Miracle-dz/UniFAR-FTUs huggingface dataset:
VEGETATION ECOLOGY OF SACRED GROVES MANAGED BY TRIBALS & NON -TRIBALS OF PASCHIM MEDINIPUR

A comprehensive ecological study of 57 sacred groves scattered over the district of Paschim Medinipur was done. A list furnishing their geographical position, approx. area, elevation and locations has been prepared. The study reveals that due to more popularity of deities of the groves, under the first group, managed by the general communities, tree vegetation is far better than the second group (managed by the tribals). All these groves experience anthropogenic disturbances and problem of land encroachment. But without better protection of these groves it is hardly expected that there will be climax formations by natural dynamics. Recovery of the climax vegetation over time could be possible if larger areas were earmarked for their growth and a network of sacred groves had been created. Since these groves are preserved mainly on religious grounds and have never been destroyed by clear felling, they represent the characteristic vegetation of each area. In 80.4% of groves managed by the non-tribals, forest spe cies are dominant whereas in the second group of groves only 72.7% are dominated by forest species. Dominant forest species include Alangium salviifolium, Shorea robusta and those of non-forest species include Ficus benghalensis Ficus religiosa etc. Both the species of Ficus are considered to be keystone species. Given the importance of sacred groves in the conservation of biodiversity and ecosystem, there is a need to take care of such sites, and attempts should be made to maintain the sanctity of these s acred groves.
Nanoscale Insights into the Mechanical Behavior of Interfacial Composite Structures between Calcium Silicate Hydrate/Calcium Hydroxide and Silica

The failure of the interfacial transition zone has been identified as the primary cause of damage and deterioration in cement-based materials. To further understand the interfacial failure mechanism, interfacial composite structures between the main hydration products of ordinary Portland cement (OPC), calcium silicate hydrate (CSH) and calcium hydroxide (Ca(OH)2), and silica (SiO2) were constructed while considering their anisotropy. Afterwards, uniaxial tensile tests were conducted using molecular dynamics (MD) simulations. Our results showed that the interfacial zones (IZs) of interfacial composite structures tended to have relatively lower densities than those of the bulk, and the anisotropy of the hydration products had almost no effect on the IZ being a low-density zone. Interfacial composite structures with different configurations exhibited diverse nanomechanical behaviors in terms of their ultimate strength, stress–strain relationship and fracture evaluation. A higher strain rate contributed to a higher ultimate strength and a more prolonged decline in the residual strength. In the interfacial composite structures, both CSH and Ca(OH)2 exhibited ruptures of the Ca-O bond as the primary atomic pair during the tensile process. The plastic damage characteristics of the interfacial composite structures during the tensile process were assessed by analyzing the normalized number of broken Ca-O bonds, which also aligned with the atomic chain break characteristics evident in the per-atom stress map.
Integrating STEM based Education for Sustainable Development (ESD) to Promote Quality Education: A Systematic Literature Review

Promoting quality education through the integration of STEM-based Education for Sustainable Development (ESD) has become a significant area of interest. Integrating STEM-based ESD can enhance the quality of education by providing interdisciplinary learning opportunities that engage students in authentic, hands-on experiences. The objective of this study is to analyze existing empirical research on the utilization of STEM-ESD in order to investigate their effectiveness in fostering quality of education. The review process involved a systematic examination of journal papers published between 2018 and 2023, using both keyword search and snowballing techniques on the Scopus database. A total of 15 journal papers were selected for inclusion in this comprehensive review. The analysis indicates that STEM-ESD program is capable in increasing student self-efficacy and student engagement, STEM-ESD learning support student’s critical thinking skills and system thinking, Implementing Local Wisdom Based ESD can increase student knowledge, STEM learning in Sustainable Food Program as an effort to increase sustainable literacy in student, ESD can increase student’s environmental awareness. In this research there are a few implications such as that STEM-ESD need to be implemented in school curriculum in order to support education that is environmentally insightful.
Biochemical compounds and structure evaluation of cocoa liquors from different origins and their derivative chocolates

Cocoa (Theobroma cacao L.) varieties have distinct characteristics that interfere with the quality of the chocolate produced. Cocoa liquors from Brazil and Peru were analyzed for bioactive compounds and physicochemical values, and dark chocolates were produced, evaluating their physical and physicochemical properties. Brazilian organic liquor showed higher phenolic content (4,403.63 mg GAE/100 g sample) and antioxidant activity (143.56 µg Trolox equivalent/g sample). Peruvian liquor cocoa butter has more palmitic acid (29.30%) and less stearic acid (32.92%), in the lower limit to oleic acid (32.92%) and the upper limit to linoleic acid (3.73%), and showed a higher content of saturated fatty acids (63.35%) and a lower content of monounsaturated acids (32.92%). Cocoa butter from organic liquor presented lower content of palmitic acid (24.01%), average stearic (34.71%) and oleic acids (35.81%), and higher content of linoleic acid (4.32%) and polyunsaturated acids (4.32%). Peruvian liquor showed higher melting point. Brazilian alkalized, organic liquors, and chocolates melting points showed no statistical difference (p > 0.05). The caramelization and carbonization points of all liquors did not show statistical differences (p > 0.05), as well as the caramelization point of all chocolates. The carbonization point was different (p < 0.05) for all chocolates. The chocolates were stable in terms of structure during storage, demonstrating the suitability for industrial production.
Cooking-Induced Oxidation and Structural Changes in Chicken Protein: Their Impact on In Vitro Gastrointestinal Digestion and Intestinal Flora Fermentation Characteristics

Meat digestion and intestinal flora fermentation characteristics are closely related to human dietary health. The present study investigated the effect of different cooking treatments, including boiling, roasting, microwaving, stir-frying, and deep-frying, on the oxidation of chicken protein as well as its structural and digestion characteristics. The results revealed that deep-fried and roasted chicken exhibited a relatively higher degree of protein oxidation, while that of boiled chicken was the lowest (p < 0.05). Both stir-frying and deep-frying led to a greater conversion of the α-helix structure of chicken protein into a β-sheet structure and resulted in lower protein gastrointestinal digestibility (p < 0.05), whereas roasted chicken exhibited moderate digestibility. Further, the impact of residual undigested chicken protein on the intestinal flora fermentation was assessed. During the fermentation process, roasted chicken generated the highest number of new intestinal flora species (49 species), exhibiting the highest Chao 1 index (356.20) and a relatively low Simpson index (0.88). Its relative abundance of Fusobacterium was the highest (33.33%), while the total production of six short-chain fatty acids was the lowest (50.76 mM). Although stir-fried and deep-fried chicken exhibited lower digestibility, their adverse impact on intestinal flora was not greater than that of roasted chicken. Therefore, roasting is the least recommended method for the daily cooking of chicken. The present work provides practical advice for choosing cooking methods for chicken in daily life, which is useful for human dietary health.
In Vitro Studies of Endophytic Bacteria Isolated from Ginger (Zingiber officinale) as Potential Plant-Growth-Promoting and Biocontrol Agents against Botrytis cinerea and Colletotrichum acutatum

Agriculture currently confronts a multitude of challenges arising from the excessive utilization of chemical pesticides and the proliferation of phytopathogenic fungi strains that exhibit resistance to commonly employed active compounds in the field. Botrytis cinerea and Colletotrichum acutatum are phytopathogenic fungi that inflict substantial economic losses within agriculture and food due to their high impacts on crops both pre- and post-harvest. Furthermore, the emergence of fungal strains that are resistant to commercial fungicides has exacerbated this problem. To explore more environmentally sustainable alternatives for the control of these pathogens, an investigation into the endophytic bacteria associated with ginger (Zingiber officinale Rosc.) was conducted. The primary focus of this study involved evaluating their inhibitory efficacy against the fungi and assessing their potential for promoting plant growth. The endophytic bacteria genera Lelliottia, Lysinibacillus, Kocuria, Agrococcus, Acinetobacter, Agrobacterium, Zymobacter, and Mycolicibacterium were identified. All isolates showed remarkable in vitro antagonistic ability against B. cinerea (>94%) and C. acutatum (>74%). Notably, the Lelliottia amnigena J29 strain exhibited a notable proficiency in producing extracellular enzymes and indole compounds (IAA), solubilizing phosphate and potassium, and forming biofilm. Furthermore, the Lysinibacillus capsici J26, Agrococcus citreus J28, and Mycolicibacterium sp. J5 strains displayed the capacity for atmospheric nitrogen fixation and siderophore production. These findings underscore the agricultural and biotechnological potential of endophytic bacteria derived from ginger plants and suggest the feasibility of developing alternative approaches to manage these two phytopathogenic fungi.
Kumano-nada 3D seismic data acquisition and processing

In the Nankai Trough off Kii Peninsula, the first scientific drilling by D/V Chikyu commenced in September 2007 as a major component of the Integrated Ocean Drilling Program (IODP), which has been an international collaborative scientific drilling program together with 22 countries since October 2003. One of its scientific challenges is to drill through the seismogenic zone to reveal the nature and mechanism of large earthquake generation. Prior to drilling, we carried out a 2D seismic survey in 2003 to identify hazards for safe and smooth drilling operation and to obtain detailed characteristics of the accretionary prism. The 2D seismic profiles, however, have some technical limitation of imaging at some targets due to the complexities of sea floor topography and sub bottom geological structures. To extend the 2D seismic results, a high resolution 3D seismic survey was conducted by M/V Nordic Explorer (PGS) in 2006. The survey area was outside shipping lanes, and fishing activities were well managed. There was, however, a strong Kuroshio Current in the southern part of the 3D survey area which significantly affected both data acquisition and data processing. The appropriate data processing including Pre-Stack Time Migration (PSTM) was carried out by CGGAP (currently CGGVeritas). To deal with the data characteristics, the processing emphasized the following three points: swell noise attenuation, multiple reflection attenuation, and handling of irregular acquisition geometry. The seismic cube, obtained as the data processing result, shows clear images of the shallow geology and most deeper targets. The Kumano-nada 3D seismic data provided information required for the scientific drilling by D/V Chikyu, and has been providing valuable information for marine science in the area.
Deep Learning Approaches with Optimum Alpha for Energy Usage Forecasting

Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of energy usage forecasting by optimizing the alpha value in exponential smoothing, thereby improving forecasting accuracy. The results showed that all DL methods experienced improved accuracy when using optimum alpha. LSTM has the most optimal MAPE, RMSE, and R2 values compared to other methods. This research promotes energy management, decision-making, and efficiency by providing an innovative framework for accurate forecasting of energy use, thus contributing to a sustainable and efficient energy system.
Research Online

Distributed lag non-linear models (DLNMs) represent a modeling framework to ﬂexibly describe associations showing potentially non-linear and delayed eﬀects in time series data. This methodology rests on the deﬁnition of a crossbasis , a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm , which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper oﬀers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.
Identification of Potential and Mitigation of Ergonomic Hazards in Stairs

Every job, even activity, has the potential for danger. Therefore, it is necessary to control hazards by looking for potential hazards that exist in work, work tools, workplaces and work environments, in order to reduce the risk of hazards occurring. Therefore, the aim of this research is to identify other Ergonomic Hazards to balance Job Demands and Worker Abilities. Occupational Safety and Health is not only carried out preventively by using Personal Protective Equipment but can be anticipated early by paying attention to design errors so that repairs, redesign or special handling are needed in an effort to reduce or even eliminate risks. This research will produce an Ergonomic Hazard List and mitigate the risk of danger to workers who are carrying out their work or people who are carrying out activities in a certain place. Not only when working, when doing activities you also need to pay attention to ergonomic dangers. Activities in public areas, including confined areas such as schools or campuses, must also pay attention to the potential ergonomic dangers involved. Of the many places to do activities, one of them is the stairs which have been identified as having the potential to be dangerous and pose a risk of injury. Therefore, a List of Potential Ergonomic Hazards on Stairs was designed.
POLD1 DEDD Motif Mutation Confers Hypermutation in Endometrial Cancer and Durable Response to Pembrolizumab

Simple Summary Germline mutations in the DNA polymerase delta 1 (POLD1) exonuclease domain cause DNA proofreading defects, tumor hypermutation, and predispose to hereditary colorectal and endometrial cancer. In this work, we used a multiprong approach to demonstrate that mutations that alter the amino acid charges in the DEDD motif of exonuclease domains could lead to proofreading deficiency. This novel mutation class, which is currently classified as a variant of uncertain significance, should be reclassified as likely pathogenic. Abstract Background: Mutations in the DNA polymerase delta 1 (POLD1) exonuclease domain cause DNA proofreading defects, hypermutation, hereditary colorectal and endometrial cancer, and are predictive of immunotherapy response. Exonuclease activity is carried out by two magnesium cations, bound to four highly conserved, negatively charged amino acids (AA) consisting of aspartic acid at amino acid position 316 (p.D316), glutamic acid at position 318 (p.E318), p.D402, and p.D515 (termed DEDD motif). Germline polymorphisms resulting in charge-discordant AA substitutions in the DEDD motif are classified as variants of uncertain significance (VUSs) by laboratories and thus would be considered clinically inactionable. We hypothesize this mutation class is clinically pathogenic. Methods: A review of clinical presentation was performed in our index patient with a POLD1(p.D402N) heterozygous proband with endometrial cancer. Implications of this mutation class were evaluated by a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review, in silico analysis with orthogonal biochemical confirmation, and whole-exome and RNA sequencing analysis of the patient’s tumor and engineered cell lines. Results: Our systematic review favored a Mendelian disease mutation class associated with endometrial and colorectal cancers. In silico analysis predicted defective protein function, confirmed by biochemical assay demonstrating loss of nuclease activity. A POLD1-specific mutational signature was found in both the patient’s tumor and POLD1(p.D402N) overexpressing cell. Furthermore, paired whole-exome/transcriptome analysis of endometrial tumor demonstrated hypermutation and T cell-inflamed gene expression profile (GEP), which are joint predictive biomarkers for pembrolizumab. Our patient showed a deep, durable response to immune checkpoint inhibitor (ICI). Conclusion: Charge-discordant AA substitution in the DEDD motif of POLD1 is detrimental to DNA proofreading and should be reclassified as likely pathogenic and possibly predictive of ICI sensitivity.
Unlocking the Key to Accelerating Convergence in the Discrete Velocity Method for Flows in the Near Continuous/Continuous Flow Regimes

How to improve the computational efficiency of flow field simulations around irregular objects in near-continuum and continuum flow regimes has always been a challenge in the aerospace re-entry process. The discrete velocity method (DVM) is a commonly used algorithm for the discretized solutions of the Boltzmann-BGK model equation. However, the discretization of both physical and molecular velocity spaces in DVM can result in significant computational costs. This paper focuses on unlocking the key to accelerate the convergence in DVM calculations, thereby reducing the computational burden. Three versions of DVM are investigated: the semi-implicit DVM (DVM-I), fully implicit DVM (DVM-II), and fully implicit DVM with an inner iteration of the macroscopic governing equation (DVM-III). In order to achieve full implicit discretization of the collision term in the Boltzmann-BGK equation, it is necessary to solve the corresponding macroscopic governing equation in DVM-II and DVM-III. In DVM-III, an inner iterative process of the macroscopic governing equation is employed between two adjacent DVM steps, enabling a more accurate prediction of the equilibrium state for the full implicit discretization of the collision term. Fortunately, the computational cost of solving the macroscopic governing equation is significantly lower than that of the Boltzmann-BGK equation. This is primarily due to the smaller number of conservative variables in the macroscopic governing equation compared to the discrete velocity distribution functions in the Boltzmann-BGK equation. Our findings demonstrate that the fully implicit discretization of the collision term in the Boltzmann-BGK equation can accelerate DVM calculations by one order of magnitude in continuum and near-continuum flow regimes. Furthermore, the introduction of the inner iteration of the macroscopic governing equation provides an additional 1–2 orders of magnitude acceleration. Such advancements hold promise in providing a computational approach for simulating flows around irregular objects in near-space environments.
Lake temperatures : thermal remote sensing and assimilation into a lake model

By assimilating space-based observations of lake surface temperatures (LSTs) into a simple lake model, a means to improve the poor representation of such lakes in weather forecasting models is demonstrated. As model resolutions increase a rapidly increasing number of lakes are now resolvable and the use of lake observations and models is required. The application of the Along Track Scanning Radiometer 2 (ATSR2) to this problem requires a method to retrieve LSTs in cloud-free conditions, validation of the retrievals, cloud and ice masking and assimilation of the observations into lake models. This work shows that data from Advanced ATSR could be used to produce a useful global LST product for assimilation into lake models within weather forecasting systems. The application of ATSR2 sea surface temperature (SST) retrieval coefficients to LST retrieval was investigated using radiative transfer modelling. These results suggest that retrieval biases should be less than 0.3 K and that large air-surface temperature differences (ASTDs) are the largest source of bias. Validation was carried out for Lake Tahoe, California. These results gave retrieval biases of 0.5 K and 0.0 K and standard deviations of 0.41 K and 0.41 K, using two and three channel dual view retrievals respectively. Applying the standard ATSR2 cloud mask to lake images can lead to systematic over-masking and so to biases in LSTs. This is mainly due to the large scale spatial coherence and thermal histogram tests, which are less applicable to lakes than oceans. These tests were removed from the lake cloud masking scheme. The daytime reflectance cloud masking was improved, by comparing 1.6 pin and 3.7 /Lm observations to discriminate between sunglint and cloud. A 1.6itm versus 0.65 jtm test was also added, which masks most snow and ice contamination during the day. Remaining cloud contamination tends to be from low cloud or fog. An algorithm designed to mask cloud by comparing observed brightness temperatures with a set of modelled values and also using new dynamic reflectance tests was also developed. This reduced the over-masking of spatially varying LSTs and large ASTDs, which can occur with the mask based on the standard ATSR2 ocean cloud mask. The results support the proposition that it is difficult to mask all fog and low cloud without large scale spatial tests. Possible methods to mask this cloud, without introducing bias, are discussed. Lake surface temperature observations were assimilated into models of four mid/high latitude lakes. An "assimilation flux" was applied at the surface, since errors in surface fluxes were estimated to frequently be the largest source of model error. The scheme was improved by basing the flux on not only the difference between the modelled and observed LSTs, but also the wind speed and thermocline depth. For the four lakes the modelled/assimilated LSTs differed from the LST climatologies used by ECMWF by between -15 K and +2 K over a year. This would be expected to have an impact on local air temperatures and maybe meteorology on the 50 km to 500 km scale.