Execution: the Critical “What’s Next?” in Strategic Human Resource Management

The Human Resource Planning Society’s 1999 State of the Art/Practice (SOTA/P) study was conducted by a virtual team of researchers who interviewed and surveyed 232 human resource and line executives, consultants, and academics worldwide. Looking three to five years ahead, the study probed four basic topics: (1) major emerging trends in external environments, (2) essential organizational capabilities, (3) critical people issues, and (4) the evolving role of the human resource function. This article briefly reports some of the study’s major findings, along with an implied action agenda – the “gotta do’s for the leading edge. Cutting through the complexity, the general tone is one of urgency emanating from the intersection of several underlying themes: the increasing fierceness of competition, the rapid and unrelenting pace of change, the imperatives of marketplace and thus organizational agility, and the corresponding need to buck prevailing trends by attracting and, especially, retaining and capturing the commitment of world-class talent. While it all adds up to a golden opportunity for human resource functions, there is a clear need to get to get on with it – to get better, faster, and smarter – or run the risk of being left in the proverbial dust. Execute or be executed

An Experimental and Analytical Study of the Distribution of Heat in Concrete Columns

Fire is one of the most devastating disasters that have caused human damage, prompting researchers to conduct numerous studies on the behavior of fire-prone elements and take action to minimize damage. With the development of computer simulation theories, it is possible to study the behavior of structures under the influence of different loads (static, dynamic, thermal ... etc), and this leads to saving time, effort and money cost instead of performing laboratory experiments. Thermal loads are considered one of the most dangerous loads to which concrete structures are exposed. Hence it is very important to know the thermal distribution in the cross section of the element exposed to high temperature. Whereas, by knowing the thermal distribution, the designed load and the expected failure load of the structural element can be calculated and thus take the necessary measures to reduce the fire risk as much as possible. In this research, an experimental and analytical study was conducted on models of reinforced concrete columns, where thermocouple were used in different places to monitor the temperature at the specified points, The experimental thermal distribution was compared with the analytical results of the ANSYS Workbench program. The analytical results showed a great accuracy compared to the experimental results. Consequently, an analytical model was simulated to simulate the experimental, through which it is possible to know the thermal distribution of the model. Keywords: thermal distribution, thermal analysis, thermocouple, ANSYS Workbench. DOI: 10.7176/CER/13-1-01 Publication date: January 31st 202

Effect of Fire on Carrying Capacity of Concrete Columns Confinement with Multi-Layers of CFRP

FRP reinforced polymers are widely accepted for use in civil engineering applications to strengthen constructions and application of confinement on the concrete columns, thereby increasing their ductility and increasing their carrying capacity as these materials are characterized by high tensile strength, high strength-to-weight ratio and high corrosion resistance of FRP composites, etc. In addition, the exposure of reinforced concrete structures to fire is one of the most dangers challenges that lead to great destruction and failure the structural in addition to loss of life. With the development of computer simulation theories to study the behavior of elements and structures under the influence of different loads (static, dynamic, thermal, etc.), it is possible to study the behavior of concrete columns under the influence of axial vertical and non-axial structural loads, and compare the results with previous research, thus saving time, effort and cost instead Of laboratory testing. Strengthening concrete columns with fiber-reinforced polymers (FRP) has been studied extensively, but the majority of published studies have focused on circular columns. Most concrete columns in the field have square or rectangular cross sections and resist eccentric loading as well. The objective of this study is to investigate the performance of square reinforced concrete (RC) columns, wrapped with carbon FRP subjected to fire so, in this paper, an analytical study was conducted using the ANSYS Workbench program, which follows the finite element method, to determine the effect of layers number of CFRP on carrying capacity of concrete columns and to know the effect of external standard fire on confined concrete columns with  CFRP. The numerical results were compared with experimental results as far as possible, and revealed the accuracy of the analytical models, when compared to the experimental studies. The results shown that with increase the layer number of CFRP, the carrying capacity of concrete columns will increase,   no benefit with increase the number of CFRP more than 4 layers where polymers materials are sensitive to fire so that it needs to insulation. Keywords: confinement, CFRP, External fire, ANSYS Workbench. DOI: 10.7176/CER/12-12-01 Publication date: December 31st 202

Modeling meiotic recombination hotspots using deep learning

La recombinaison méiotique joue un rôle essentiel dans la ségrégation des chromosomes pendant la méiose et dans la création de nouvelles combinaisons du matériel génétique des espèces. Ses effets cause une déviation du principe de l'assortiment indépendant de Mendel; cependant, les mécanismes moléculaires impliqués restent partiellement incompris jusqu'à aujourd'hui. Il s'agit d'un processus hautement régulé et de nombreuses protéines sont impliquées dans son contrôle, dirigeant la recombinaison méiotique dans des régions génomiques de 1 à 2 kilobases appelées « hotspots ». Au cours des dernières années, l'apprentissage profond a été appliqué avec succès à la classification des séquences génomiques. Dans ce travail, nous appliquons l'apprentissage profond aux séquences d'ADN humain afin de prédire si une région spécifique d'ADN est un hotspot de recombinaison méiotique ou non. Nous avons appliqué des réseaux de neurones convolutifs sur un ensemble de données décrivant les hotspots de quatre individus non-apparentés, atteignant une exactitude de plus de 88 % avec une précision et un rappel supérieur à 90 % pour les meilleurs modèles. Nous explorons l'impact de différentes tailles de séquences d'entrée, les stratégies de séparation des jeux d'entraînement/validation et l’utilité de montrer au modèle les coordonnées génomiques de la séquence d'entrée. Nous avons exploré différentes manières de construire les motifs appris par le réseau et comment ils peuvent être liés aux méthodes classiques de construction de matrices position-poids, et nous avons pu déduire des connaissances biologiques pertinentes découvertes par le réseau. Nous avons également développé un outil pour visualiser les différents modèles afin d'aider à interpréter les différents aspects du modèle. Dans l'ensemble, nos travaux montrent la capacité des méthodes d'apprentissage profond à étudier la recombinaison méiotique à partir de données génomiques.Meiotic recombination plays a critical role in the proper segregation of chromosomes during meiosis and in forming new combinations of genetic material within sexually-reproducing species. For a long time, its side effects were observed as a deviation from the Mendel’s principle of independent assortment; however, its molecular mechanisms remain only partially understood until today. We know that it is a highly regulated process and that many molecules are involved in this tight control, resulting in directing meiotic recombination into 1-2 kilobase genomic pairs regions called hotspots. During the past few years, deep learning was successfully applied to the classification of genomic sequences. In this work, we apply deep learning to DNA sequences in order to predict if a specific stretch of DNA is a meiotic recombination hotspot or not. We applied convolution neural networks on a dataset describing the hotspots of four unrelated male individuals, achieving an accuracy of over 88% with precision and recall above 90% for the best models. We explored the impact of different input sequence lengths, train/validation split strategies and showing the model the genomic coordinates of the input sequence. We explored different ways to construct the learnt motifs by the network and how they can relate to the classical methods of constructing position-weight-matrices, and we were able to infer relevant biological knowledge uncovered by the network. We also developed a tool for visualizing the different models output in order to help digest the different aspects of the model. Overall, our work shows the ability for deep learning methods to study meiotic recombination from genomic data

High-wavenumber steady solutions of two-dimensional Rayleigh--B\'enard convection between stress-free boundaries

Recent investigations show that steady solutions share many features with turbulent Rayleigh--B\'enard convection (RBC) and form the state space skeleton of turbulent dynamics. Previous computations of steady roll solutions in two-dimensional (2D) RBC between no-slip boundaries reveal that for fixed Rayleigh number $Ra$ and Prandtl number $Pr$, the heat-flux-maximizing solution is always in the high-wavenumber regime. In this study, we explore the high-wavenumber steady convection roll solutions that bifurcate supercritically from the motionless conductive state for 2D RBC between stress-free boundaries. Our computations confirm the existence of a local heat-flux-maximizing solution in the high-wavenumber regime. To elucidate the asymptotic properties of this solution, we perform computations over eight orders of magnitude in the Rayleigh number, $10^{8} \le Ra \le 10^{16.5}$, and two orders of magnitude in the Prandtl number, $10^{-1} \leq Pr \leq 10^{3/2}$. The numerical results indicate that as $Ra\to\infty$, the local heat-flux-maximizing aspect ratio $\Gamma^*_{loc}\simeq Ra^{-1/4}$, the Nusselt number $Nu(\Gamma^*_{loc})\simeq Ra^{0.29}$, and the Reynolds number $Re(\Gamma^*_{loc})\simeq Pr^{-1}Ra^{2/5}$, with all prefactors depending on $Pr$. Moreover, the interior flow of the local $Nu$-maximizing solution can be well described by an analytical heat-exchanger solution, and the connection to the high-wavenumber asymptotic solution given by Blennerhassett & Bassom is discussed. With a fixed aspect ratio $0.06\le\Gamma\le\pi/5$ at $Pr=1$, however, our computations show that as $Ra$ increases, the steady rolls converge to the semi-analytical asymptotic solutions constructed by Chini & Cox, with scalings $Nu\sim Ra^{1/3}$ and $Re\sim Pr^{-1}Ra^{2/3}$. Finally, a phase diagram is delineated to gain a panorama of steady solutions in the high-Rayleigh-number-wavenumber plane

Effect of Fire on Confined Concrete Columns under Axial Loading

The aim of this study is to numerically investigate the feasibility of confinement, the load carrying capacity and the temperature at which the confinement become obsolete for a RC column with dimensions of [200x200x 800 mm] subjected to a standard fire loads (ISO834) from four sides. The study was carried out using the research-oriented FE code ANSYS APDL. ANSYS can integrate the nonlinear behavior of concrete by accounting for both crushing under compression stresses and cracking under tensile stresses, and well as the bilinear behavior of the reinforcing steel.The Numerical program was subcategorized into two major groups. The first one consisted of thirteen models. Those models were analyzed under static loading conditions. The second group consisted of 72 models. The models in this group where subjected to both structural and thermal loading conditions. The structural loading was in a form of static service loads, while the thermal loading was in a form of standard fire curve that has been applied to the four faces of the column.The numerical results were compared with experimental results as far as possible, in order to verify the accuracy of the numerical models used. The numerical analysis aimed to study of the effect of many variables, i.e., the diameter of the lateral reinforcement, the diameter of the longitudinal reinforcement.The results revealed the accuracy of the analytical models when compared to the experimental studies. A positive effect was captured in terms of the load carrying capacity and delaying the failure time, i.e., loss in confinement effect, when increasing 1) the diameter of the longitudinal, 2) the diameter of the transverse reinforcement and Additionally, the results indicated an increase in the column loading time under thermal loading conditions when static design loads are applied. And when the percentage of failure load increased, the time of carrying columns of fire decreased. Keywords: Finite Element Theory, Thermal Analysis, Reinforced Concrete Column

Ungdomsstraff: Er det behov for reform?

Masteravhandlingen søker å klarlegge hvilket behov det er for reform av straffereaksjonen ungdomsstraff. Før reformbehovet drøftes, blir det i avhandlingen gitt en oversikt over ungdomsstraffens innhold og oppbygning samt grunnleggende hensyn bak reaksjonen. Når reformbehovet deretter drøftes, blir det tatt utgangspunkt i ungdomsstraffens hoveddeler; ungdomsstormøtet og ungdomsplanen.MasteroppgaveJUS399MAJUR-2MAJU

The Impact of the International Monetary Fund’s 2016 – 2019 Loan to Egypt on the Country’s Development

The primary objective of the International Monetary Fund (IMF) is growth. The organization and its programs can enable the development of nations across the globe and stimulate growth. However, due to weaknesses in its system with conditions that are offered as blanket solutions for unique problems as well as unequal bargaining terms, the IMF can exacerbate the situation in nations that are already suffering with crises. Following years of unrest after the Arab Spring, Egypt finds itself in an unwieldly position having both vowed to increasing its development as well as introduced major reforms based on IMF recommendations in order to acquire loans from it. Egypt’s 2016 – 2019 loan from the IMF echoes the country’s past experience with the Fund in the 1990s. Both programs heavily focus on macroeconomic stability. However, the 1990s’ program was criticized for its weak implementation of structural adjustments for multiple reasons including delays caused by legislation changes needed for enforcement. The recent program, on the other hand, was preceded by the passing of bills in the Egyptian Parliament and rigid conditions to ensure the fruition of the agreements. The IMF’s recent loans to Egypt are expected to achieve long-term goals of development. Unfortunately, they added more strains on middle and low income populations despite the Fund’s promises of easing adjustments to weaken the shock magnitude of measures such as currency floating and decreases in subsidies