Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Planting Distance in a Simple Model of Habitat Restoration With an Allee Effect

Ecological restoration is emerging as an important strategy to improve the recovery of degraded lands and to combat habitat and biodiversity loss worldwide. One central unresolved question revolves around the optimal spatial design for outplanted propagules that maximizes restoration success. Essentially, two contrasting paradigms exist: the first aims to plant propagules in dispersed arrangements to minimize competitive interactions. In contrast, ecological theory and recent field experiments emphasize the importance of positive species interactions, suggesting instead clumped planting configurations. However, planting too many propagules too closely is likely to waste restoration resources as larger clumps have less edges and have relatively lower spread rates. Thus, given the constraint of limited restoration efforts, there should be an optimal planting distance that both is able to harness positive species interactions but at the same time maximizes spread in the treated area. To explore these ideas, here we propose a simple mathematical model that tests the influence of positive species interactions on the optimal design of restoration efforts. We model the growth and spatial spread of a population starting from different initial conditions that represent either clumped or dispersed configurations of planted habitat patches in bare substrate. We measure the spatio-temporal development of the population, its relative and absolute growth rates as well as the time-discounted population size and its dependence on the presence of an Allee effect. Finally, we assess whether clumped or dispersed configurations perform better in our models and qualitatively compare the simulation outcomes with a recent wetland restoration experiment in a coastal wetland. Our study shows that intermediate clumping is likely to maximize plant spread under medium and high stress conditions (high occurrence of positive interactions) while dispersed designs maximize growth under low stress conditions where competitive interactions dominate. These results highlight the value of mathematical modeling for optimizing the efficiency of restoration efforts and call for integration of this theory into practice.
Iron Speciation in Fram Strait and Over the Northeast Greenland Shelf: An Inter-Comparison Study of Voltammetric Methods

Competitive ligand exchange – adsorptive cathodic stripping voltammetry (CLE-AdCSV) is a widely used technique to determine dissolved iron (Fe) speciation in seawater, and involves competition for Fe of a known added ligand (AL) with natural organic ligands. Three different ALs were used, 2-(2-thiazolylazo)-p-cresol (TAC), salicylaldoxime (SA) and 1-nitroso-2-napthol (NN). The total ligand concentrations ([Lt]) and conditional stability constants (log K′Fe’L) obtained using the different ALs are compared. The comparison was done on seawater samples from Fram Strait and northeast Greenland shelf region, including the Norske Trough, Nioghalvfjerdsfjorden (79N) Glacier front and Westwind Trough. Data interpretation using a one-ligand model resulted in [Lt]SA (2.72 ± 0.99 nM eq Fe) > [Lt]TAC (1.77 ± 0.57 nM eq Fe) > [Lt]NN (1.57 ± 0.58 nM eq Fe); with the mean of log K′Fe’L being the highest for TAC (log ′KFe’L(TAC) = 12.8 ± 0.5), followed by SA (log K′Fe’L(SA) = 10.9 ± 0.4) and NN (log K′Fe’L(NN) = 10.1 ± 0.6). These differences are only partly explained by the detection windows employed, and are probably due to uncertainties propagated from the calibration and the heterogeneity of the natural organic ligands. An almost constant ratio of [Lt]TAC/[Lt]SA = 0.5 – 0.6 was obtained in samples over the shelf, potentially related to contributions of humic acid-type ligands. In contrast, in Fram Strait [Lt]TAC/[Lt]SA varied considerably from 0.6 to 1, indicating the influence of other ligand types, which seemed to be detected to a different extent by the TAC and SA methods. Our results show that even though the SA, TAC and NN methods have different detection windows, the results of the one ligand model captured a similar trend in [Lt], increasing from Fram Strait to the Norske Trough to the Westwind Trough. Application of a two-ligand model confirms a previous suggestion that in Polar Surface Water and in water masses over the shelf, two ligand groups existed, a relatively strong and relatively weak ligand group. The relatively weak ligand group contributed less to the total complexation capacity, hence it could only keep part of Fe released from the 79N Glacier in the dissolved phase.
A High Triglyceride-Glucose Index Is Associated With Contrast-Induced Acute Kidney Injury in Chinese Patients With Type 2 Diabetes Mellitus

Background and Objectives Triglyceride-glucose (TyG) is an emerging vital indicator of insulin resistance and is associated with increased risk of T2DM and cardiovascular events. We aimed to explore the TyG index and contrast-induced acute kidney injury (CI-AKI) in patients with type 2 diabetes who underwent coronary angiology. Methods This study enrolled 928 patients with suspected coronary artery disease who underwent coronary angiology or percutaneous coronary intervention in Zhongda hospital. Patient data were divided into quartiles according to the TyG index: group 1: TyG ≤ 8.62; group 2: 8.629. 45. CI-AKI was diagnosed according to the KIDIGO criteria. Demographic data, hematological parameters, coronary angiology data, and medications were all recorded. We calculated the TyG index using the following formula: ln [fasting TG (mg/dL)×FPG (mg/dL)/2]. Results Patients who developed CI-AKI exhibited significantly higher TyG index levels compared to patients who did not develop CI-AKI. The incidence of CI-AKI sharply increased with increasing TyG. Univariate and multivariate analysis identified TyG as an independent risk factor for CI-AKI. The AUC of the ROC curve was as high as 0.728 when the value of TyG was 8.88. The corresponding sensitivity was as high as 94.9%. Adding the variable TyG to the model for predicting CI-AKI risk further increased the predictive value of the model from 80.4% to 82%. Conclusions High TyG is closely associated with increased incidence of CI-AKI, demonstrating that TyG is an independent risk factor for CI-AKI. TyG has potentially predictive value for CI-AKI and may play a crucial role in risk stratification in clinical practice.
Use of Synonymous Deoptimization to Derive Modified Live Attenuated Strains of Foot and Mouth Disease Virus

Foot-and-mouth disease (FMD) is one of the most economically important viral diseases that can affect livestock. In the last 70 years, use of an inactivated whole antigen vaccine has contributed to the eradication of disease from many developed nations. However, recent outbreaks in Europe and Eastern Asia demonstrated that infection can spread as wildfire causing economic and social devastation. Therefore, it is essential to develop new control strategies that could confer early protection and rapidly stop disease spread. Live attenuated vaccines (LAV) are one of the best choices to obtain a strong early and long-lasting protection against viral diseases. In proof of concept studies, we previously demonstrated that “synonymous codon deoptimization” could be applied to the P1 capsid coding region of the viral genome to derive attenuated FMDV serotype A12 strains. Here, we demonstrate that a similar approach can be extended to the highly conserved non-structural P2 and P3 coding regions, providing a backbone for multiple serotype FMDV LAV development. Engineered codon deoptimized P2, P3 or P2, and P3 combined regions were included into the A24Cruzeiro infectious clone optimized for vaccine production, resulting in viable progeny that exhibited different degrees of attenuation in cell culture, in mice, and in the natural host (swine). Derived strains were thoroughly characterized in vitro and in vivo. Our work demonstrates that overall, the entire FMDV genome tolerates codon deoptimization, highlighting the potential of using this technology to derive novel improved LAV candidates.
Rapid Learning Optimization Approach for Battery Recovery-Aware Embedded System Communications

To date, battery optimization for embedded systems still a crucial subject. Actually, the majority of carried out works focus on transmission controls without taking into account the specifications of the batteries themselves. Indeed, an improvementof 70\% is reported by exploiting the battery recovery effect.In this paper, the recovery phenomenon is exploited to design an algorithm that optimizes both the lifetime of the battery and the performance of the studied system. The algorithms from Dynamic programming and Reinforcement learning fields are the first to be considered. When in Dynamic programming prior detailed information are assumed to be available, in reinforcement learning those information becomes unknown and long calculation times are needed to converge toward an optimal policy solution. The paper contribution is about designing a new Rapid Learning Algorithm (RLA) that combines both Dynamic programming and Reinforcement learning features. RLA exploits a reduced model of the system instead of exploring the whole and heavy system state model as Dynamic programming do. The RLA run-time is then shortened. Based on battery stochastic model, the simulation results obtained with RLA are compared to the Dynamic programming and Reinforcement learning algorithms under the same conditions. By taking into account the recovery effect this paper illustrates that the calculation time and the system performance are greatly improved when RLA is adopted.
Engineering of the Energy Level Alignment at Organic Semiconductor Interfaces by Intramolecular Degrees of Freedom: Transition Metal Phthalocyanines

We have determined the energy level alignment at interfaces between various transition metal phthalocyanines (MnPc, FePc, CoPc, NiPc, CuPc, ZnPc) and gold using photoemission spectroscopy. We demonstrate that the energy level alignment at these interfaces depends upon the type of transition metal. This offers a route to adjust the hole injection barrier via the choice of otherwise equivalent molecular organic semiconductors. In particular, the interfaces MnPc/Au and CoPc/Au are characterized by a small hole injection barrier, which would be advantageous for applications.
Tournament Selection Improves Cartesian Genetic Programming for Atari Games

The objective of this paper is to extend Cartesian Genetic Programming (CGP) for the evolution of Atari game agents in the Ar-cade Learning Environment. Based upon preliminary work on the use of CGP playing Atari games, we propose extensions like the repeated evaluation of elite solutions. Furthermore, we improve the CGP optimization process by increasing the diversity in the population with tournament selection. Experimental studies on four exemplary Atari games show that the modiﬁcations decrease premature stagnation during the evolutionary optimization process and result in more robust agent strategies.
Investigating 3D-STDenseNet for Explainable Spatial Temporal Crime Forecasting

Crime is a well-known social problem faced worldwide. With the availability of large city datasets, the scientiﬁc community for predictive policing has switched its focus from people-centric to place-centric, focusing on heterogeneous data points related to a particular geographic region in predicting crimes. Such data-driven techniques identify micro-level regions known as hotspots with high crime intensity. In this paper, we adapt the state-of-the-art spatial-temporal prediction model STDenseNetFus to predict crime in geographic regions in the presence of external factors such as a region’s demographics, seasonal events and weather. We demonstrate that STDenseNet maintains prediction performance compared to previous results [1] on the same dataset despite signiﬁcantly reduced parameter count. We further extend STDenseNetFus architecture from two-dimensional to three-dimensional convolutions and show that it further improves the prediction results. Finally we investigate the use of the DeepShap model expla-nation method to provide insights into the important input features eﬀecting the model forecasts.
DETERMINANTS OF CLIENTS' INTENTION TO ADOPT TAKAFUL SERVICES IN GOMBE STATE Abstract The Vision 2020 of the Federal Government of Nigeria envisaged a reduction of the financially

The Vision 2020 of the Federal Government of Nigeria envisaged a reduction of the financially excluded adults to at most 20% by the target year. Records have shown that there is no substantial progress towards the target for the three geopolitical zones to the north of the country under the insurance sub-sector even with an available alternative. This study, therefore, sought to identify the factors that individuals consider to be the determinants of the decision to partake in Takaful. Primary data requirements were met in Gombe state, which is situated in the North-east geopolitical zone of the country. It utilises the partial least square structural equation modelling method adapting the Ajzen's (1991) Theory of Planned Behaviour through the expansion of Subjective Norm into Religious influence, Social & demographic influences and perceived usefulness. The study's interesting finding is that the attitude towards purpose beta(at â= 0.473) is greater than the beta of the remaining constructs in the model. This indicates that the degree of positive understanding and perception has a greater effect on changing consumer attitudes towards behavioral intentions. The paper, therefore, recommended the building of societal knowledge and awareness towards Takaful and financial inclusion by all stakeholders through campaigns.
Multiword Expression Aware Dependency Parsing

Currently, natural language understanding (NLU) has a increasing inﬂuence on our daily life, such as automatically speech recognition and neural machine translation. Multiword expression identiﬁcation is a real headache for decades, which could dig out the idiomatically words from sentences for advanced application like information retrieval. This thesis proposes a multi-task deep learning model, aiming to extract the syntactic relations incorporated with multiword expression identiﬁcation via a novel transition based dependency parsing. Due to the poor performance of traditional probabilistic graphical model for inferencing the distributions of different types of multiword expression, this thesis tries to improve the identiﬁcation of multiword expressions by adding syntactic and semantic informations which is derived from transition based dependency parsing. However, the traditional transition based dependency parsing only carries transitions on single word. Therefore, we modiﬁed the arc-standard dependency parsing to be consistent with doing transitions over multiword expressions which may be more than two words. By combining these two tasks, the identiﬁcation result is roughly below the pure multiword expression identiﬁcation work, but better than another work that also integrates two tasks (has different parsing structure and training method). As for dependency relations result, it performs much worse than others with only about 60% on UAS and 55% on LAS. In all, this model has better ability of recalling multiword expression with over 45% exact recall rate, and the precision is also close to the best result from others’ work, but the function of constructing syntactic relations still needs to be improved.
Voices from EFL Thai learners towards English writing

English language writing is seen as one of the most difficult skills for undergraduate students. When composing a piece of writing, students usually face various problems ranging from grammatical aspects to expressing ideas and opinions. To answer the research questions, this study employed a mixed method of both qualitative and quantitative approaches to identify the students’ perceptions towards Business Article Writing Course, as well as to pinpoint their challenges when working on the written assignments. The intensive data were collected from 20 fourth year students majoring in Business English via the use of questionnaire and a semi-structured interview. The findings give teachers, course designers, and educational organizations an insight into students’ problems in learning English language writing. It also highlights the need to integrate different genres of writing to enhance students’ writing skills so that they can use such techniques to overcome any struggles when composing a piece of writing. Keywords: Academic Writing, EFL, Writing Strategies, Peer Feedback
Structural Stability, Electronic, Magnetic, and Optical Properties of Rectangular Graphene and Boron Nitride Quantum Dots: Effects of Size, Substitution, and Electric Field

Using density functional theory calculations, we have examined the structural stability, electronic, magnetic, and optical properties of rectangular shaped quantum dots (QDs) of graphene (G), boron nitride (BN), and their hybrids. Different hybrid QDs have been considered by substituting a GQD (BNQD) with BN-pairs (carbon atoms) at different positions. Several parameters, like size, amount of substitution, and so forth, have been varied for all these QDs (GQDs, BNQDs, hybrid-QDs) to monitor the corresponding changes in their properties. Among the considered parameters, we find that substitution can act as a powerful tool to attain interesting properties with these QDs, for example, a broad range of absorption (∼2000 nm) in the near-infrared (NIR) region, spin-polarized HOMO–LUMO gaps without the application of any external-bias, and so forth, which are highly required in the preparation of opto-electronic and electronic/spintronic devices, among others. Explanations have been given in detail by varying di.
Dielectric measurement of the resistance of Trichosporon cutaneum against toxic chemicals

Conditioning of cultures involves growing cells in the presence of increasing amounts of a toxic chemical. In order to investigate how conditioning affects a culture’s ability to resist new challenges, the resistance of Trichosporon cutaneum to various toxic chemicals, before and after conditioning to growth on phenol, was investigated by measuring the capacitance of cell suspensions at 0.4 MHz following a toxic challenge. The results show that cells grown on phenol are more resistant to the influence of polar aromatic toxic chemicals such as phenol (log Pow = 1.48) and benzylalcohol (log Pow = 1.1), but less resistant against less polar non-aromatic compounds such as n-octanol (log Pow = 2.9). In reverse, cells grown on glucose were found to be more resistant against n-octanol, but less so against phenol and benzylalcohol. The results indicate that cells, adapted to be more resistant to one type of substance, may become more susceptible to other compounds.
Mechanisms of the removal of metals from acid and neutral mine water under varying redox systems

This thesis investigates the effectiveness of a passive treatment technology for Fe removal from low pH metal mine water. In addition, the use of electrocoagulation (EC) in removing Zn from circumneutral mine water and acid mine drainage (AMD) was studied. Using an advanced oxidation process (AOP) followed by EC converted Fe(II) from coal mine drainage to a stable magnetic form of Fe. Research also studied the use of Cu electrodes in removing high concentrations of metals and sulphate from AMD.
Tailoring crystal shape and polymorphism using combinations of solvents and a structurally related additive

Controlling polymorphism is one of the most difficult challenges for the pharmaceutical industry. Polymorphs of the same compound can have very different properties that might affect the quality of the final drug. Many studies have focused on trying to determine robust methods to produce specific polymorphs that exhibit the desired characteristics of the drug (solubility and rate of dissolution in particular). The choice of solvent, pH, kinetic conditions and the presence of impurities can all have very strong effects on the polymorphic outcome of cooling crystallization. In this work, the crystallization of ortho-aminobenzoic acid (OABA) in the presence of a structurally related additive (benzoic acid) will be studied using both in situ PAT tools and offline techniques. The effect on morphology, polymorphic outcome, polymorphic transformation kinetics and tendency towards agglomeration in different solvents will be studied using a large variety of instrumentation. The incorporation of benzoic acid in solid solution in the three different polymorphs of OABA will also be quantified and discussed. The results of the crystallization experiments and offline analysis will be compared and interpreted using the information on the crystal structures of the three OABA polymorphs from the Cambridge Crystallographic database.
Secondary Reactions in the High-Temperature Free Radical Polymerization of Butyl Acrylate

Secondary reactions have a marked effect on butyl acrylate polymerization rate and polymer structure under the high-temperature free radical reaction conditions typically used for production of solvent-based acrylic coatings resins. The low monomer concentrations characteristic of semibatch starved-feed reactor operation lead to significant rates of intramolecular transfer, resulting in a tertiary radical center capable of termination, monomer addition, or β-scission. The rate coefficients for these reactions are estimated from monomer concentrations, polymer molecular weights, and NMR analyses of quaternary branch points and macromer end groups for a series of semibatch experiments with varying monomer and polymer concentrations. A classical free radical polymerization model is insufficient for the description of this complex system. Thus, a mechanistic model including the additional reactions has been formulated and is shown to provide a good representation of the experimental results.
QUANTITATIVE ANALYSIS OF GLUCOSE LEVEL IN BLOOD SERUM OF THREE GOAT BREEDS (CAPRA HIRCUS) IN NORTHERN PAKISTAN

Glucose is used as fuel for energy production, leading to maintaining physiological phenomena of cell and animal body. The blood glucose level in ruminants is actively transported through bloodstreams and circulating carbohydrates. The study aimed to evaluate the glucose level as an indicator of energy in goat breeds (Koh-e-Ghizer, Gojali and Baltistani) inhabiting three regions of Gilgit-Baltistan (GB), namely Ghizer, Baltistan and Hunza-Nagar. Data were collected from both male and female goats with the age of two years and above, determined based on teeth composition. Samples of blood were randomly taken from 270 goats (120 male &150 females) by using 5ml clinical syringes and serum was obtained by centrifugation process. The quantity of glucose in mg/dl of serum was determined by analyzing the serum in Micro-lab 300. These goats majorly feed on pure organic forage in high altitude pastures in all three regions. The results revealed that the average level of glucose obtained from male goats was 65.50±16.77 mg/dl in Ghizer, 76.40±16.11 mg/dl in Baltistan, 87.95±11.52 mg/dl in Hunza-Nagar and glucose level in female was 67.94±15.02 mg/dl in Ghizer, 70.92±15.01mg/dl in Baltistan, and 83.82±9.51 mg/dl in Hunza Nagar respectively. The analysis of variance (ANOVA) has shown significant differences of glucose within sex and region at p≤0.001. Serum glucose was observed higher in female goats in comparison with male goats in district Ghizer. It also reflects the pastures’ potential in the three major regions of Gilgit-Baltistan, need to be noticed by the herders and livestock department in the regions while taking initiatives for pasture management.