Miracle-dz/UniFAR-FTUs huggingface dataset:
Additive and Non-additive Biomass Equations for Black Wattle

ABSTRACT The objectives of this work were to propose additive equations for biomass components (stem and crown) and total biomass for black wattle (Acacia mearnsii De Wild.) and show the inconsistency of independently adjusted biomass equations. Two procedures were used to fit nonlinear equations of biomass: i) independent and ii) systems of equations. The second procedure, defined by the application of the seemingly unrelated regression model, has better biological and statistical properties to estimate allometric equations of biomass components and total biomass when compared with the independent estimation. An effective property of this procedure is the additivity, i.e., the estimates of component biomass are compatible with those of total biomass. Independent fitted adjusted equations do not consider the dependence between the biomass components, thus, besides the estimates being non-additive, which is an undesirable property, they will result in estimates with larger variance.
You Only Evaluate Once – a Simple Baseline Algorithm for Ofﬂine RL

The goal of ofﬂine reinforcement learning (RL) is to ﬁnd an optimal policy given prerecorded trajectories. This setup is appealing since it separates the learning process from the possibly expensive or unsafe data-gathering process. Concerning this problem, much research has been proposed that customizes existing off-policy RL algorithms, especially actor-critic algorithms in which policy evaluation and improvement are iterated. However, the convergence of such approaches is not guaranteed due to the use of complex non-linear function approximation and an intertwined optimization process. In this paper, we propose a simple baseline algorithm for ofﬂine RL that only performs the policy evaluation step once so that the algorithm does not require complex stabilization schemes. The algorithm is not likely to converge to an optimal policy, but we empirically ﬁnd that when we use proper regularization, a greedy policy implied by the learned value function exhibits competitive performance in a subset of the D4RL ofﬂine RL benchmark, and it even achieves state-of-the-art results in the hopper-medium-replay, walker2d-medium-replay, and hopper-medium datasets.
Simulation de réseaux hydrographiques. Comportements géométriques et hydrologiques

Dans ce travail nous tentons d'etudier le couplage entre precipitations et topographie a l'aide de modeles volontairement simplifies de reseaux hydrographiques. Certains comportements statistiques pourraient etre conserves dans ces simplifications, en particulier ceux relatifs aux evenements extremes. Les comparaisons sont faites entre la plus simple des topographies, et des reseaux fractals consistant en un ensemble dense de rivieres decrivant chacune une marche au hasard (brownienne) sans intersections. Des modelisations introduisant certaines proprietes de rectification locale du chevelu sont egalement utilisees. Intuitivement, une complexite croissante du chevelu doit tendre a integrer ou a lisser le comportement des debits observes (par exemple le debit maximal ou, plus physiquement, la densite de probabilite du debit). Nous tentons de verifier cette hypothese dans le cas de deux modeles extremes de precipitations: une precipitation uniforme (pluie stratiforme) et l'advection aleatoire de cellules precipitantes isolees (pluie cumuliforme).
UN THÉORÈME DE CONVEXITÉ RÉEL POUR LES APPLICATIONS MOMENT À VALEURS DANS UN GROUPE DE LIE

Dans cette note, on présente l'´ enoncé et les principales idées de la démonstration d'un théorème de convexité réel pour les applications momentà valeurs dans un groupe de Lie. Ce résultat est un analogue quasi-hamiltonien du théorème de O'Shea et Sjamaar dans le cadre hamiltonien usuel. On démontre que l'image par l'application moment du lieu des points fixes d'une involution renversant la 2-forme de structure d'un espace quasi-hamiltonien est un polytope convexe, et l'on décrit ce polytope comme sous-polytope du polytope moment. In this note, we state and give the main ideas of the proof of a real convexity theorem for group-valued momentum maps. This result is a quasi-Hamiltonian analogue of the O'Shea-Sjamaar theorem in the usual Hamiltonian setting. We prove here that the image under the momentum map of the fixed-point set of a form-reversing involution defined on a quasi-Hamiltonian space is a convex polytope, that we describe as a subpolytope of the momentum polytope.
FastRAT: Fast and Efficient Cross-lingual Text-to-SQL Semantic Parsing

Recent advances of large pre-trained language models have motivated significant break-throughs in various Text-to-SQL tasks. However, a number of challenges inhibit the deployment of SQL parsers in commercial applications. In this paper, we focus on two such challenges: decoding speed and multilingual input, and introduce FastRAT, a model that includes (i) a decoder-free framework to quickly generate SQL queries from natural language questions based on SQL Semantic Predictions, (ii) a cross-lingual multi-task pre-training scheme, and (iii) a method, based on distant supervision, to extend a semantic parser to new languages. We apply FastRAT on CSpider and Spider, two challenging zero-shot semantic parsing benchmarks. Our system achieves an average of 10 x decoding speedup over a set of competitive baselines based on auto-or semi-auto-regressive decoding. In the cross-lingual CSpi-der dataset, our approach achieves an exact query match accuracy score of 61 . 3 , outper-forming the relevant competition. In the mono-lingual task, it maintains competitive performance by exhibiting < 5% accuracy drop compared to disproportionately slower solutions.
RIT Digital Institutional Repository RIT Digital Institutional Repository

Several works have been done in the area of image retrieval systems, and many are still trying to provide improvements for a better model for retrieving said images. Image segmentation using clustering techniques is one of the most used approaches. There are various clustering methods available, but the non-linear k-means clustering technique is the most used method. In the following research, a model of retrieving images using a non-linear classifier aided with a convolutional neural network is proposed. Both algorithms were exploited and paired in terms of feature extraction and classification. Comprehensive evaluations over a dataset containing over 7,000 pill images of 1,000 pill types obtained from the National Library of Medicine database demonstrate significant success during the data classification using the proposed model.
Towards Automatic Transformations of Coq Proof Scripts

Proof assistants like Coq are increasingly popular to help mathematicians carry out proofs of the results they conjecture. However, formal proofs remain highly technical and are especially difficult to reuse. In this paper, we present a framework to carry out a posteriori script transformations. These transformations are meant to be applied as an automated post-processing step, once the proof has been completed. As an example, we present a transformation which takes an arbitrary large proof script and produces an equivalent single-line proof script, which can be executed by Coq in one single step. Other applications, such as fully expanding a proof script (for debugging purposes), removing all named hypotheses, etc. could be developed within this framework. We apply our tool to various Coq proof scripts, including some from the GeoCoq library.
Germany's path towards a nearly climate-neutral residential building stock: A techno-economic comparison of greenhouse gas mitigation strategies

In order to limit global warming to less than 2°C, the EU has committed itself to reducing greenhouse gas emissions by 2020 by 20% compared to 1990 levels and as part of the plans for reducing emissions in industrialized countries to cutting them by 2050 by 80–95% compared to 1990 levels [EU-Rat, 2009]. Buildings are responsible for 40% of total energy consumption and 36% of CO2 emissions in Europe [EU-COM, 2008]. Improving energy efficiency and an increased use of renewables are therefore decisive measures to ensure a decrease in the EU’s Abstract
Phytochemical Profiling and Biological Assessment of the Aerial Parts from Three Mediterranean Alkanna Species (A. orientalis, A. tinctoria, A. kotschyana) in the Boraginaceae Family

This study focuses on the phytochemical analysis of the aerial parts of three Alkanna species: A. orientalis (L.) Boiss. , A. tinctoria Tausch. and A. kotschyana A. DC. (Boraginaceae) growing wild in the Mediterranean basin, as mostly the roots of the genus have been widely researched. Their methanol extracts were subjected to qualitative LC-MS analyses, resulting in the annotation of 28 different secondary metabolites, with 27 originating from A. orientalis, 25 from A. tinctoria and 23 from A. kotschyana. The detected metabolites are categorized into three chemical types: organic acids (2), flavonoids and their glycosides (17), and caffeic acid derivatives (9). Furthermore, the chemical profiles of the three species are discussed chemotaxonomically. Caffeic acid and its derivatives, along with glucosides of quercetin and kaempferol, were identified in all three studied species. Additionally, their total phenolic and flavonoid contents were determined. The antioxidant capacity was evaluated through various chemical assays, as well as their in vitro enzyme inhibitory properties towards cholinesterases (AChE and BChE), α-amylase and α-glucosidase. The results showed that A. tinctoria exhibited the strongest antioxidant activity (211 mgTE/g extract in DPPH and 366 mgTE/g extract in ABTS), probably due to its high total phenolic (53.3 mgGAE/g extract) and flavonoid (20.8 mgRE/g extract) content, followed by A. kotschyana. These chemical and biological findings provide valuable insights for potential promising applications of the aerial parts of the species outside of the well-known uses of their roots.
An innovative network intrusion detection system (NIDS): Hierarchical deep learning model based on Unsw-Nb15 dataset

With the increasing prevalence of network intrusions, the development of effective network intrusion detection systems (NIDS) has become crucial. In this study, we propose a novel NIDS approach that combines the power of long short-term memory (LSTM) and attention mechanisms to analyze the spatial and temporal features of network traffic data. We utilize the benchmark UNSW-NB15 dataset, which exhibits a diverse distribution of patterns, including a significant disparity in the size of the training and testing sets. Unlike traditional machine learning techniques like support vector machines (SVM) and k-nearest neighbors (KNN) that often struggle with limited feature sets and lower accuracy, our proposed model overcomes these limitations. Notably, existing models applied to this dataset typically require manual feature selection and extraction, which can be time-consuming and less precise. In contrast, our model achieves superior results in binary classification by leveraging the advantages of LSTM and attention mechanisms. Through extensive experiments and evaluations with state-of-the-art ML/DL models, we demonstrate the effectiveness and superiority of our proposed approach. Our findings highlight the potential of combining LSTM and attention mechanisms for enhanced network intrusion detection.
Community Service to Provide Assistance in Preparing Financial Reports, Taxation to All Muhammadiyah Schools in Gresik Regency

The purpose of this service program is to provide knowledge and skills to schools so that they are able to prepare financial reports according to generally accepted accounting principles and are able to report tax obligations in accordance with applicable regulations. This activity was attended by 140 Muhammadiyah schools throughout Gresik Regency. The results obtained are that the school has obtained a decree ratifying the permit for the establishment of Muhammadiyah Charity Business from the Muhammadiyah Central Executive, the school has registered NPWP as the center to fulfill tax obligations, and the school has started to build an accounting system to produce school financial reports in accordance with accepted accounting principles.
Variations of soil microbial community diversity along an elevational gradient in mid-subtropical forest

Aims Soil microbes play a key role in material recycling and energy conversion in forest ecosystems. We studied the functional diversity of microbial communities and soil physical-chemical properties in order to illustrate variations of soil microbial community diversity along an elevational gradient in the Wuyi Mountains of China and influencing factors. Methods Evergreen broad-leaved forest (EBF), coniferous forest (CF), dwarf forest (DF) and alpine meadow (AM) were chosen as experimental sites along an elevation gradient in the National Natural Reserve of the Wuyi Mountains. We used Biolog EcoPlate analysis to study the functional diversity of microbial communities. Important findings There were significant differences in functional diversity of microbial communities in different soil elevations. The average well color development (AWCD), which directly reflected microbial activity and functional diversity, increased over time, while AWCD at the same soil depth gradually decreased along with increasing altitude and in the order of EBF CF DF AM. The AWCD of different soil depths for the same vegetation type was in the order of 0–10 cm 10–25 cm 25–40 cm. The Simpson index, Shannon-Wiener index, richness index and McIntosh index of EBF were all higher than AM. There was variation among substrates used by soil microbial communities in different soil elevations. The substrate used in EBF was significantly higher than the substrate used in AM. The carbon sources mostly used by soil microbes were carbohydrates and carboxylic acids, followed by amino acids, phenolic acids and polymers; the lowest was amines. Principal component analysis (PCA) identified two factors in relation to carbon sources; they explained 75.27% and 16.14% of the variation. The carbon sources used by soil microbial communities were different among different vegetationtypes. Amino acids and amides were the two main carbon sources separating the two principal component factors. Soil microbial community diversity decreased along the elevation gradient and with soil thickness, and vegetative biomass, forest litter, soil nutrient, microzoon and plant roots might be the major factors controlling this diversity.
Comparison of Aquatic Exercise Program and Vitamin D Supplementation on Vitamin D and hs-CRP Serum Levels in Children with Autism Spectrum Disorders

only vitamin D supplementation improved vitamin D serum levels (p <0.05) and aquatic exercise intervention had no significant effect on vitamin D levels. Conclusion: Aquatic exercise and vitamin D supplementation, as low-cost therapies can reduce the level of hs-CRP and improve the serum level of vitamin D in children with ASD.
High atmospheric horizontal resolution eliminates the wind‐driven coastal warm bias in the southeastern tropical Atlantic

We investigate the strong warm bias in sea surface temperatures (SST) of the southeastern tropical Atlantic that occurs in most of the current global climate models. We analyze this bias in the Max Planck Institute Earth System Model at different horizontal resolutions ranging from 0.1° to 0.4° in the ocean and 0.5° to 1.8° in the atmosphere. High atmospheric horizontal resolution eliminates the SST bias close to the African coast, due to an improved representation of surface wind stress near the coast. This improvement affects coastal upwelling and horizontal ocean circulation, as confirmed with dedicated sensitivity experiments. The wind stress improvements are partly caused by the better represented orography at higher horizontal resolution in the spectral atmospheric model. The reductions of the coastal SST bias obtained through higher horizontal resolution do not, however, translate to a reduction of the large‐scale bias extending westward from the African coast into the southeastern tropical Atlantic.
The Pre-Natal Development of Wool Follicles in Merino Sheep

A histological study has been mado of wool folliclos in skin from the trunk of 24 shcep foetuses ranging in age from (J)) to 145 days of gestation. Fifteen of t.hese foetuses are known to be entirely Merino in origin, and the remainder are believed to be wholly or predominantly Merino. Extensive use has berm mado of serial sections parallel to the axis of the wool follicles as well as those parallel to [,he skin snrfaco. Skin from ]\lorino lambs and adults has also boen examined.
A New Systemic Disease Mouse Model for Glioblastoma Capable of Single-Tumour-Cell Detection

Background: Glioblastoma is characterised by extensive infiltration into the brain parenchyma, leading to inevitable tumor recurrence and therapeutic failure. Future treatments will need to target the specific biology of tumour recurrence, but our current understanding of the underlying mechanisms is limited. Significantly, there is a lack of available methods and models that are tailored to the examination of tumour recurrence. Methods: NOD-SCID mice were orthotopically implanted with luciferase-labelled donor U87MG or MU20 glioblastoma cells. Four days later, an unlabelled recipient tumor was implanted on the contralateral side. The mice were euthanised at a humane end-point and tissue and blood samples were collected for ex vivo analyses. Results: The ex vivo analyses of the firefly-labelled MU20 tumours displayed extensive invasion at the primary tumour margins, whereas the firefly-labelled U87MG tumours exhibited expansive phenotypes with no evident invasions at the tumour margins. Luciferase signals were detected in the contralateral unlabelled recipient tumours for both the U87MG and MU20 tumours compared to the non-implanted control brain. Remarkably, tumour cells were uniformly detected in all tissue samples of the supratentorial brain region compared to the control tissue, with single tumour cells detected in some tissue samples. Circulating tumour cells were also detected in the blood samples of most of the xenografted mice. Moreover, tumour cells were detected in the lungs of all of the mice, a probable event related to haematogenous dissemination. Similar results were obtained when the U87MG cells were alternatively labelled with gaussian luciferase. Conclusions: These findings describe a systemic disease model for glioblastoma which can be used to investigate recurrence biology and therapeutic efficacy towards recurrence.
An Integrated Approach for Conducting long-term PM2.5 Exposure and Health Impact Assessments for Residents of a City-scale

This study aims to show the benefits of integrating the mobile monitoring system (MMS), hybrid land use regression (h_LUR), and air quality monitoring station (AQMS) data in both conducting long-term PM 2.5 exposure assessment (EA) and health impact assessment (HIA) for residents in a city-scale. A city installed with a government-operated AQMS was selected. A 1-year PM 2.5 dataset was collected from AQMS (AQMS 1yr , reflecting the temporal variation of the rooftop level), and was served as a basis for characterizing the spatiotemporal heterogeneity of the rooftop level (h_LUR 1yr ) using the h_LUR model. A 1-year dataset was simultaneously collected from an established MMS for characterizing the spatiotemporal heterogeneity of the ground level (MMS 1yr ). A ground-level PM 2.5 concentration predictive model was established by relating hourly MMS 1yr to h_LUR 1yr data and significant environmental covariables using the multivariate linear regression analysis. To establish long-term exposure datasets, 9-year AQMS data (AQMS 9yr ) were collected, and h_LUR 9yr and MMS 9yr were established through the application of the h_LUR and the obtained predictive model, respectively. Results show MMS 1yr (24–26 µ g m –3 ) > h_LUR 1yr (17– 19 µ g m –3 ) > AQMS 1yr (13–15 µ g m –3 ). An R 2 = 0.61 was obtained for the established ground predictive model. PM 2.5 concentrations consistently decrease by year for MMS 9yr (29–17 µ g m –3 ), h_LUR 9yr (25–12 µ g m –3 ), and AQMS 9yr (22–11 µ g m –3 ), respectively. The result MMS 9yr > h_LUR 9yr > AQMS 9yr indicates both the use of h_LUR 9yr and AQMS 9yr would result in underestimating residents’ exposures. By reference to the results obtained from MMS 9yr , using AQMS 9yr and h_LUR 9yr would respectively lead to the underestimation of the attributed fraction (AFs) ~ 21%–36% and 18%–26% for the 5 disease burdens, including ischemic heart disease, stroke, chronic obstructive pulmonary disease, lung cancer, and lower respiratory tract infection. The above results clearly indicate the importance of using the integrating approach on conducting EA and HIA.
Donepezil and Quercetin Simultaneous Estimation in Rat Plasma Using Developed Bioanalytical HPLC Method: Relevance in Pharmacokinetic Studies

The objective of this investigation was to create and apply a reliable reverse phase high performance liquid chromatography (RP-HPLC) technique for the concurrent measurement of donepezil (DPZ) and quercetin (QT) in rat blood samples for pharmacokinetic research. This is the first publication that introduces a method for DPZ and QT simultaneous determination in rat plasma by high-performance liquid chromatography (HPLC). Using a mobile phase of methanol and HPLC grade water (pH 2.8; adjusted with 0.05% v/v orthophosphoric acid) 45:55 v/v with 2-3 drops of triethylamine (TEA) in an isocratic elution mode at flow rate of 1.0ml/min, DPZ and QT were successfully separated chromatographically on a Hypersil gold C-18 column (250 mm × 4.6 mm, 5μm). The retention time for DPZ and QT was observed to be 6.3 and 12.3 minutes and was detected at an isobestic wavelength of 273 nm using a UV detector. The method was shown to be precise (%RSD < 2%), accurate (96–100%), and specific for the simultaneous detection of DPZ and QT. Several freeze-thaw cycles of the treated plasma samples did not significantly affect the analyte’s stability. The method’s applicability was subsequently confirmed through an oral pharmacokinetic investigation in rats. Since the results were deemed trustworthy, the validated RP-HPLC method may be used to simultaneously detect and quantify both drugs. The method worked well for evaluating the pharmacokinetic characteristics in wistar rats following a single oral dose of 5 mg/kg of QT and 10 mg/kg of DPZ. It is well acknowledged that the chromatographic process is straightforward, robust, accurate, exact, and repeatable.
Achieving social justice through hybrid rural and urban model of community based tourism: A conceptual framework / Nuraisyah Chua Abdullah and Ramzyzan Ramly

The governments of many countries have identified Community Based Tourism (CBT) in rural tourism as a catalyst for the development of rural community. Urban poverty in many countries including Malaysia and Cambodia is due to rural-urban migration. The natural population growth in urban areas is an increasingly visible phenomenon in these countries. Hence, this paper aims to suggest the inclusion of the existing concept of community based tourism (CBT) into the urban setting as a supplement to the existing concept, which is dominant in the rural setting. Using Malaysia and Cambodia as a case study, it is the contention of this paper that the hybrid rural and urban community based tourism would better facilitate social justice in tourism destinations.