Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECT OF WORKFORCE DIVERSITY ON EMPLOYEE PERFORMANCE IN NIGERIAN BANKING INDUSTRY(A STUDY OF FIRSTBANK NIGERIA LTD., OTA BRANCH)

The purpose of this paper is to examine the effects of workforce diversity on employee performance. The survey research design method was adopted for the paper. The instrument used to gather relevant data for the study was the questionnaire. The study centred on the Nigerian Banking Sector to examine the level of diversity practiced in terms of gender, age, ethnicity and educational in Nigerian Organizations. First Bank of Nigeria Plc, Ota, Ogun State was the focal organization. A total of 81 copies of questionnaire were disseminated to the respondents of the study and they were all filled and returned and also relevant for the study. In order to attain the research objectives, four hypotheses were created. The data were collated and analyzed using the Statistical Package for Social Sciences (SPSS) percentages and frequencies tables were used to for the descriptive aspects. To test the hypotheses, Spearman Rank Correlation Coefficient Analysis was adopted, Regression Model, Anova were adopted to examine the relationship between variables and identify the influence of the independent variables on the dependent variable. The limitation to the study is that the study made use of only few aspects of workforce diversity and as such, findings can not be generalized to cover other dimensions of diversity not covered in the study. The research findings showed all aspects of workforce diversity used in the study has a significant relationship with employee performance except for ethnic diversity. It was also discovered that gender, age and educational diversity have strong influence on employee performance. Hence, based on findings, it is recommended that management continue to uphold its diversity policies and practices in order to increase the benefits of diversity. Management should ensure that all employees are properly trained on diversity issues as these trainings will also help employees to change those unconscious behaviours that hinder diversity and inclusion practices. This study will add to the already existing literature on diversity and it will help First Bank, other organizations, employees, government and the society as a whole to fully understand diversity issues, how to manage it and how to reap the benefits.
In Which Situations Do We Eat? A Diary Study on Eating Situations and Situational Stability

Eating situations are crucial for understanding and changing eating behavior. While research on individual situational dimensions exists, little is known about eating situations as a whole. This study aimed to fill this gap by identifying eating situations as combinations of multiple situational dimensions and describing how stable individuals eat in those situations. In a five-day online diary study, 230 participants reported a total of 2461 meals and described the corresponding eating situation using predefined situational dimensions. Divisive hierarchical cluster analyses were conducted separately for breakfast, lunch, and dinner, resulting in unique cluster solutions that characterized the most common eating situations. The most common breakfast situations were characterized by a combination of the dimensions social, affect, and hunger. The most common lunch and dinner situations were characterized by varying combinations of the dimensions social, affect, and activity. Based on the identified situations, a situational stability index was developed to describe how stable individuals eat in the same situations. The findings suggest high interindividual differences in situational stability, which were associated with socio-demographic characteristics like age or employment. This study enhances our understanding of the situational aspects of eating behavior while offering tools to describe eating situations and situational stability.
From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?

We examine the challenging “marriage” between computational efficiency and biological plausibility—A crucial node in the domain of spiking neural networks at the intersection of neuroscience, artificial intelligence, and robotics. Through a transdisciplinary review, we retrace the historical and most recent constraining influences that these parallel fields have exerted on descriptive analysis of the brain, construction of predictive brain models, and ultimately, the embodiment of neural networks in an enacted robotic agent. We study models of Spiking Neural Networks (SNN) as the central means enabling autonomous and intelligent behaviors in biological systems. We then provide a critical comparison of the available hardware and software to emulate SNNs for investigating biological entities and their application on artificial systems. Neuromorphics is identified as a promising tool to embody SNNs in real physical systems and different neuromorphic chips are compared. The concepts required for describing SNNs are dissected and contextualized in the new no man’s land between cognitive neuroscience and artificial intelligence. Although there are recent reviews on the application of neuromorphic computing in various modules of the guidance, navigation, and control of robotic systems, the focus of this paper is more on closing the cognition loop in SNN-embodied robotics. We argue that biologically viable spiking neuronal models used for electroencephalogram signals are excellent candidates for furthering our knowledge of the explainability of SNNs. We complete our survey by reviewing different robotic modules that can benefit from neuromorphic hardware, e.g., perception (with a focus on vision), localization, and cognition. We conclude that the tradeoff between symbolic computational power and biological plausibility of hardware can be best addressed by neuromorphics, whose presence in neurorobotics provides an accountable empirical testbench for investigating synthetic and natural embodied cognition. We argue this is where both theoretical and empirical future work should converge in multidisciplinary efforts involving neuroscience, artificial intelligence, and robotics.
On the Contribution of EMIC Waves to the Reconfiguration of the Relativistic Electron Butterfly Pitch Angle Distribution Shape on 2014 September 12—A Case Study

Following the arrival of two interplanetary coronal mass ejections on 2014 September 12, the Relativistic Electron–Proton Telescope instrument on board the twin Van Allen Probes observed a long-term dropout in the outer belt electron fluxes. The interplanetary shocks compressed the magnetopause, thereby enabling the loss of relativistic electrons in the outer radiation belt to the magnetosheath region via the magnetopause shadowing. Previous studies have invoked enhanced radial transport associated with ultra-low-frequency waves activity and/or scattering into the atmosphere by whistler mode chorus waves to explain electron losses deep within the magnetosphere (L < 5.5). We show that energetic electron pitch angle distributions (PADs) provide strong evidence for precipitation also via interaction with electromagnetic ion cyclotron (EMIC) waves. High-resolution magnetic field observations on Van Allen Probe B confirm the sporadic presence of EMIC waves during the most intense dropout phase on September 12. Observational results suggest that magnetopause shadowing and EMIC waves together were responsible for reconfiguring the relativistic electron PADs into peculiar butterfly PAD shapes a few hours after an interplanetary shock arrived at Earth.
Groundwater-surface water interactions at a fen margin: hydrological controls on the micro-habitat of an indicator snail species Vertigo geyeri.

Pollardstown fen is an important groundwater-dependent ecosystem in eastern Ireland. One of the ecological features of the fen is the rare snail species Vertigo geyeri, which is protected under the European Union Habitats Directive. A major study in the period 2002―2005 focused on establishing the micro-meteorological and micro-hydrological requirements for this indicator snail species at Pollardstown fen. It was shown that high relative humidity (above 80%) and close proximity to a phreatic water surface (approximately 0.1 m below ground surface) are important for maintaining snail populations. A study of the groundwater inflows to the fen, involving measurements of vertical and lateral hydraulic gradients, coupled with an evaluation of soil thermodynamics and meteorological observations, suggested that the hydrological regime of the fen is sensitive to both the groundwater inflow rate and the transpiration process of the wetland vegetation. Local topography and geomorphology are important considerations when deciding on the extent of potential snail conservation areas, as the long-term viability of conservation sites is likely to be greater in areas with gentle slopes that allow seepages to emerge at lower levels, if such seepages are reduced or lost at higher elevations.
THE IMPACT OF ANIMAL RIGHTS ON WILDLIFE CONSERVATION AND MANAGEMENT IN KENYA

ii Acknowledgements and dedication iv List of figures vi List of organizations and agencies vii Chapter 1 – Introduction 1 Chapter 2 – A History of Animal Rights 34 Chapter 3 – The Animal rights network in Kenya; the analytical terrain 74 Chapter 4 – Impact of Animal rights in conservation management and Kenya 122 Chapter 5 – Diagnosing a change in conservation; tactics, and Emotional pressure 167 Chapter 6 – The passage of rights in Africa 201
Self-Writing xnor Magnetic Random Access Memory for Binary Neural Network Acceleration

A XNOR circuit is proposed using a spin-transfer torque magnetic random access memory (STT-MRAM) array for weight-stationary binarized neural network (BNN) acceleration. The proposed circuit allows the memory array to perform XNOR operations using a self-writing technique in that the previous state of the bit-cell is used to modify the current bit-cell content. The proposed self-writing technique re-utilizes the standard memory infrastructure and requires only two additional CMOS switches per column. Also, the non-volatility of the STT-MRAM reduces the XNOR computation as well as energy on non-writing XNOR computation. A $64\,\, {}\times {}16$ in-MRAM XNOR macro is designed and evaluated using a compact magnetic tunnel junction (MTJ) model, targeting an implementation in a 14 nm technology node. Analysis indicates that the proposed design succeeds in reducing the energy by 26.7% while maintaining the conventional bit-cell structure.
University of Birmingham Kernel truncated regression representation for robust subspace clustering

Subspace clustering aims to group data points into multiple clusters of which each corresponds to one subspace. Most existing subspace clustering approaches assume that input data lie on linear subspaces. In practice, however, this assumption usually does not hold. To achieve nonlinear subspace clustering, we propose a novel method, called kernel truncated regression representation. Our method consists of the following four steps: 1) projecting the input data into a hidden space, where each data point can be linearly represented by other data points; 2) calculating the linear representation coeﬃcients of the data representations in the hidden space; 3) truncating the trivial coeﬃcients to achieve robustness and block-diagonality; and 4) executing the graph cutting operation on the coeﬃcient matrix by solving a graph Laplacian problem. Our method has the advantages of a closed-form solution and the capacity of clustering data points that lie on nonlinear subspaces. The ﬁrst advantage makes our method eﬃcient in handling large-scale datasets, and the second one enables the proposed method to conquer the nonlinear subspace clustering challenge. Extensive experiments on six benchmarks demonstrate the eﬀectiveness and the eﬃciency of the proposed method in comparison with current state-of-the-art approaches.
Assessments as Teaching and Research Tools in an Environmental Problem-Solving Program for In-Service Teachers

A scenario-based assessment tool used in two environmental geoscience in-service programs for middle school and high school teachers served both to guide instructional techniques and as a method to evaluate the success of the instructional approach. In each in-service program the participants were assessed at an initial meeting to determine their understandings of environmental problems. The assessments included a hypothetical watershed scenario in which participants had to choose water quality monitoring sites, monitoring parameters, and provide justification of their choices. The results of these pre-assessments provided staff with an understanding of participant misconceptions that could be addressed specifically in program activities. In each program the participants were given the same assessment after participating in the workshops and this revealed significant shifts in certain areas of their understanding of watershed quality concepts and monitoring approaches. Good assessment scenarios are complex and are based on accurate information or data that are used to answer a question or prompt. They are particularly revealing and valuable because they ask students to make decisions by applying their understandings using information or data. Development and use of scenario-based assessment in this program came about only because of genuine and sustained cooperation between science education faculty and geoscience faculty. This highly beneficial collaboration was key to providing quality training to participating in-service teachers, and development of a synergistic teaching and learning environment.
Optimization of the SD2 memory system

As far as is evidenced, man has sought the answers to his deepest questions by observing the sky. The findings and studies that have been made in this way have helped us know the planet where we live and our situation in the universe. From Greeks to now, through Galileo, Kepler or the Hubble telescope, look out was key to better know the Earth. The Rosseta Mission is the best example of this strategy. It is know that there are comets that have similar features with the Earth at its younger phase. So, the goal of the mission is to land on a comet surface and make a study about its composition and properties. In this way it could be increased the knowledge about how was the Earth, and furthermore, what were the conditions that allowed the emergence of life on it. The objective of this project is work on the optimization of one subsystem of this mission. It is known that the space missions have all their resources optimized in order to reach their goals (the power consumption, the heat, the memory, etc.). So, in that case, it is important to work on the optimization of the memory consumption of the SD2 subsystem.
On flexible Green function methods for atomistic/continuum coupling

Atomistic/continuum (A/C) coupling schemes have been developed during the past twenty years to overcome the vast computational cost of fully atomistic models, but have not yet reached full maturity to address many problems of practical interest. This work is therefore devoted to the development and analysis of flexible Green function methods for A/C coupling. Thereby, the Green function of the harmonic crystal is computed a priori and subsequently employed during the simulation of a fully nonlinear atomistic problem to update its boundary conditions on-the-fly, based on the motion of the atoms and without the need of an explicit numerical discretization of the bulk material. The first part is devoted to the construction of a discrete boundary element method (DBEM) which bears several advantages over its continuous analog, i.a. nonsingular Green kernels and direct application to nonlocal elasticity. As is well-known from integral problems, the DBEM leads to dense system matrices which become quickly unfeasible due to their quadratic complexity. To overcome this computational burden, an implicit approximate representation using hierarchical matrices is proposed which have proven their efficiency in the context of boundary integral equations while preserving overall accuracy. In order to solve the coupled atomistic/DBEM problem, several staggered and monolithic solution procedures are assessed. An improvement of the overall accuracy by several orders of magnitude is found in comparison with naive clamped boundary conditions. To further account for plasticity in the continuum domain the coupled atomistic/discrete dislocations (CADD) method is examined, including the treatment of hybrid dislocation lines that span between the two domains. In particular, a detailed derivation of a quasistatic problem formulation is covered and a general algorithm to simulate the motion of the hybrid dislocations along A/C interfaces is presented. In addition, to avoid solving the complementary elasticity problem, a simplified solution procedure, which updates the boundary conditions based on the Green function of the entire dislocation network for obtaining accurate stress and displacement fields, is introduced and validated. The test problem consists of the bowout of a single dislocation in a semi-periodic box under an applied shear stress, and excellent results are obtained in comparison to fully-atomistic solutions of the same problem.
Adaptation of Motor Parameters in Sensorless PMSM Drives

This paper proposes an online method for the estimation of the stator resistance and the permanent-magnet (PM) flux in sensorless PM synchronous motor drives. An adaptive observer augmented with a high-frequency signal injection technique is used for sensorless control. The observer contains excess information that is not used for the speed and position estimation. This information is used for the adaptation of the motor parameters: At low speeds, the stator resistance is estimated, whereas at medium and high speeds, the PM flux is estimated. Small-signal analysis is carried out to investigate the proposed method. The convergence of the parameter estimates is shown by simulations and laboratory experiments. The stator resistance adaptation works down to zero speed in sensorless control.
Evidence of a Transient Aseismic Slip Driving the 2017 Valparaiso Earthquake Sequence, From Foreshocks to Aftershocks

Following laboratory experiments and friction theory, slow slip events and seismicity rate accelerations observed before mainshocks are sometimes interpreted as evidence of a nucleation phase. However, such precursory observations still remain scarce and are associated with different time and length scales, raising doubts about their actual preparatory nature. We study the 2017 Valparaiso Mw = 6.9 earthquake, which was preceded by aseismic slip accompanied by an intense seismicity, suspected to reflect its nucleation phase. We complement previous observations, which have focused only on precursory activity, with a continuous investigation of seismic and aseismic processes from the foreshock sequence to the post‐mainshock phase. By building a high‐resolution earthquake catalog and searching for anomalous seismicity rate increases compared to aftershock triggering models, we highlight an over‐productive seismicity starting within the foreshock sequence and persisting several days after the mainshock. Using repeating earthquakes and high‐rate GPS observations, we highlight a transient aseismic perturbation starting 1‐day before the first foreshock and continuing after the mainshock. The estimated slip rate over time is lightly impacted by large magnitude earthquakes and does not accelerate toward the mainshock. Therefore, the unusual seismic and aseismic activity observed during the 2017 Valparaiso sequence might be interpreted as the result of a slow slip event starting before the mainshock and continuing beyond it. Rather than pointing to a possible nucleation phase of the 2017 Valparaiso mainshock, the identified slow slip event acts as an aseismic loading of nearby faults, increasing the seismic activity, and thus the likelihood of a large rupture.
Short Sequence Aligner Benchmarking for Chromatin Research

Much of today’s molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner’s ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.
Characterization of an isolated lactase enzyme produced by Bacillus licheniformis ALSZ2 as a potential pharmaceutical supplement for lactose intolerance

Introduction Lactose intolerance is a widespread problem that affects people of many different races all over the world. The following pharmacological supplements can improve the lives of those who suffer from this issue. Methods This work focused on lactase producer isolation and statistical design (Plackett–Burman, and BOX–Behnken) to maximize the effectiveness of environmental factors. A lactase-producing bacterium was chosen from a discovery of 100 strains in soil that had previously been polluted with dairy products. Plackett-Burman investigated fifteen variables. Results The most critical variables that lead to increased lactase synthesis are glucose, peptone, and magnesium sulfate (MgSO4). The ideal process conditions for the creation of lactase yield among the stated variables were then determined using a BOX-Benken design. To establish a polynomial quadratic relationship between the three variables and lactase activity, the Box–Behnken design level was used. The EXCEL-solver nonlinear optimization technique was used to predict the best form for lactase production. The ideal temperature and pH levels have been determined, both before and after the lactase purification process, to achieve the highest performance of isolated lactase. Conclusion According to this study, Bacillus licheniformis is a perfect supply of the lactase enzyme (β -Galactosidase), It can be used as a product to assist people who have health issues due to lactose intolerance.