Biosorption of Lithium using Microbes

Lithium (Li) is a very valuable metal that is used across several industries including ceramics, glass, batteries, pharmaceuticals, and polymers. However, in recent years, the global demand for Li and its market price have increased considerably, due to its application as a critical component in the production of rechargeable Li-ion batteries and energy storage systems that are used in electric vehicles and a variety of electronic devices. Although Li occurs as a mineral in hard rocks and salt brines, substantial amounts are found in our environment as part of industrial wastes and oil-field wastewaters. Despite its importance, Li is also harmful and poses a risk to the environment. Besides, the conventional (chemical and physical) methods that are used today for its removal, such as solvent extraction and acid leaching, require high energy consumption and produce toxic by-products, posing additional environmental and economic challenges. Alternatively, the use of bacteria for Li extraction has been proposed as a viable, non-toxic, and cost- effective alternative. In this study, the potential of using Gram-negative Escherichia coli, and Gram-positive Bacillus subtilis and Bacillus cereus as biosorbents for Li was explored. Results indicate that all three bacterial species tested were capable of absorbing Li to varying degrees from aqueous solutions. However, E. coli had the highest and most consistent absorption capacity and was selected for further investigation. Amounts of total dissolved solids (TDS) and Li, analyzed by inductively coupled plasma atomic emission spectroscopy (ICP-OES), methods were obtained in this study. In a kinetic study of Li biosorption, most Li-binding occurred within the first 24 h and slowed down until maximum biosorption was attained following 72 h, our experimental endpoint. The biosorption capacity for E. coli ranged from 60% to 43% depending on initial Li concentrations in solution. Also, the optimal pH for E. coli biosorption was found to be between pH 6-6.5. Recovered/eluted absorbed Li was measured following a 12 h mild-acid solution (distilled H2O adjusted to pH 4 with HNO3) wash of the Li-bound biomass membranes

Environmental Disclosure and Share Price Performance

Background: Businesses are working to create sustainability plans and give investors non-financial data reports that capture other aspects that aren\u27t covered in regular financial reports because they now have a broader perspective than just making a profit. This study underscores the importance of addressing the environmental and social disclosure and share price performance of firms in Nigeria. Purpose: The objective of the study was to investigate whether environmental reporting, social reporting, governance reporting and environmental and social governance have significant effect on share price performance of listed conglomerate firms in Nigeria. Methods: The secondary source of data collection was adopted in the study where the purposive sampling technique was used to select a sample size of ten (10) selected firms for the study. Least Square regression analysis was used in this study. Results: The findings revealed that social reporting have no significant effect on share price performance while environmental reporting, governance reporting environmental and social governance has significant effect on share price performance of listed conglomerate firms in Nigeria. Conclusions: It was concluded that the since environment where human being lives are being distorted with substances that are dangerous to his life, the need for sustainability has resulted in the appearance of various international organizations expressing a range of attitudes that guide and direct human dealings with the environment. Finally, it was recommended that there is need for investors and analysts to utilize indicators that factor the social and environmental issues into context prior to investment advice or decisions. Keywords: Environmental reporting, social disclosure, share price performance, environmental reporting, socialreporting, governmental reporting, environmental and social governanc

ENVIRONMENTAL ACCOUNTING REPORTING AND MANAGEMENT OF FRAUD OF LISTED AGRICULTURAL FIRMS IN NIGERIA

This study examined environmental accounting reporting and management fraud of listed agricultural firms in Nigeria. The objective of the study was to investigate whether emission reporting, effluent and waste reporting, compliance to environmental laws and biodiversity reporting have significant effect on management fraud. The secondary source of data collection was adopted in the study where the purposive sampling technique was used to select a sample size of four (4) listed agricultural firms for the study. Least Square regression analysis was used in this study and the findings revealed that emission reporting, effluent and waste reporting, compliance to environmental laws and biodiversity reporting has significant effect on management fraud. Finally, it recommended that priority should be given to policies regarding emission and energy management to promote optimal energy consumption. A careful mix of such policies should be considered as over-appropriation or under appropriation may lead financial misappropriation

SemanticLock: An authentication method for mobile devices using semantically-linked images

We introduce SemanticLock, a single factor graphical authentication solution for mobile devices. SemanticLock uses a set of graphical images as password tokens that construct a semantically memorable story representing the user`s password. A familiar and quick action of dragging or dropping the images into their respective positions either in a \textit{continous flow} or in \textit{discrete} movements on the the touchscreen is what is required to use our solution. The authentication strength of the SemanticLock is based on the large number of possible semantic constructs derived from the positioning of the image tokens and the type of images selected. Semantic Lock has a high resistance to smudge attacks and it equally exhibits a higher level of memorability due to its graphical paradigm. In a three weeks user study with 21 participants comparing SemanticLock against other authentication systems, we discovered that SemanticLock outperformed the PIN and matched the PATTERN both on speed, memorability, user acceptance and usability. Furthermore, qualitative test also show that SemanticLock was rated more superior in like-ability. SemanticLock was also evaluated while participants walked unencumbered and walked encumbered carrying "everyday" items to analyze the effects of such activities on its usage

Biomove: Biometric user identification from human kinesiological movements for virtual reality systems

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Virtual reality (VR) has advanced rapidly and is used for many entertainment and business purposes. The need for secure, transparent and non-intrusive identification mechanisms is important to facilitate users’ safe participation and secure experience. People are kinesiologically unique, having individual behavioral and movement characteristics, which can be leveraged and used in security sensitive VR applications to compensate for users’ inability to detect potential observational attackers in the physical world. Additionally, such method of identification using a user’s kinesiological data is valuable in common scenarios where multiple users simultaneously participate in a VR environment. In this paper, we present a user study (n = 15) where our participants performed a series of controlled tasks that require physical movements (such as grabbing, rotating and dropping) that could be decomposed into unique kinesiological patterns while we monitored and captured their hand, head and eye gaze data within the VR environment. We present an analysis of the data and show that these data can be used as a biometric discriminant of high confidence using machine learning classification methods such as kNN or SVM, thereby adding a layer of security in terms of identification or dynamically adapting the VR environment to the users’ preferences. We also performed a whitebox penetration testing with 12 attackers, some of whom were physically similar to the participants. We could obtain an average identification confidence value of 0.98 from the actual participants’ test data after the initial study and also a trained model classification accuracy of 98.6%. Penetration testing indicated all attackers resulted in confidence values of less than 50% (\u3c50%), although physically similar attackers had higher confidence values. These findings can help the design and development of secure VR systems

Biomove: Biometric user identification from human kinesiological movements for virtual reality systems

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Virtual reality (VR) has advanced rapidly and is used for many entertainment and business purposes. The need for secure, transparent and non-intrusive identification mechanisms is important to facilitate users’ safe participation and secure experience. People are kinesiologically unique, having individual behavioral and movement characteristics, which can be leveraged and used in security sensitive VR applications to compensate for users’ inability to detect potential observational attackers in the physical world. Additionally, such method of identification using a user’s kinesiological data is valuable in common scenarios where multiple users simultaneously participate in a VR environment. In this paper, we present a user study (n = 15) where our participants performed a series of controlled tasks that require physical movements (such as grabbing, rotating and dropping) that could be decomposed into unique kinesiological patterns while we monitored and captured their hand, head and eye gaze data within the VR environment. We present an analysis of the data and show that these data can be used as a biometric discriminant of high confidence using machine learning classification methods such as kNN or SVM, thereby adding a layer of security in terms of identification or dynamically adapting the VR environment to the users’ preferences. We also performed a whitebox penetration testing with 12 attackers, some of whom were physically similar to the participants. We could obtain an average identification confidence value of 0.98 from the actual participants’ test data after the initial study and also a trained model classification accuracy of 98.6%. Penetration testing indicated all attackers resulted in confidence values of less than 50% (\u3c50%), although physically similar attackers had higher confidence values. These findings can help the design and development of secure VR systems

Diagnóstico energético de República Dominicana 2015

En el marco del proyecto de "Desarrollo de Capacidades de Planificación", OLADE, con el apoyo financiero del Gobierno de Canadá, desarrolló un Manual de Planificación Energética estandarizado para ser aplicado en la región. OLADE ha implementado este manual mediante diversas actividades de planificación enfocadas en la realidad nacional de cada país, utilizando talleres altamente participativos que requieren la involucración directa del equipo de Planificación Energética del país beneficiario y de los principales actores del sector energético. República Dominicana, como país beneficiario del proyecto, aplica los principios básicos y lineamientos del Manual en el desarrollo de las etapas de la planificación energética. La primera fase del proyecto incluyó el desarrollo del Diagnóstico Energético Nacional, un documento de alto valor técnico elaborado por funcionarios de la Comisión Nacional de Energía. Este documento fue socializado y discutido con distintas instituciones del sector energético para consolidar la problemática y el estado actual de los diferentes subsectores energéticos de República Dominicana

Cadena de producción sustentable de bioqueroseno en la América Latina y el Caribe vinculada a los territorios rurales

La presente publicación constituye una contribución para visualizar un modelo conceptual por medio del cual, los segmentos de población urgidos de acceso a oportunidades de desarrollo, sustentabilidad e inclusión social en los territorios rurales de América Latina y el Caribe, se beneficiarían con una o varias soluciones de innovación en la cadena de valor de bioqueroseno. Para arribar a este modelo se inicia con un detalle de los aspectos generales y de los escenarios actuales del bioqueroseno para la aviación comercial, seguido de un análisis conceptual de competitividad, sustentabilidad y vinculación de la cadena de valor de bioqueroseno en los territorios rurales. Finaliza con una sección de conclusiones desde el enfoque de las oportunidades y desafíos para los eslabones de dicha cadena de valor. Se espera que el escenario sea propicio para el lanzamiento de una iniciativa en procura de la consolidación de una plataforma intensiva de conocimiento para la innovación agrícola y la sustentabilidad en la cadena de valor de biodiesel y biokeroseno, ante la comunidad de los principales actores del desarrollo tecnológico, promoción, utilización y mercado de los biocombustibles en América Latina y el Caribe, por cuanto el evento regional de biocombustibles congrega representantes de entidades que realizan investigación de tecnologías avanzadas además de entidades que apoyan el desarrollo agrícola rural, empresas de negocios y autoridades de los sectores energético, agrícola, industrial, ambiental, comercial y educativo de la Región y de Organismos Internacionales de Cooperación Técnica