. Our results suggest that if the planet returns to a Pliocene warm world, precipitation will increase in northern China, while southern China and the Indo‐China Peninsula will experience more frequent droughts.
A novel mathematical modeling in shift in emotion for gauging the social influential in big data streams with hybrid sarcasm detection

Online social network is a platform that plays an essential role in identifying the emotional values of user‐generated content such as blogs, posts, and comments along with their influential factors. Especially on Twitter, network users are growing worldwide day by day and creating a massive amount of data that is not analyzed effectively in a quick way. Identifying the most influential persons on the social network is also a challenging task over the wide range of real‐time applications like recommendation systems. Now, to handle these situations, this article proposes a novel approach for prediction of information diffusion that includes emotion recognition with sarcasm detection based influence spreader identification (PID‐ERSDISI). The proposed method uses the user‐generated posts for emotion recognition in tandem with sarcasm detection both implicitly and explicitly. This approach helps to gauge the leverage that influences spreaders and also enhances the prediction accuracy of information diffusion in a better way. The implementation of the proposed work executed their task one after another in the following way, namely, sarcasm detection, emotional‐level computation, breakpoint computation, breakpoint validation, influential user generation, and information diffusion. After the successful implementation of this proposed PID‐ERSDIS, it produced prominent results against other state‐of‐art methods.
A review on applications of graphene in triboelectric nanogenerators

Nanogenerators is the growing technology that facilitates self‐powered systems, sensors, and flexible and portable electronics in the thriving era of internet of things (IoT). Since the first invention of the triboelectric nanogenerators (TENGs) in 2012, it has become one of the most important inventions in energy harvesting technologies. In this paper, a brief review on the recent progress of energy harvesting research based on TENGs technology is discussed. Basic working modes of the TENG are discussed in detail and the general procedure to synthesize, measure, and characterize a nanogenerator is presented in a direct structure. The triboelectric material choices are extremely important for TENGs since the triboelectric effects of the materials are fundamental for TENGs. The materials used as triboelectric layers are varied from polymers, metals, and inorganic materials with the commonly used materials are dielectric polymers such as PTFE, PVDF, PDMS, nylon, and Kapton. Recently, two‐dimensional (2D) materials have been widely reported as candidate materials for TENGs. Graphene, the most attractive 2D materials exhibits an excellent electrical property, great flexibility, and a high surface‐to‐volume ratio. Owing to the very low thickness of the atomic unit, a stacking graphene structure can be also made to form a very thin and miniature TENGs device. The major applications of the graphene as active materials for TENGs as a sustainable energy harvester are presented, following which structural designs and materials optimization for output performance improvement of the graphene‐based TENGs are summarized. Finally, the future directions and perspectives of the graphene‐based TENGs are outlined. The graphene‐based TENGs is not only a sustainable micro‐power source for small devices, but also serves as a potential macro‐scale generator of power from blue energy in the future.
Marsh Spot Disease and Its Causal Factor, Manganese Deficiency in Plants: A Historical and Prospective Review

This review provides an examination of the marsh spot disease in beans and the roles played by its causal factor, manganese (Mn) deficiency. The discovery of the marsh spot disease, its relation with Mn deficiency, and how it can be treated are discussed. Mn serves as a cofactor and a catalyst in various metabolic processes in different cell compartments, such as the oxygen-evolving complex of photosystem II (PSII) or reactive oxygen species scavenging. Some major quantitative trait loci (QTL) and putative candidate genes associated with Mn content in plants, especially in plant seeds, have been identified. Marsh spot disease in cranberry common bean is controlled by several major genes with significant additive and epistatic effects. They provide valuable clues for QTL candidate gene prediction and an improved understanding of the genetic mechanisms responsible for marsh spot resistance in plants.
Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method

ABSTRACT A digital transformation is currently taking place in society, where people and things are connected to each other and the Internet. The number of connected devices is projected to be 28 Billion in 2025, and our expectations on digitalization set new requirements of mobile communication technology. To handle the increased amount of connected devices and data generated, the next generation of mobile communication technology is under deployment: 5G-technology. The manufacturing industry follows the digital transformation, aiming for digitalized manufacturing with competitive and sustainable production systems. 5G-technology meets the connectivity requirements in digitalized manufacturing, with low latency, high data rates, and high reliability. Despite these technological benefits, the question remains: Why should the manufacturing industry invest in 5G-technology? This study aims to determine the impact of 5G-technology on manufacturing performance; based on a mixed-methods approach including a modified TOPSIS method to ensure robustness of the results. The results show that 5 G-technology will mainly impact productivity, maintenance performance, and flexibility. By linking 5G-technology to the performance of the manufacturing system, instead of focusing on network performance, the benefits of using 5G-technology in manufacturing become clear, and can thus facilitate investment and deployment of 5G-technology in the manufacturing industry.