Miracle-dz/UniFAR-FTUs huggingface dataset:
Trans-1,4-polybutadiene: Influences of Lewis bases on polymerization of butadiene with supported titanium catalyst systems

Abstract Three MgCl2 supported TiCl4 pro-catalysts; Cat-A, Cat-B and Cat-C were synthesized. Cat-A was synthesized without any internal Lewis base (ILB); while Cat-B and Cat-C were synthesized using diisobutyl phthalate and ethyl benzoate as ILBs respectively. The effect of ILBs on stereoregularity and the microstructure of polybutadiene (PBD) was investigated. The vast differences in the amount of trans-1,4-structure of PBD by Cat-A, Cat-B and Cat-C systems were correlated with the nature of ILBs used by studying their polymerization kinetics. The energy barriers for polymerization reactions were calculated for all three catalysts systems using Arrhenius equation. Cat-B, has shown the highest energy barrier (23 kJ/mol) due to DIBP as ILB in its structure. Cat-A has given the lowest trans-1,4-PBD as it does not contain any ILB and has the minimum energy barrier (12 kJ/mol) while Cat-C has shown medium energy barrier (17 kJ/mol). We have also studied the effect of suitable external Lewis bases during polymerization. The effect of polymerization parameters like Al/Ti molar ratio, Al/LB molar ratios and the temperatures on PBD microstructure were studied. Based on the polymerization kinetics studies and the effect of LBs on PBD microstructure, a possible reaction mechanism has been proposed. Graphical Abstract
Red and Purple Flesh Potatoes a Healthy and Attractive Alternative Associated with New Market Trends

The potato is the fourth most important crop in the world in terms of human food, after maize, wheat and rice (FAOSTAT, 2019). The cultivated potato is a vital food-security crop considering its worldwide growth, from latitudes 65° Lat N to 53° Lat S, high yield, and great nutritive value. The potato is a good source of dietary energy and micronutrients, and its protein content is high in comparison with other roots and tubers. The cultivated potato is also a concentrated source of vitamin C and some minerals such as potassium and magnesium. Tuber flesh color generally ranges from white to dark yellow in cultivated potato; however, the high potato diversity shows tuber flesh color varies from white to dark purple. Red and purple-flesh potatoes are an interesting alternative for consumers due to phenolic compounds and antioxidant capacity. The goal of this publication is to show the advances in red and purple flesh potato, in terms of anthocyanin profile, color extraction and stability in simulated in vitro digestion.
Ten future challenges for synthetic biology

Abstract After 2 decades of growth and success, synthetic biology has now become a mature field that is driving significant innovation in the bioeconomy and pushing the boundaries of the biomedical sciences and biotechnology. So what comes next? In this article, 10 technological advances are discussed that are expected and hoped to come from the next generation of research and investment in synthetic biology; from ambitious projects to make synthetic life, cell simulators and custom genomes, through to new methods of engineering biology that use automation, deep learning and control of evolution. The non‐exhaustive list is meant to inspire those joining the field and looks forward to how synthetic biology may evolve over the coming decades.
Predicting ewe body condition score using adjusted liveweight for conceptus and fleece weight, height at withers, and previous body condition score record

Abstract The relationship between ewe body condition score (BCS) and liveweight (LW) has been exploited previously to predict the former from LW, LW-change, and previous BCS records. It was hypothesized that if fleece weight and conceptus-free liveweight and LW-change, and in addition, height at withers were used, the accuracy of current approaches to predicting BCS would be enhanced. Ewes born in 2017 (n = 429) were followed from 8 mo to approximately 42 mo of age in New Zealand. Individual ewe data were collected on LW and BCS at different stages of the annual production cycle (i.e., prebreeding, at pregnancy diagnosis, prelambing, and weaning). Additionally, individual lambing dates, ewe fleece weight, and height at withers data were collected. Linear regression models were fitted to predict current BCS at each ewe age and stage of the annual production cycle using two LW-based models, namely, unadjusted for conceptus weight and fleece weight (LW alone1) and adjusted (LW alone2) models. Furthermore, another two models based on a combination of LW, LW-change, previous BCS, and height at withers (combined models), namely, unadjusted (combined1) and adjusted for conceptus and fleece weight (combined2), were fitted. Combined models gave more accurate (with lower root mean square error: RMSE) BCS predictions than models based on LW records alone. However, applying adjusted models did not improve BCS prediction accuracy (or reduce RMSE) or improve model goodness of fit (R2) (P > 0.05). Furthermore, in all models, both LW-alone and combined models, a great proportion of variability in BCS, could not be accounted for (0.25 ≥ R2 ≥ 0.83) and there was substantial prediction error (0.33 BCS ≥ RMSE ≥ 0.49 BCS) across age groups and stages of the annual production cycle and over time (years). Therefore, using additional ewe data which allowed for the correction of LW for fleece and conceptus weight and using height at withers as an additional predictor did not improve model accuracy. In fact, the findings suggest that adjusting LW data for conceptus and fleece weight offer no additional value to the BCS prediction models based on LW. Therefore, additional research to identify alternative methodologies to account for individual animal variability is still needed.
Effects of released farmed mallards on species richness of breeding waterbirds and amphibians in natural, restored and constructed wetlands

Common practices in current game management are wetland restoration and creation, as well as releases of quarry species. We studied the impact of releases of mallard ducklings on species richness of wild waterbirds and amphibians on three types of wetlands: natural, constructed and restored. Data on species richness, macrophyte cover and water characteristics (total phosphorous and pH) were collected at 32 sites in an agricultural landscape in southern Sweden. In total, 14 species of waterbirds were recorded, ranging from zero to seven per wetland and survey. Amphibians were present in 24 of the 32 wetlands; in total five species were found, ranging from zero to three per wetland. By using generalized linear modelling we found that wetland type best predicted waterbird species richness. Constructed wetlands had significantly more waterbird species, regardless of whether they were used for mallard releases or not. There were breeding amphibians in 62% of natural, 100% of restored and 77% of constructed wetlands. Breeding amphibians were present in 84% of wetlands without, and in 62% of wetlands with releases. However, included variables did not explain amphibian species richness in the wetlands. Releasing large numbers of mallards on a wetland and providing food ad libitum is likely to affect water quality, nutrient availability and predation pressure. Indeed, phosphorous levels were significantly higher in release wetlands, but no differences were found between wetland types.This means that mallard releases may increase nutrient loads in environments that are already eutrophied. However, in our study system releases did not influence species richness of waterbirds and amphibians locally. Constructing wetlands for mallard releases can thus have positive local effects on species richness.
Contributions Regarding the Development and Experimentation of a Specific Physical
 Training Model for Greco-Roman Junior Wrestlers

The use of methods to objectify the specific activities of athletes in training and competitions is not a problem studied to its true extent in wrestling. Measuring and evaluating the predictability components of competitive performance in this sport is even more important given the fact that in free and Greco-roman wrestling the elaboration of models has never been easy, due to the unquantifiable performance that performers have to achieve. Therefore, the issue is the most important field of research in the current stage in sports wrestling, before becoming an operational tool available to practitioners. The transformation of these components into figures allows obtaining results that can define the weight and impact they have in creating training and competitive models, selection models, planning, control and evaluation of the efficiency of training methods and especially the establishment of a battery of tests, usually validated by the method of factor analysis, to support periodic improvements by assimilating the progress in knowledge. From this point of view, we proposed the elaboration of the action strategy in order to increase the efficiency and highlight some components of the specific physical training model, whose materialization at the level of junior athletes decisively influenced the training activity, as a premise in obtaining the performance goals. Our experimental approach took place at the Dinamo Bucharest Sports Club, where the junior sports of the club and the national junior team trained. The training of the junior wrestlers from the Greco-roman style according to the parameters of the specific physical training model foreshadowed by us, demonstrated its efficiency and led to the modeling of the wrestling behavior and performance compatible with that of high-performance wrestlers.
GWO-Based Tuning of LQR-PID Controller for a 3-DOF Parallel Manipulator

This paper presents the mathematical modeling and optimal trajectory tracking control of a 3-degree-of-freedom parallel manipulator, commonly known as Maryland manipulator. Three unlike sequential trajectories are considered, and the trajectory-tracking control of a manipulator is performed by the LQR-PID controller. The tuning of LQR-PID is done by using the Grey Wolf Optimizer (GWO), a meta-heuristic method. The two other traditional benchmarking algorithms are Particle Swarm Optimizer (PSO) and Genetic Algorithm (GA). The main goal of this work is to calculate the optimum values of LQR gain parameters i.e. Q and R matrices and PID controller’s gains i.e. Kp , Ki and Kd using three different optimization algorithms, and their performance comparisons are highlighted in simulation results and discussion section. According to the obtained simulation results, the proposed GWO methodology is more efficient and more accurate in trajectory tracking control and generates optimal torques to the input links of the manipulator when compared with other evolutionary optimization algorithms such as PSO and GA.
Root System Morphology of Ipê-Roxo Tree Grown in Soil Subjected to Phosphorus Application in Subtropical Climate Region

Phosphorus (P) availability in subtropical soils does not often meet the nutritional demand of native tree species such as the ipê-roxo tree (Handroanthus heptaphyllus); therefore, it is necessary to supply P at planting. However, the impact of P on root system growth remains unknown. The aim of the current study was to investigate the effect of P application on root morphology of H. heptaphyllus plants over a 36-month period in a subtropical climate region. During the experiment, the plants subjected to fertilization with 40 kg P ha−1 were compared to untreated control. Plant roots were scanned through minirhizotron system 18 and 36 months after transplant (MAT), and generated images were used to determine total root length, mean root diameter and total root volume. Plant height and leaf P concentrations were also evaluated. Phosphorus application enhanced root and whole plant growth with a more evident effect at 36 MAT, when soil P availability decreased. The results give important information on the cultivation of H. heptaphyllus plants in soils presenting low P availability.
Featurization strategies for protein–ligand interactions and their applications in scoring function development

The predictive performance of classical scoring functions (SFs) seems to have reached a plateau. Currently, SFs relying on sophisticated machine learning techniques have shown great potential in binding affinity prediction and virtual screening. As one of the most indispensable components in the workflow of training a machine learning scoring function (MLSF), the featurization or representation process enables us to catch certain physical processes that are important for protein–ligand interactions and to obtain machine‐readable descriptors. Currently, according to how they are derived, the descriptors used in MLSFs for both continuous and binary binding affinity estimates can be grouped into two broad categories: handcrafted features and automated‐extraction features. Moreover, the automated‐extraction features emerge as a new featurization trend along with the application of deep learning algorithms. Here, we make a thorough summary of the advances in the featurization strategies for protein–ligand interactions in the context of MLSFs, with emphasis on the recently rising automated‐extraction features. We also discuss the similarity between protein–ligand interaction representations and small‐molecule representations, and the challenges confronted by the scientific community in characterizing protein–ligand interactions. We expect that this review could inspire the development of novel featurization approaches and boosted MLSFs.
The Role of Recent (1985–2014) Patterns of Land Abandonment and Environmental Factors in the Establishment and Growth of Secondary Forests in the Iberian Peninsula

Farmland abandonment has been a widespread land-use change in the Iberian Peninsula since the second half of the 20th century, leading to the establishment of secondary forests across the region. In this study, we aimed to address changes in the recent (1985–2014) emergence patterns of these forests and examine how environmental factors affected their growth by considering differences in leaf-habit types. We used a combination of Landsat-derived land-cover maps and aboveground biomass (AGB) maps from the European Space Agency to assess the secondary forest establishment and growth, respectively, in the study region. We also obtained a set of topographic, climatic and landscape variables from diverse GIS layers and used them for determining changes over time in the environmental drivers of forest establishment and AGB using general linear models. The results highlight that secondary forest cover was still increasing in the Iberian Peninsula at a rate above the European average. Yet, they also indicate a directional change in the emergence of secondary forests towards lower and less steep regions with higher water availability (mean rainfall and SPEI) and less forest cover but are subjected to greater drought events. In addition, these environmental factors differentially affect the growth of forests with different leaf-habit types: i.e., needleleaf secondary forests being less favoured by high temperature and precipitation, and broadleaf deciduous forests being most negatively affected by drought. Finally, these spatial patterns of forest emergence and the contrasting responses of forest leaf-habits to environmental factors explained the major development of broadleaf evergreen compared to broadleaf deciduous forests and, especially, needleleaf secondary forests. These results will improve the knowledge of forest dynamics that have occurred in the Iberian Peninsula in recent decades and provide an essential tool for understanding the potential effects of climate warming on secondary forest growth.
Tetraploidization Increases the Contents of Functional Metabolites in Cnidium officinale

Cnidium officinale is an important medicinal crop grown in Asia for its pharmacological properties. In this study, tetraploid breeding was conducted to increases the content of medicinal compound and tolerance to the environmental conditions using in vitro shoot culture of C. officinale. For this, we generated tetraploid C. officinale plants using oryzalin, a chromosome doubling agent, and compared the morphological traits, cytological characteristics, and heat stress-responsive gene expression levels between tetraploid and diploid genotypes. Chromosome doubling efficiency was the highest in plantlets treated with 4.0 mg∙L−1 oryzalin for 2 days. Compared with diploids, the plant height of tetraploids was reduced, while the petiole diameter was increased by approximately 39%. The dry matter of tetraploid leaves was significantly higher than that of diploid leaves. Compared with diploids, tetraploids showed higher chloroplast number and stomatal complex size but lower chlorophyll and carotenoid contents. The phenolic content of tetraploid plantlets was significantly higher than that of diploid plantlets. Contents of naringin as well as salicylic acid and gentisic acid, which are strong antioxidant compounds, were dramatically increased upon tetraploidization. Interestingly, liquid chromatography–mass spectrometry (LC–MS) analyses revealed increased levels of senkyunolide F and phthalide in tetraploid roots but not in tetraploid or diploid leaves.
Smoothed kernel estimation of bivariate residual entropy function

Abstract In this article, we propose an estimator for a bivariate residual entropy function based on smoothed kernel procedure. Asymptotic properties of the proposed estimator are established under some regularity conditions. Simulation studies demonstrate that the estimator performs well even for increased sample sizes and different combinations of lifetimes. The performances of the proposed estimator are tabulated and illustrated through a data on recurrence of cancer.
Effect on Microstructure and Hardness of Reinforcement in Al–Cu with Al4C3 Nanocomposites

By superposition, the individual strengthening mechanisms via hardness analyses and the particle dispersion contribution to strengthening were estimated for Al–C and Al–C–Cu composites and pure Al. An evident contribution to hardening due to the density of dislocations was observed for all samples; the presence of relatively high-density values was the result of the difference in the coefficients of thermal expansion (CTE) between the matrix and the reinforced particles when the composites were subjected to the sintering process. However, for the Al–C–Cu composites, the dispersion of the particles had an important effect on the strengthening. For the Al–C–Cu composites, the maximum increase in microhardness was ~210% compared to the pure Al sample processed under the same conditions. The crystallite size and dislocation density contribution to strengthening were calculated using the Langford–Cohen and Taylor equations from the microstructural analysis, respectively. The estimated microhardness values had a good correlation with the experimental. According to the results, the Cu content is responsible for integrating and dispersing the Al4C3 phase. The proposed mathematical equation includes the combined effect of the content of C and Cu (in weight percent). The composites were fabricated following a powder metallurgical route complemented with the mechanical alloying (MA) process. Microstructural analyses were carried out through X-ray analyses coupled with a convolutional multiple whole profile (CMWP) fitting program to determine the crystallite size and dislocation density.
Prevalence and factors associated with intimate partner violence and related injuries in India: evidence from National Family Health Survey-4

ABSTRACT Violence against women perpetrated by the partner is a serious human rights violation and public health concern. This study examines the prevalence and factors associated with intimate partner violence (IPV) and related injuries in India using data from the National Family Health Survey (NFHS-4), 2015–2016. We found that 27.4% of women experienced physical violence, 12% faced emotional violence, and 6.7% suffered from sexual violence perpetrated by the partner. Additionally, around one in every four women (24.5%) were subjected to violence-related injuries. Multivariable regression results show that alcohol consumption by couples, history of family violence, child marriage, and longer marital duration increased the likelihood of intimate partner violence and related injuries. Women who belonged to Muslim and Scheduled Caste communities and were employed had significantly more likelihood to experience husband-perpetrated violence than their counterparts. Contrastingly, women residing in rural areas, belonging to economically well-off families, and having higher levels of education and decision-making autonomy were associated with lower odds of intimate partner violence and injuries. This study underscores the need for prioritizing girls’ education, promoting gender equality, and enforcing strict actions against the perpetrators to prevent the act of violence.
Stochastic Depth Residual Network for Hyperspectral Image Classification

The convolutional neural network (CNN) is a feed-forward neural network with deep structure and convolution operation. In the hyperspectral image (HSI) classification, CNN has demonstrated excellent performance in extracting spectral and spatial information. However, the inherent complexity and high dimension of HSIs still limit the performance of most neural network models. The powerful feature extraction ability of CNN is normally achieved by dozens or more layers, which brings a series of problems such as gradient vanishing, overfitting, and slow training speed. In order to address these problems, this article presents a CNN architecture-based stochastic depth residual network (SDRN), which is specially designed for HSI data. This model takes the original 3-D cube as the input and 3-D convolution is used to extract abundant spectral and spatial features through corresponding residual blocks. In order to reduce the training time, we adopt a stochastic depth strategy. For each small batch, a sublayer is randomly discarded by an identity function. During the testing stage, the residual network with complete depth is used. Experiments on three datasets and a comparison of the state-of-art methods show that SDRN has great advantages in accuracy and training time compared with state-of-the-art HSI classification methods.
The Mediating Role of Employees' Negative Moods Between Bullying at Work and Organizational Citizenship Behavior Toward Individuals in Egyptian Hotels

For all people, bullying always sparks unpleasant memories, especially at the workplace when employees may be regularly bullied "verbally/ non-verbally" regardless of their age and position. Such a phenomenon consequently affects the employee mood and creates counter organizational citizenship behaviors. This research aims at shedding light on the mediating role of employees' moods between bullying at work and organizational citizenship behavior in Egyptian hotels. A questionnaire was directed to a random sample of 383 workers in front of-house employees in five-star hotels in SharmElshiekh. The obtained data was analyzed statistically by smart PLS version 3. The research revealed a mediating role of employees' moods between bullying at work and organizational citizenship behavior in Egyptian hotels. The research recommends that hotels should accurately monitor the workplace bullying phenomenon among employees to avoid its exacerbating effects.