Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and yield components of wheat genotypes as influenced by potassium and farm yard manure on a saline sodic soil.

The adequate supply of mineral nutrients through chemical fertilizers and manure may help to sustain the crop productivity and ensure plant survival under salinity stress. A field study was conducted on saline sodic soil (ECe = 13 dS m -1 , S AR 23.3 (mmol L -1 ) 1/2 , pH = 8.6 of surface 15 cm layer) to quantify the effects of potassium (K) and farm yard manure (FYM) on two wheat genotypes differing in salinity tolerance. Three K levels (0, 80, 120 kg ha -1 ) and two FYM levels (0, 10 t ha -1 ) were tested using randomized compete block design (RCBD) with three replications. The application of K along with FYM reduced Na + uptake and accumulation in plant tissue. The K concentration and K + / Na + ratio were significantly improved in both wheat genotypes with the supplementation of K and FYM. The grain yield was improved by 40-156% in salt tolerant genotype and 46-206% in salt sensitive genotype with added K and FYM. Similar trend was observed in yield components. Ameliorative effects of added K and FYM were more marked in salt sensitive genotype (Auqab-2000) than in salt tolerant (Inqlab-91). Grain yield of salt sensitive and salt tolerant wheat genotypes was positively correlated with leaf K + concentration determined at various treatments. Addition of K along with FYM decreased sodium adsorption ratio (SAR) and electrical conductivity (EC) of soil particularly in upper layers. Therefore, it is concluded that K along with FYM could help to alleviate deleterious effects of salts and thus improve the productivity of salt affected soils.
Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence

The societal and ethical implications of the use of opaque artificial intelligence systems in consequential decisions, such as welfare allocation and criminal justice, have generated a lively debate among multiple stakeholders, including computer scientists, ethicists, social scientists, policy makers, and end users. However, the lack of a common language or a multi-dimensional framework to appropriately bridge the technical, epistemic, and normative aspects of this debate nearly prevents the discussion from being as productive as it could be. Drawing on the philosophical literature on the nature and value of explanations, this paper offers a multi-faceted framework that brings more conceptual precision to the present debate by identifying the types of explanations that are most pertinent to artificial intelligence predictions, recognizing the relevance and importance of the social and ethical values for the evaluation of these explanations, and demonstrating the importance of these explanations for incorporating a diversified approach to improving the design of truthful algorithmic ecosystems. The proposed philosophical framework thus lays the groundwork for establishing a pertinent connection between the technical and ethical aspects of artificial intelligence systems.
Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts

Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations that build and deploy automated decision-support systems. They are modeled after impact assessments in other domains. Our study of the history of impact assessments shows that "impacts" are an evaluative construct that enable actors to identify and ameliorate harms experienced because of a policy decision or system. Every domain has different expectations and norms around what constitutes impacts and harms, how potential harms are rendered as impacts of a particular undertaking, who is responsible for conducting such assessments, and who has the authority to act on them to demand changes to that undertaking. By examining proposals for AIAs in relation to other domains, we find that there is a distinct risk of constructing algorithmic impacts as organizationally understandable metrics that are nonetheless inappropriately distant from the harms experienced by people, and which fall short of building the relationships required for effective accountability. As impact assessments become a commonplace process for evaluating harms, the FAccT community, in its efforts to address this challenge, should A) understand impacts as objects that are co-constructed accountability relationships, B) attempt to construct impacts as close as possible to actual harms, and C) recognize that accountability governance requires the input of various types of expertise and affected communities. We conclude with lessons for assembling cross-expertise consensus for the co-construction of impacts and building robust accountability relationships.
Mocasin—Rapid Prototyping of Rapid Prototyping Tools: A Framework for Exploring New Approaches in Mapping Software to Heterogeneous Multi-cores

We present Mocasin, an open-source rapid prototyping framework for researching, implementing and validating new algorithms and solutions in the field of mapping software to heterogeneous multi-cores. In contrast to the many existing tools that often specialize for a particular use-case, Mocasin is an open, flexible and generic research environment that abstracts over the approaches taken by other tools. Mocasin is designed to support a wide range of models of computation and input formats, implements manifold mapping strategies and provides an adjustable high-level simulator for performance estimation. This infrastructure serves as a flexible vehicle for exploring new approaches and as a blueprint for building customized tools. We highlight the key design aspects of Mocasin that enable its flexibility and illustrate its capabilities in a case-study showing how Mocasin can be used for building a customized tool for researching runtime mapping strategies in an LTE uplink receiver.
Fifty Shades of Grey: In Praise of a Nuanced Approach Towards Trustworthy Design

Environmental data science is uniquely placed to respond to essentially complex and fantastically worthy challenges related to arresting planetary destruction. Trust is needed for facilitating collaboration between scientists who may share datasets and algorithms, and for crafting appropriate science-based policies. Achieving this trust is particularly challenging because of the numerous complexities, multi-scale variables, interdependencies and multi-level uncertainties inherent in environmental data science. Virtual Labs---easily accessible online environments provisioning access to datasets, analysis and visualisations---are socio-technical systems which, if carefully designed, might address these challenges and promote trust in a variety of ways. In addition to various system properties that can be utilised in support of effective collaboration, certain features which are commonly seen to benefit trust---transparency and provenance in particular---appear applicable to promoting trust in and through Virtual Labs. Attempting to realise these features in their design reveals, however, that their implementation is more nuanced and complex than it would appear. Using the lens of affordances, we argue for the need to carefully articulate these features, with consideration of multiple stakeholder needs on balance, so that these Virtual Labs do in fact promote trust. We argue that these features not be conceived as widgets that can be imported into a given context to promote trust; rather, whether they promote trust is a function of how systematically designers consider various (potentially conflicting) stakeholder trust needs.
Building and Auditing Fair Algorithms: A Case Study in Candidate Screening

Academics, activists, and regulators are increasingly urging companies to develop and deploy sociotechnical systems that are fair and unbiased. Achieving this goal, however, is complex: the developer must (1) deeply engage with social and legal facets of "fairness" in a given context, (2) develop software that concretizes these values, and (3) undergo an independent algorithm audit to ensure technical correctness and social accountability of their algorithms. To date, there are few examples of companies that have transparently undertaken all three steps. In this paper we outline a framework for algorithmic auditing by way of a case-study of pymetrics, a startup that uses machine learning to recommend job candidates to their clients. We discuss how pymetrics approaches the question of fairness given the constraints of ethical, regulatory, and client demands, and how pymetrics' software implements adverse impact testing. We also present the results of an independent audit of pymetrics' candidate screening tool. We conclude with recommendations on how to structure audits to be practical, independent, and constructive, so that companies have better incentive to participate in third party audits, and that watchdog groups can be better prepared to investigate companies.
A Semiotics-based epistemic tool to reason about ethical issues in digital technology design and development

One of the important challenges regarding the development of morally responsible and ethically qualified digital technologies is how to support designers and developers in producing those technologies, especially when conceptualizing their vision of what the technology will be, how it will benefit users, and avoid doing harm. However, traditional software design and development life cycles do not explicitly support the reflection upon either ethical or moral issues. In this paper we look at how a number of ethical issues may be dealt with during digital technology design and development, to prevent damage and improve technological fairness, accountability, and transparency. Starting from mature work on semiotic theory and methods in human-computer interaction, we propose to extend the core artifact used in semiotic engineering of human-centered technology design, so as to directly address moral responsibility and ethical issues. The resulting extension is an epistemic tool, that is, an instrument to create and elaborate on this specific kind of knowledge. The paper describes the tool, illustrates how it is to be used, and discusses its promises and limitations against the background of related work. It also includes proposed empirical studies, accompanied by briefly described methodological challenges and considerations that deserve our attention.
Superior Bifunctional Electrocatalytic Activity of Ba0.5Sr0.5Co0.8Fe0.2O3‐δ/Carbon Composite Electrodes: Insight into the Local Electronic Structure

By using X-ray absorption near edge structure spectroscopy (XANES), changes in the local electronic structure of the perovskite have been observed when a composite perovskite/ carbon electrode is developed. This ﬁ nding provides a novel understanding of perovskite/carbon composite electrodes and thus opens new perspectives for the optimization of the composite electrodes or for tailoring new perovskite compositions. Furthermore, our results also indicate that the electrode preparation process can deeply change the perovskite electronic structure. This should be always carefully taken into account in order to develop a proper electronic structure/catalytic activity correlation for this class of compounds. The selected perovskite composition for this study is Ba 3- (BSCF) since this perovskite has already been shown to be a promising bifunctional catalyst (i.e., high ORR and OER activity) in combination with carbon but not as a single perovskite catalyst. [ 6,7,14–16,20 ] BSCF was prepared by a sol–gel combustion method, and after calcination
Diving in hot water: a meta-analytic review of how diving vertebrate ectotherms will fare in a warmer world

ABSTRACT Diving ectothermic vertebrates are an important component of many aquatic ecosystems, but the threat of climate warming is particularly salient to this group. Dive durations typically decrease as water temperatures rise; yet, we lack an understanding of whether this trend is apparent in all diving ectotherms and how this group will fare under climate warming. We compiled data from 27 studies on 20 ectothermic vertebrate species to quantify the effect of temperature on dive durations. Using meta-analytic approaches, we show that, on average, dive durations decreased by 11% with every 1°C increase in water temperature. Larger increases in temperature (e.g. +3°C versus +8–9°C) exerted stronger effects on dive durations. Although species that respire bimodally are projected to be more resilient to the effects of temperature on dive durations than purely aerial breathers, we found no significant difference between these groups. Body mass had a weak impact on mean dive durations, with smaller divers being impacted by temperature more strongly. Few studies have examined thermal phenotypic plasticity (N=4) in diving ectotherms, and all report limited plasticity. Average water temperatures in marine and freshwater habitats are projected to increase between 1.5 and 4°C in the next century, and our data suggest that this magnitude of warming could translate to substantial decreases in dive durations, by approximately 16–44%. Together, these data shed light on an overlooked threat to diving ectothermic vertebrates and suggest that time available for underwater activities, such as predator avoidance and foraging, may be shortened under future warming. Summary: Using meta-analytic approaches, we show that diving ectothermic vertebrates are particularly vulnerable to climate warming. On average, dive durations decreased by 11% with every 1°C increase in water temperature.
Crystal structure–physical property relationships in perovskites

Les structures cristallines de sept composes de structure perovskites sont analysees du point de vue du polyedre de coordination de cation. L'analyse indique qu'un compose ABO 3 de structure perovskite peut etre ferroelectrique si le rapport du volume de l'ion A cuboctaedrique et celui de l'ion B octaedrique vaut exactement S et s'il y a volume d'ion B octaedrique minimum associe aux proprietes ferroelectriques. Application de la methode a PbZrO 3 TiO 3 et PbZnNbO 3
Selective modification of the β-β linkage in DDQ-treated Kraft lignin analysed by 2D NMR spectroscopy

The depolymerisation of the biopolymer lignin has the potential to provide access to a range of high value and commodity chemicals. However, research in this increasingly important area of green chemistry is hindered by the lack of analytical methods. The key challenge in using NMR is the throughput that can be achieved without the need for high field spectrometers fitted with cryoprobes. Here, we report the use of a relatively fast 2D HSQC NMR experiment performed on a 500 MHz spectrometer fitted with a BBFO+ probe to obtain high quality spectra. The use of the developed protocol to study the selective modification of the β–β linkage in Kraft lignin is also reported.
Automatic Image Checkpoint Selection for Guider‐Follower Pedestrian Navigation

In recent years guider‐follower approaches show a promising solution to the challenging problem of last‐mile or indoor pedestrian navigation without micro‐maps or indoor floor plans for path planning. However, the success of such guider‐follower approaches is highly dependent on a set of manually and carefully chosen image or video checkpoints. This selection process is tedious and error‐prone. To address this issue, we first conduct a pilot study to understand how users as guiders select critical checkpoints from a video recorded while walking along a route, leading to a set of criteria for automatic checkpoint selection. By using these criteria, including visibility, stairs and clearness, we then implement this automation process. The key behind our technique is a lightweight, effective algorithm using left‐hand‐side and right‐hand‐side objects for path occlusion detection, which benefits both automatic checkpoint selection and occlusion‐aware path annotation on selected image checkpoints. Our experimental results show that our automatic checkpoint selection method works well in different navigation scenarios. The quality of automatically selected checkpoints is comparable to that of manually selected ones and higher than that of checkpoints by alternative automatic methods.
Performance analysis of shunt active filter for harmonic compensation under various non-linear loads

Abstract This paper shows the motivation towards the development of a dq-Proportional Resonant (PR) control strategy in shunt active power filter design for eliminations of distortions in source currents for different loading conditions. The switching signals for the inverter of shunt active power filter (APF) have been generated by the hysteresis current control scheme. The controller performance has been verified by using different types of loads such as non-linear balanced, unbalanced and variable etc., with the system in MATLAB/Simulink environment. An experimental prototype has also been developed in the laboratory and results are analyzed to validate the efficacy of the proposed controller.
Error Analysis of Nonlinear Time Fractional Mobile/Immobile Advection-Diffusion Equation with Weakly Singular Solutions

In this paper, a weighted and shifted Grünwald-Letnikov difference (WSGD) Legendre spectral method is proposed to solve the two-dimensional nonlinear time fractional mobile/immobile advection-dispersion equation. We introduce the correction method to deal with the singularity in time, and the stability and convergence analysis are proven. In the numerical implementation, a fast method is applied based on a globally uniform approximation of the trapezoidal rule for the integral on the real line to decrease the memory requirement and computational cost. The memory requirement and computational cost are O ( Q ) and O ( QK ), respectively, where K is the number of the final time step and Q is the number of quadrature points used in the trapezoidal rule. Some numerical experiments are given to confirm our theoretical analysis and the effectiveness of the presented methods.
Crystal Structure, Energetics, And Electrochemistry of Li2FeSiO4 Polymorphs from First Principles Calculations

The influence of crystal structure and relative stability on the electrochemical properties of Li2FeSiO4 polymorphs as cathode materials for Li-ion batteries is investigated. Six Li2FeSiO4 forms related to the crystal structure of Li3PO4 have been considered: three known polymorphs crystallizing in layered structures (with space groups P21, Pmnb, and Pmn21) and three forms reported for other LiMSiO4 materials crystallizing in three-dimensional (3D) frameworks (with space groups Pmn21, Pbn21, and P21/n). While Li2FeSiO4 polymorphs are very close in energy, their energies begin to differ substantially upon removal of Li, rendering those with lower electrostatic energy more stable. The change in relative stability of polymorphs upon delithiation results in a driving force for a phase transformation of the exiting two-dimensional (2D)-Li2FeSiO4 polymorphs to a more stable structure having a 3D network of [SiO4] and [FeO4] tetrahedra. The resulting phase exhibits a voltage plateau that is predicted to be 0.3 V.
Polycondensates of 2′‐(Chalcone‐4‐Oxy)Ethyl‐3,5‐Diaminobenzoate with Some Aromatic Dicarboxylic Acids

A new set of polycondensates with –CO–NH– groups was synthesized by the direct reaction of 2′‐(chalcone‐4‐oxy)ethyl 3,5‐diaminobenzoate with various aromatic dicarboxylic acids using phosphorylation protocol. The polymers were produced in high yields and with moderate inherent viscosities (0.62–0.76 dL/g). The obtained polyamides were essentially amorphous as revealed by differential scanning calorimetry (DSC) and X‐ray diffraction (XRD) measurements and are readily soluble in a variety of aprotic polar solvents affording films from their solutions. They showed glass‐transition temperatures ranging from 216 to 254°C and were thermally stable with 10% weight loss temperatures over 380°C, in nitrogen atmosphere. UV spectroscopy was used in order to confirm the presence of oxyethylchalconyl pendant group in the polymer structures.
A COMPARISON OF VOLATILE COMPONENTS OF FLOWER OF PAGE MANDARIN OBTAINED BY ULTRASOUND-ASSISTED EXTRACTION AND HYDRODISTILLATION

Traditional hydrodistillation (HD) and ultrasound-assisted extraction method (UAE) have been compared and evaluated for their quantitative and qualitative compositions of the isolated essential oil from fresh page mandarin flowers. Thirty-eight flower components and twenty-nine flower components in the UAE and HD method, respectively including: aldehydes, alcohols, ketons, monoterpenes, sesquiterpenes and other components were indentified and quantified. The major flavor components of oil obtained by UAE were β-sinensal, α-sinensal, linalool, limonene, sabinene, ocimene, (z)-β-farnesene and E,E-α-farnesene. The major flavor components of oil obtained by HD were β-sinensal, α-sinensal, linalool, limonene, sabinene, ocimene and terpinene-4-ol. The UAE method offers important advantages over HD method, namely: provides a higher amount of oxygenated compounds. It offers also the possibility for a better reproduction of natural aroma of the essential oil from page mandarin flowers than the HD method. UAE method showed the highest content of aldehydes and alcohols. Since the aldehydes and alcohols content of citrus oil is considered as one of the more important indicators of high quality, method apparently has a profound influence on Page Mandarin oil quality. Key words: Page mandarin flower, ultrasound-assisted extraction, hydrodistillation, oxygenated components.
Hexagonal orthovanadates as catalysts in the oxidation of methanol to formaldehyde

Improved selectivities are obtained in the catalytic oxidation of methanol to formaldehyde using hexagonal orthovanadates of the type Sr3–xLa2x/3(VO4)2(x = 0.3–1.5) in comparison with those using the strontium and lanthanum orthovanadates separately.
A Privacy Preserving and Efficient Multi Authority - CP-ABE Scheme for Secure Cloud Communication

In the cloud computing environment, Multi authority Ciphertext Policy-Attribute Based Encryption (CP-ABE) schemes are used as a key escrow free solution to securely and efficiently share data over cloud. However, the length of ciphertext in existing Multi Authority-CP-ABE schemes increases with the number of attributes in the access policy. Moreover, these schemes do not protect against dishonest attribute authorities. In this paper, a constant length ciphertext Multi Authority-CP-ABE scheme is proposed that reduces the communication overhead over the network. The scheme also prevents dishonest authority from compromising the system. Apart from this, for enhanced privacy of receivers, the access policy is communicated in hidden form. Thus, the presented scheme provides an efficient corrupt resistant, key escrow free Multi Authority-CP-ABE scheme by generating constant length ciphertext and hidden access structure. Results demonstrate the enhanced security and reduced cost of encryption and decryption by 8% and 48% respectively as compared to other existing works.