IN SEARCH OF A FINANCIAL PROTECTION MODEL FOR OLD AGE

Discussions about the shortcomings of the pension system and its design raise the question of how to ensure a dignified life after working life. According to the currently adopted model of old age security, the responsibility is generally placed on the state and its structures. A number of questions arise in this context, in particular whether this is a rational approach from the point of view of its optimality, or whether the responsibility should not be distributed among various actors: public authorities, employers, employees or someone else.

Teaching and research in plant health in times of COVID-19

<p>The current pandemic caused by the SARS-CoV-2 virus has led to radical changes in the teaching and research of plant health. Confinement forced us to make a rapid transition from the in-person model to virtual environments using different digital platforms such as Google, Microsoft Teams, Blackboard, Moodle. Research activities were planned based on a strict access schedule for students and academics when using research facilities. Theoretical subjects were taught in completely virtual settings, incorporating playful learning tools such as ‘flipped classroom’ and gamification. In theoretical-practical subjects, such as Introduction to Plant Pathology, new teaching schemes were designed. The most successful and innovative model was to take the laboratory to the student’s home. Students used conventional materials to isolate and identify phytopathogenic fungi through the Foldscope, a paper microscope with a resolution of up to two microns, priced less than 200 MXN. Teaching-learning innovation can improve the commonly adopted model of video conferences.</p>

Modelling Regime Changes of Dunes to Upper-Stage Plane Bed in Flumes and in Rivers

In this paper we derive a new morphological model, with an extended version of the sediment transport model for the mean step length (the average distance travelled by sediment particles), in which this mean step length depends on the mean bed shear stress. This model makes the step length increase with increasing flow, in line with previous experimental results. To account for suspension and the large-scale turbulent structures in rivers, the step length also depends explicitly on water depth. This approach enabled modelling of the transition from dunes to the upper-stage plane bed. It was shown that by increasing the step length, the lag between shear stress and bed load transport rate increases, and the dunes eventually become smoother and lower, until finally the dunes wash out. The newly adopted model approach is tested successfully with a synthetic data set from the literature, where plane bed conditions are indeed reached in the model, similar to the results of a more advanced model. It is shown that with increasing discharge, the flow increases, which leads to higher step length and to the washing out of the dunes. Although the present model still overestimates the dune height for river cases, the potential of the model concept for river dune dynamics, including the transition to upper-stage plane bed, is shown. The model results indicate that, if a transition to upper-stage plane bed occurs in a realistic river scenario, a reduction of the water depth of approximately 0.5 m can occur.

Water Erosion in the Moulouya Watershed and its Impact on Dams' Siltation (Eastern Morocco)

The Moulouya watershed presents high risks of water erosion. The dams built on this river lose each year, by siltation, a volume of water of about 10 M m3 (Lahlou, 1994). This worrying rate shows that water erosion can hinder the socio-economic development of the basin if soil protection and siltation measures are not taken. This study defines the areas most threatened by water erosion to protect them as a priority. Using a GIS and the Universal Earth Loss Equation (USLE), we mapped soil losses. The adopted model determines soil loss from erosivity of rainfall, soil erodibility, inclination and slope length, soil cover, and erosion control practices. The possible origins of the deposits alluviating the dams are related to the products of alteration of the Secondary's carbonate formations and the Tertiary and Quaternary formations. The modalities of the transport of deposits of banks of the network of Moulouya are mainly by a suspension. The specific degradation in the Moulouya watershed is estimated at 214 t/km2/year. Precipitation intensity, steep slopes and deforestation are responsible for these losses.

Dynamic and Probabilistic Seismic Performance Assessment of Precast Prestressed Rcfs Incorporating Slab Influence Through Three-Dimensional Spatial Model

The dynamic and probabilistic seismic performances of precast prestressed RCFs are assessed in this paper, and the slab influence in the overall structural behavior is considered during the process. The threedimensional spatial model is established to provide the numerical basis, and the slab is modelled through L-/T-section beam-slab fiber-sections considering the effective width and centroid positions. The adopted model is verified with the experimental data, and the slab influence in hysteresis curves is investigated by parametric study. Then, two groups of precast prestressed RCFs are well designed to evaluate the slab influence in dynamic responses through seismic excitations, and the modal analysis, roof displacement analysis, maximum and residual drift ratio analysis are conducted for discussion. Moreover, the incremental dynamic analysis and fragility analysis are also conducted to investigate the probabilistic performance of precast prestressed RCFs with or without slabs. In general, different demand parameters may result in the variability of analyzing results, and ignoring the slab influence may underestimate the structural capacity under the frequent earthquakes (i.e., elastic stage) and overestimate the structural capacity under the rare earthquakes (i.e., plastic stage). In a sense, the research proves the significance of slabs in the seismic performance of dry-connected precast prestressed RCFs, and meanwhile provides the reference for the further explorations of slab factors in precast concrete structures.

A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis

Spectral clustering is one of the fundamental unsupervised learning methods and is widely used in data analysis. Sparse spectral clustering (SSC) imposes sparsity to the spectral clustering, and it improves the interpretability of the model. One widely adopted model for SSC in the literature is an optimization problem over the Stiefel manifold with nonsmooth and nonconvex objective. Such an optimization problem is very challenging to solve. Existing methods usually solve its convex relaxation or need to smooth its nonsmooth objective using certain smoothing techniques. Therefore, they were not targeting solving the original formulation of SSC. In this paper, we propose a manifold proximal linear method (ManPL) that solves the original SSC formulation without twisting the model. We also extend the algorithm to solve multiple-kernel SSC problems, for which an alternating ManPL algorithm is proposed. Convergence and iteration complexity results of the proposed methods are established. We demonstrate the advantage of our proposed methods over existing methods via clustering of several data sets, including University of California Irvine and single-cell RNA sequencing data sets.

The Selectivity of Immunoassays and of Biomimetic Binding Assays with Imprinted Polymers

Molecularly imprinted polymers have been shown to be useful in competitive biomimetic binding assays. Recent developments in materials science have further enhanced the capabilities of imprinted polymers. Binding assays, biological and biomimetic alike, owe their usefulness to their selectivity. The selectivity of competitive binding assays has been characterized with the cross-reactivity, which is usually expressed as the ratio of the measured IC50 concentration values of the interferent and the analyte, respectively. Yet this cross-reactivity is only a rough estimate of analytical selectivity. The relationship between cross-reactivity and analytical selectivity has apparently not been thoroughly investigated. The present work shows that this relationship depends on the underlying model of the competitive binding assay. For the simple but widely adopted model, where analyte and interferent compete for a single kind of binding site, we provide a simple formula for analytical selectivity. For reasons of an apparent mathematical problem, this formula had not been found before. We also show the relationship between analytical selectivity and cross-reactivity. Selectivity is also shown to depend on the directly measured quantity, e.g., the bound fraction of the tracer. For those cases where the one-site competitive model is not valid, a practical procedure is adopted to estimate the analytical selectivity. This procedure is then used to analyze the example of the competitive two-site binding model, which has been the main model for describing molecularly imprinted polymer behavior. The results of this work provide a solid foundation for assay development.

The Methodology for Designing Residential Buildings with a Positive Energy Balance—Case Study

The article presents the results of the application of an original methodology for designing residential buildings with a positive energy balance in accordance with the principles of sustainable development. The methodology was verified using a computational example involving the selection of a compromise solution for a single-family residential building with a positive energy balance located in Warsaw, Poland. Three different models of decision-makers’ preferences were created, taking into account selected decision sub-criteria. Three technical solutions were identified, permissible according to the principles and guidelines for designing buildings with a positive energy balance. As a result of the performed calculations, the final order of the analyzed variants was obtained, from the most preferred to the least accepted solution. Variant 2 is definitely the most advantageous solution, being the best in a group of 20 to 26 evaluation sub-criteria—depending on the adopted model of the decision-maker’s preferences. Its ranking index Ri ranged from 0.773 to 0.764, while for the other variants it was much lower and varied from 0.258 to 0.268 for variant 1, and from 0.208 to 0.226 for variant 3. The methodology used for the case study proved to be applicable. The developed methodology facilitates the process of designing residential buildings with a positive energy balance, which is an extremely complex process.

Politeness in Social Justice Texts of the New Testament and Nahjul- Balagh

God sends prophets and messengers to make justice prevail on the planet and threaten oppressors who take people’s rights away to humiliate them. Divine books given to prophets and messengers show how a just society can be built where people save their dignity and live a secured life. This study deal with politeness as a pragmatic strategy in such texts. The present study is going to analyze 16 texts in two religious resources. The theme of these texts deals with social justice in the New Testament and Nahjul-Balagha. The adopted model is that of Leech’s (1983) politeness. It aims to find out the politeness maxims in the New Testament and Nahjul-Balagha of social justice texts. The study aims to reveal the similarities and differences in their implying politeness maxims.

Neural network-based estimation of lighting condition in indoor environment with improved brain storm algorithm

Purpose For decades, continuous research work is going on to maximize the power harvested from the sun; however, there is only a limited analysis on exploiting the microwatt output power from indoor lightings. Microelectronic system has power demand in the µW range, and therefore, indoor photovoltaics would be appropriate for micro-energy harvesting appliances. “Energy harvesting is defined as the transfer process by which energy source is acquired from the ambient energy, stored in energy storage element and powered to the target systems”. The theory of energy harvesting is: gathering energy from surroundings and offering technological solutions such as solar energy harvesting, wind energy collection and vibration energy harvesting. “The solar cell or photovoltaic cell (PV), is a device that converts light into electric current using the photoelectric effect”. Factors such as light source, temperature, circuit connection, light intensity, angle and height can manipulate the functions of PV cells. Among these, the most noticeable factor is the light intensity that has a major impact on the operations of solar panels. Design/methodology/approach This paper aims to design an enhanced prediction model on illuminance or irradiance by an optimized artificial neural network (ANN). The input attributes or the features considered here are temperatures, maxim, TSL, VI, short circuit current, open-circuit voltage, maximum power point (MPP) voltage, MPP current and MPP power, respectively. To enhance the performance of the prediction model, the weights of ANN are optimally tuned by a new self-improved brain storm optimization (SI-BSO) model. Findings The superiority of the implemented work is compared and proved over the conventional models in terms of error analysis and prediction analysis. Accordingly, the presented approach was analysed and its superiority was proved over other conventional schemes such as ANN, ANN-Levenberg–Marquardt (LM), adaptive-network-based fuzzy inference system (ANFIS) and brainstorm optimization (BSO). In addition, analysis was held with respect to error measures such as mean absolute relative error (MARE), mean square root error (MSRE), mean absolute error and mean absolute percentage error. Moreover, prediction analysis was also performed that revealed the betterment of the presented model. More particularly, the proposed ANN + SI-BSO model has attained minimal error for all measures when compared to the existing schemes. More particularly, on considering the MARE, the adopted model for data set 1 was 23.61%, 48.12%, 79.39% and 90.86% better than ANN, ANN-LM, ANFIS and BSO models, respectively. Similarly, on considering data set 2, the MSRE of the implemented model was 99.87%, 70.69%, 99.57% and 94.74% better than ANN, ANN-LM, ANFIS and BSO models, respectively. Thus, the enhancement of the presented ANN + SI-BSO scheme has been validated effectively. Originality/value This work has established an improved illuminance/irradiance prediction model using the optimization concept. Here, the attributes, namely, temperature, maxim, TSL, VI, Isc, Voc, Vmpp, Impp and Pmpp were given as input to ANN, in which the weights were chosen optimally. For the optimal selection of weights, a novel ANN + SI-BSO model was established, which was an improved version of the BSO model.