Miracle-dz/UniFAR-FTUs huggingface dataset:
Physico-chemical characterization of cross linked chitosan-polyacrylonitrile polymer blends

Chitin a natural polymer extracted commercially from the shells of crustaceans such as prawns, crabs, krill, insects and shrimps. Chitosan is prepared from chitin by partially deacylating its acetamido groups with a strong alkaline solution. Chitin and chitosan have a wide variety of applications such as wastewater treatment which decreases the Chemical Oxygen Demand [COD] and used in preventing infections of wounds and also as a food supplement, which lower plasma cholesterol and improves the HDL cholesterol. Besides these applications chitosan has a few drawbacks like acidic solubility, low thermal and mechanical stability. To rectify these drawbacks of chitosan can be modified physically and chemically. In this present study, the biopolymer chitosan was cross linked with glutaraldehyde and blended with the copolymer polyacrylonitrile in different ratios and the prepared blend was characterized by FTIR, DSC, TGA and XRD studies. The prepared cross linked Chitosan-Poly acrylonitrile blend has good thermal stability and better adsorption capacity.
AI based Computation for Hybrid Precoding/Combining in Millimeter-Wave Massive MIMO Systems

Millimeter-wave (mm-Wave) have emerged as a potential leading technology for the 5G cellular systems due to the enormous availability of high radio-frequency spectrum, which can deliver extreme data speed and enhance spectral efficiency (SE). An economical architecture of hybrid precoder (HP) is widely used in mm-Wave massive MIMO systems (mm-WmM) to recompense for the severe propagation loss of the mm-Waves. This paper examines the design of the hybrid precoder and combiner (HPC) in mm-WmM by integrating Artificial Intelligence (AI) based optimization algorithm. AI is going to be a key component to enhance the performance of 5G wireless communications and beyond. The emerging AI based computation using Hierarchical Particle Swarm Optimization technique (HPSO) is proposed to design a HPC to maximize the SE in mm-Wave massive MIMO systems. Results obtained from simulations demonstrate the improved performance of the HPSO algorithm in contrast to the existing algorithms and can accomplish close to the optimal performance.
An Emerging Key Concept in European Constitutional Law: Sustainability

Sustainability, as comp ared to the rule of law, human rights, sovereignty or democracy, is a relatively new constitutional key concept. It is mentioned explicitly more and more in constitutional discourses, and – even more importantly – it helps to reconstruct a number of current constitutional debates under one conceptual umbrella. Sustainability comprises different responses to long term social challenges which cannot efficiently be responded to via democratic mechanisms. Democratic mechanisms are based on election terms and which are, consequently, structurally short-sighted. By ‘European constitutional law’, I mean in this paper both the primary law of the EU and domestic constitutional documents. In the present paper is am first going to sketch the nature and the types of the sustainability challenges that contemporary societies face, with a special focus on Europe (environmental, demographic and financial). In the main part of the paper, I am going to show possible constitutional responses to these challenges. Finally, I will summarise the main argument of the paper which is a suggestion to set up an economic constitutional court consisting of economists with the power to annul laws if these contradict the principles of sustainability.
The Relationship between Perceived Security Threats and Negative Descriptions of Armenians in Turkish Politics (1946–1960)

Abstract How do perceived threats influence politicians’ attitudes towards religious minorities? Examining the Turkish parliamentary records between 1946 and 1960, this study suggests that perceived security threats significantly contribute to Turkish political parties’ negative descriptions of Armenians. The research analyzes speeches about Armenians via a mixed-method content analysis. The findings demonstrate that (a) debate about security threats is a reliable predictor of the political parties’ negative portrayals, and (b) members of the parliament justify their negative views by labeling Armenians as an enemy. The article concludes that perceived threats evoke negative speeches about Armenians in Turkish politics.
Numerical Analysis of Transient Response in a Single-Pass Cross flow Heat Exchanger

Crossflow heat exchangers are commonly employed in process critical applications in industries. A heat exchanger can be subjected to flow or temperature perturbation during its regular operation. It should be noted that a heat exchanger would require a finite time to overcome such perturbations. In this study, the transient response of a single-pass crossflow heat exchanger with variable inlet temperatures and mass flow rates was determined. Herein, the analysis of the transient performance of cross flow heat exchangers is conducted on a dimensionless basis. In every instance, the energy balance equations were solved using an explicit finite difference method. Numerical predictions were obtained for cases where both the fluids were subjected to step changes in inlet temperature, coupled with step mass flow rate change of the fluids. The analysis can be readily extended to study different flow circuiting and inlet conditions.
Dynamic predictive models of five alkaloids in Coptis during the process of stir-frying with wine using near-infrared spectroscopy

ABSTRACT The goal of this research was to develop dynamic predictive models for five alkaloids in Coptis during the process of stir-frying with wine by near-infrared spectroscopy (NIR). Six batches of samples were collected and then processed on the basis of orthogonal design. With high-performance liquid chromatography (HPLC) analysis as reference, calibration models were generated by a partial least squares (PLS) regression. The root mean square errors of prediction (RMSEP) for the PLS models of jatrorrhizine, epiberberine, coptisine, palmatine, and berberine were 0.0030, 0.0387, 0.0206, 0.0095, and 0.0516, and the correlation coefficients (R) were 99.43%, 98.41%, 99.29%, 99.23%, and 99.87%, respectively. Accordingly, these results demonstrated that the models could be efficiently used to develop robust methods of online analysis and quality control for Coptis.
Sequencing and Annotated of Goat's Milk using Bioinformatics Tool: ClustalX

Bioinformatics tool is a software program made to extract meaningful information from the mass of molecular biology or biological databases and carry out sequence or structural analysis. The method of determining the order of nucleotides within a deoxyribonucleic acid (DNA) molecule is known as DNA sequencing. This analysis is meant to be run to the commercialized or factorymade goat's milk (pasteurised) from various states in Malaysia to identify the milk's authenticity, either it is pure or mixed with other foreign substances from other animals. The main objective is to compare DNA sequences of commercialized and raw goat's milk (handmilking and non-pasteurised). To achieve this, we used ClustalX to align and compare the obtained DNA from both milk samples. The sequences will be aligned using ClustalX software. ClustalX is a provider of an automated system for performing multiple alignments of sequences and profiles and evaluating the outcomes. The usage of ClustalX is helpful as it is cost-effective, user-friendly, and showing a high accuracy of the analysis.
Hyperthermophilic Composting Technology for Organic Solid Waste Treatment: Recent Research Advances and Trends

Organic solid waste is considered a renewable resource that can be converted by various technologies into valuable products. Conventional thermophilic composting (TC), a well-studied and mature technology, can be applied to organic solid waste treatment to achieve waste reduction, mineralization, and humification simultaneously. However, poor efficiency, a long processing period, as well as low compost quality have always limited its wide application. In order to overcome these shortages, hyperthermophilic composting (HTC) has been recently put forward. This paper reviews the basic principle, process flow, operation parameters, research advances, and application status of HTC. Compared with the TC process, the shorter composting period and higher temperature and treatment efficiency, as well as more desirable compost quality, can be achieved during HTC by inoculating the waste with hyperthermophilic microbes. Additionally, HTC can reduce greenhouse gas emission, increase the removal rate of microplastics and antibiotic residues, and achieve in-situ remediation of heavy metal-polluted soils, which greatly improve its application potential for organic solid waste treatment. This paper also proposes the limitations and future prospects of HTC technology for a wider application. As a result, this review advances our understanding of the HTC process, which promotes its further investigation and application.
On the use of a digital twin to enhance femtosecond laser inscription of arbitrary phase patterns

Thanks to the non-linear nature of laser-matter interaction, the use of femtosecond lasers offers a versatile method for encoding information and modifying transparent materials in their volumes and this, with sub-micron resolution. The underlying physical process is a succession of intricate and complex nonlinear phenomena that are sensitive to multiple and multidimensional parameters, such as beam intensity distribution, exposure dose homogeneity and pulse-overlapping sequences as well as propagating wavefront angular orientations and temporal distortions. As a consequence to this inherent and often overwhelming complexity, obtaining a repeatable and accurate result relies strongly on time-consuming machine-specific calibration and experiment-specific fine-tuning attempts until the desired result is reached. Here, we present a digital twin of the processed specimen that not only accurately predicts the exposure outcome in terms of introduced retardance, but also offers a pathway for designing feedforward schemes that compensate for known inaccuracies. We demonstrate the merit of this approach through illustrative examples of arbitrary phase patterns, forming waveplates and images, based on refractive index modulation induced during laser exposure.
Investigating a multiple mediated-effects model of instructional leadership and teacher professional learning in the Malaysian School Context: A partial least squares analysis

The poor student performance in the Programme for International Student Assessment has urged the Malaysian authorities to upskill teachers’ professional learning. However, little is known about how instructional leadership contributes to teacher professional learning, especially in the Malaysian context. This study seeks to investigate the direct relationship between principal instructional leadership and teacher professional learning through the mediating effects of teachers’ trust in the principal and self-efficacy in a multiple mediated-effects model. Data were collected from 335 primary and secondary school teachers in Penang, Malaysia. A partial least squares structural equation modelling approach was used for data analysis. The results found that the relationship between principal instructional leadership and teacher professional learning is mediated by teachers’ trust in the principal and self-efficacy. Implications for theory and knowledge are presented.
A robustness evaluation of Bayesian tests for longitudinal data

Abstract Linear mixed models are standard models to analyze repeated measures or longitudinal data under the assumption of normality for random components in the model. Although the mixed models are often used in both frequentist and Bayesian inference, their evaluation from robustness perspective has not received as much attention in Bayesian inference as in frequentist. The aim of this study is to evaluate Bayesian tests in mixed models for their robustness to normality. We use a general class of exponential power distributions, EPD, and particularly focus on testing fixed effects in longitudinal models. The EPD class contains both light and heavy tailed distributions, with normality as a special case. Further, we consider a new paradigm of Bayesian testing decision theory where the hypotheses are formulated as a mixture model, with subsequent testing based on the posterior distribution of the mixture weights. It is shown that the EPD class provides a flexible alternative to normality assumption, particularly in the presence of outliers. Real data applications are also demonstrated.
Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases

Abstract. The Emissions Database for Global Atmospheric Research (EDGAR) estimates the human-induced emission rates on Earth. EDGAR collaborates with atmospheric modelling activities and aids policy in the design of mitigation strategies and in evaluating their effectiveness. In these applications, the uncertainty estimate is an essential component, as it quantifies the accuracy and qualifies the level of confidence in the emission. This study complements the EDGAR emissions inventory by providing an estimation of the structural uncertainty stemming from its base components (activity data, AD, statistics and emission factors, EFs) by (i) associating uncertainty to each AD and EF characterizing the emissions of the three main greenhouse gases (GHGs), namely carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O); (ii) combining them; and (iii) making assumptions regarding the cross-country uncertainty aggregation of source categories. It was deemed a natural choice to obtain the uncertainties in EFs and AD statistics from the Intergovernmental Panel on Climate Change (IPCC) guidelines issued in 2006 (with a few exceptions), as the EF and AD sources and methodological aspects used by EDGAR have been built over the years based on the IPCC recommendations, which assured consistency in time and comparability across countries. On the one hand, the homogeneity of the method is one of the key strengths of EDGAR, on the other hand, it facilitates the propagation of uncertainties when similar emission sources are aggregated. For this reason, this study aims primarily at addressing the aggregation of uncertainties' sectorial emissions across GHGs and countries. Globally, we find that the anthropogenic emissions covered by EDGAR for the combined three main GHGs for the year 2015 are accurate within an interval of −15 % to +20 % (defining the 95 % confidence of a log-normal distribution). The most uncertain emissions are those related to N 2 O from waste and agriculture, while CO 2 emissions, although responsible for 74 % of the total GHG emissions, account for approximately 11 % of global uncertainty share. The sensitivity to methodological choices is also discussed.
The Bergen Shift Work Sleep Questionnaire (BSWSQ) – European Portuguese validation in a sample of shift workers from the paper industry

ABSTRACT Sleep problems are the major reported consequence of working on shifts. The specificity of working on rotating shifts is not always captured by the instruments used in other samples. The Bergen Shift Work Seep Questionnaire (BSWSQ) is a self-report tool able to identify insomnia symptoms’ presence and severity and distinguish differences by shift and rest days/vacations. The aim of the current study was to present preliminary psychometric properties of the European Portuguese version of the BSWSQ. Data from 569 shift workers in a Portuguese paper industry were collected and analysed. The results indicated good internal consistency and significant correlations among insomnia symptoms, depression, anxiety, and stress. The insomnia scores considering the various shifts were significant differents. Almost 63% of the shift workers were classified as having “shift-related insomnia”. ROC analysis found optimal cut-offs for the presence of insomnia in each shift and rest days/vacations. A Confirmatory Factor Analysis showed excellent fit. The BSWSQ seems to be a measure with good psychometric properties, capable of evaluate the presence and severity of insomnia symptoms related to each shift. However, more studies are necessary, specifically with other shift-work samples.
Omics in Major Cereals: Applications, Challenges, and Prospects

Omics technologies, viz., genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal breeding program because they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in cereal-omics promise—in combination with time efficiency—the cost benefits. In this review, we provide a comprehensive overview of the established cereal-omics methods in five major cereals, viz., rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants, (2) high-density transcriptomics data to study gene expression patterns, (3) global and targeted proteome profiling to study protein structure and interaction, (4) metabolomic profiling to quantify organ level small-density metabolites and their composition, and (5) high-resolution high-throughput image-based phenomics approaches are surveyed in this review.
Graphene nanoribbon photogating for graphene-based infrared photodetectors

Graphene—atomically thin carbon sheets with a two-dimensional hexagonal lattice structure—exhibits unusual electronic and optical properties. Photodetectors are a good prospective application of graphene because they should ideally exhibit a broadband photoresponse from the ultraviolet to terahertz regions and high-speed operation, as well as be inexpensive to produce. Numerous methods have been proposed in order to enhance the responsivity of graphene-based photodetectors. Among these methods, photogating is most promising because it can realize the highest performance. Photogating requires photosensitive layers at the vicinity of graphene in order to produce a voltage change. Various photosensitive layers, including quantum dots, Si, InSb, and LiNbO3, are used in the visible to near-, mid-, and long-wavelength IR (NIR, MWIR, and LWIR) regions, respectively. However, the operating wavelength region is determined by the photosensitive layer, which undermines the advantage of broadband operation of the graphene. In this work, graphene nanoribbon (GNR) was used as a photosensitive layer. Graphene transistors were prepared using Si substrates with a SiO2 layer and source and drain electrodes. Single-layer graphene fabricated by chemical vapor deposition was transferred onto this substrate and formed a channel, and GNR was formed on the graphene channel using a solution dispersion method. The photoresponse was measured in the mid- and long-wavelength infrared regions. The photoresponse was found to be enhanced by GNR photogating compared with the photoresponse of devices without GNR. These results are expected to contribute to the development of high-performance broadband IR photodetectors.
Trading Animal Lives: Ten Tricky Issues on the Road to Protecting Commodified Wild Animals

Abstract Wildlife commodification can generate benefits for biodiversity conservation, but it also has negative impacts; overexploitation of wildlife is currently one of the biggest drivers of vertebrate extinction risk. In the present article, we highlight 10 issues that in our experience impede sustainable and humane wildlife trade. Given humanity's increasing demands on the natural world we question whether many aspects of wildlife trade can be compatible with appropriate standards for biodiversity conservation and animal welfare, and suggest that too many elements of wildlife trade as it currently stands are not sustainable for wildlife or for the livelihoods that it supports. We suggest that the onus should be on traders to demonstrate that wildlife use is sustainable, humane, and safe (with respect to disease and invasion risk), rather than on conservationists to demonstrate it is not, that there is a need for a broad acceptance of responsibility and, ultimately, widespread behavior change. We urge conservationists, practitioners, and others to take bold, progressive steps to reach consensus and action.
Acceptance of Society-Level and Individual-Level Preventive Measures during the COVID-19 Pandemic among College Students in Three Societies

Drawing from social domain theory, this study examined people’s evaluation of society-level disease-prevention regulations (e.g., school closure) and personal precautions (e.g., wearing a facemask) during the coronavirus (COVID-19) crisis, as assessed in Spring, 2020. Participants from three countries (United States [US], China, and Japan; N = 528) rated their acceptance of a range of society-level and individual-level preventive measures and then indicated their main reasons for these ratings, which were categorized as moral, societal, personal, and prudential based on social domain theory. Consistent with this theoretical framework, we found both similarities and differences across the three societies. Specifically, we found that, across the three societies, moral considerations predicted higher acceptance of society-level preventive measures, whereas personal considerations predicted lower acceptance of both society-level and individual-level preventive measures. However, a stronger link between societal considerations and higher acceptance of society-level preventive measures was found for Chinese participants than for US and Japanese participants.
Special education funding and teacher turnover

ABSTRACT We exploit differences in state special education funding systems based on special education enrollment (‘bounty systems’) or on total student enrollment (‘census systems’) to assess whether funding systems impact teacher turnover, teacher specialty, special education enrollment, state education spending, average class sizes, and teacher effort. We find that census funding decreases special education enrollment and increases turnover among special education teachers. Relative to their counterparts, special education teachers are 5 percentage points more likely to move across schools and 18 percentage points more likely to switch to general education teaching after the implementation of census funding in their state.