Universidad Politécnica de Cartagena

This revised, expanded, edition covers the theory, design, geometry and manufacture of all types of gears and gear drives. This is an invaluable reference for designers, theoreticians, students, and manufacturers. This edition includes advances in gear theory, gear manufacturing, and computer simulation. Among the new topics are: 1. New geometry for modified spur and helical gears, face-gear drives, and cycloidal pumps. 2. New design approaches for one stage planetary gear trains and spiral bevel gear drives. 3. An enhanced approach for stress analysis of gear drives with FEM. 4. New methods of grinding face gear drives, generating double crowned pinions, and improved helical gear shaving. 5. Broad application of simulation of meshing and TCA. 6. New theories on the simulation of meshing for multi-body systems, detection of cases wherein the contact line on generating surfaces may have its own envelope, and detection and avoidance of singularities of generated surfaces.

Purpose Structural equation modelling (SEM) has been defined as the combination of latent variables and structural relationships. The partial least squares SEM (PLS-SEM) is used to estimate complex cause-effect relationship models with latent variables as the most salient research methods across a variety of disciplines, including knowledge management (KM). Following the path initiated by different domains in business research, this paper aims to examine how PLS-SEM has been applied in KM research, also providing some new guidelines how to improve PLS-SEM report analysis. Design/methodology/approach To ensure an objective way to analyse relevant works in the field of KM, this study conducted a systematic literature review of 63 publications in three SSCI-indexed and specific KM journals between 2015 and 2017. Findings Our results show that over the past three years, a significant amount of KM works has empirically used PLS-SEM. The findings also suggest that in light of recent developments of PLS-SEM reporting, some common misconceptions among KM researchers occurred mainly related to the reasons for using PLS-SEM, the purposes of PLS-SEM analysis, data characteristics, model characteristics and the evaluation of the structural models. Originality/value This study contributes to that vast KM literature by documenting the PLS-SEM-related problems and misconceptions. Therefore, it will shed light for better reports in PLS-SEM studies in the KM field.

Ionic liquids (ILs) are finding technological applications as chemical reaction media and engineering fluids. Some emerging fields are those of lubrication, surface engineering and nanotechnology. ILs are thermally stable, non-flammable highly polar fluids with negligible volatility, these characteristics make them ideal candidates for new lubricants under severe conditions, were conventional oils and greases or solid lubricants fail. Such conditions include ultra-high vacuum and extreme temperatures. Other very promising areas which depend on the interaction between IL molecules and material surfaces are the use of ILs in the lubrication of microelectromechanic and nanoelectromechanic systems (MEMS and NEMS), the friction and wear reduction of reactive light alloys and the modification of nanophases.

Scalability is a requirement before any new energy source can be expected to house a possible solution to the challenge that mankind’s increasing energy demand presents. No renewable energy source is as abundant as the Sun and yet efficient and low-cost conversion of solar energy still has not been developed. We approach the challenge by firstly taking a technology that efficiently addresses the need for daily production of 1 GWp on a global level, which does not employ elements with critically low abundance and has a low thermal budget. We then applied life cycle assessment methodologies to direct research and developed such technology in the form of a polymer solar cell that presents a significant improvement in energy payback time (EPBT) and found that very short energy payback times on the order of one day are possible, thus potentially presenting a solution to the current energy gap of >14 TW by year 2050.

Multicomponent quantum systems in strong interaction with their environment are receiving increasing attention due to their importance in a variety of contexts, ranging from solid state quantum information processing to the quantum dynamics of biomolecular aggregates. Unfortunately, these systems are difficult to simulate as the system-bath interactions cannot be treated perturbatively and standard approaches are invalid or inefficient. Here we combine the time-dependent density matrix renormalization group with techniques from the theory of orthogonal polynomials to provide an efficient method for simulating open quantum systems, including spin-boson models and their generalizations to multicomponent systems.

Frequency in large power systems is usually controlled by adjusting the production of generating units in response to changes in the load. As the amount of intermittent renewable generation increases and the proportion of flexible conventional generating units decreases, a contribution from the demand side to primary frequency control becomes technically and economically desirable. One of the reasons why this has not been done was the perceived difficulties in dealing with many small loads rather than a limited number of generating units. In particular, the cost and complexity associated with two-way communications between many loads and the control center appeared to be insurmountable obstacles. This paper argues that this two-way communication is not essential and that the demand can respond to the frequency error in a manner similar to the generators. Simulation results show that, using this approach, the demand side can make a significant and reliable contribution to primary frequency response while preserving the benefits that consumers derive from their supply of electric energy.

Euclid is a mission of the European Space Agency that is designed to constrain the properties of dark energy and gravity via weak gravitational lensing and galaxy clustering. It will carry out a wide area imaging and spectroscopy survey (the Euclid Wide Survey: EWS) in visible and near-infrared bands, covering approximately 15 000 deg 2 of extragalactic sky in six years. The wide-field telescope and instruments are optimised for pristine point spread function and reduced stray light, producing very crisp images. This paper presents the building of the Euclid reference survey: the sequence of pointings of EWS, deep fields, and calibration fields, as well as spacecraft movements followed by Euclid as it operates in a step-and-stare mode from its orbit around the Lagrange point L2. Each EWS pointing has four dithered frames; we simulated the dither pattern at the pixel level to analyse the effective coverage. We used up-to-date models for the sky background to define the Euclid region-of-interest (RoI). The building of the reference survey is highly constrained from calibration cadences, spacecraft constraints, and background levels; synergies with ground-based coverage were also considered. Via purposely built software, we first generated a schedule for the calibrations and deep fields observations. On a second stage, the RoI was tiled and scheduled with EWS observations, using an algorithm optimised to prioritise the best sky areas, produce a compact coverage, and ensure thermal stability. The result is the optimised reference survey RSD_2021A, which fulfils all constraints and is a good proxy for the final solution. The current EWS covers ≈14 500 deg 2 . The limiting AB magnitudes (5 σ point-like source) achieved in its footprint are estimated to be 26.2 (visible band I E ) and 24.5 (for near infrared bands Y E , J E , H E ); for spectroscopy, the H α line flux limit is 2 × 10 −16 erg −1 cm −2 s −1 at 1600 nm; and for diffuse emission, the surface brightness limits are 29.8 (visible band) and 28.4 (near infrared bands) mag arcsec −2 .

Although US and European research has documented improvement in earnings quality associated with corporate governance characteristics, the situation in Latin America is questionable, given the business environment in which firms operate, which is characterized by controlling family ownership and weak legal protection. The purpose of this study is to examine the relation between the internal mechanisms of Corporate Governance and Earnings Management measured by discretionary accrual. We use a sample of listed Latin American non-financial companies from the period 2006–2009. Our results show how in the Latin American context the role of external directors is limited and that Boards which meet more frequently take a more active position in the monitoring of insiders, so showing a lower use of manipulative practices. In addition, we find a non-linear relation between insider ownership and discretionary accruals, also pointing to the fact that ownership concentration may be a manipulative practices constrictor mechanism only when the ownership of main shareholders is moderate. The findings have important policy implications since this is, to the best of our knowledge, the first study to analyze the relation between the effectiveness of the government and the earnings management behavior. As policy implications, we document how when a country implements controls aimed at reducing corruption, strengthening the rule of law or improving the effectiveness of government, this leads to a reduction in firm earnings management.

This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.

Aims. The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. The estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on various individual methodologies and numerical implementations, which were developed for different observational probes and for the combination thereof. In this paper we present validated forecasts, which combine both theoretical and observational ingredients for different cosmological probes. This work is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts. Methods. We describe in detail the methods adopted for Fisher matrix forecasts, which were applied to galaxy clustering, weak lensing, and the combination thereof. We estimated the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations, some of which are made publicly available, in different programming languages, together with a reference training-set of input and output matrices for a set of specific models. These can be used by the reader to validate their own implementations if required. Results. We present new cosmological forecasts for Euclid . We find that results depend on the specific cosmological model and remaining freedom in each setting, for example flat or non-flat spatial cosmologies, or different cuts at non-linear scales. The numerical implementations are now reliable for these settings. We present the results for an optimistic and a pessimistic choice for these types of settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy figure of merit by at least a factor of three.

Petunia hybrida is a popular bedding plant that has a long history as a genetic model system. We report the whole-genome sequencing and assembly of inbred derivatives of its two wild parents, P. axillaris N and P. inflata S6. The assemblies include 91.3% and 90.2% coverage of their diploid genomes (1.4 Gb; 2n = 14) containing 32,928 and 36,697 protein-coding genes, respectively. The genomes reveal that the Petunia lineage has experienced at least two rounds of hexaploidization: the older gamma event, which is shared with most Eudicots, and a more recent Solanaceae event that is shared with tomato and other solanaceous species. Transcription factors involved in the shift from bee to moth pollination reside in particularly dynamic regions of the genome, which may have been key to the remarkable diversity of floral colour patterns and pollination systems. The high-quality genome sequences will enhance the value of Petunia as a model system for research on unique biological phenomena such as small RNAs, symbiosis, self-incompatibility and circadian rhythms.

BACKGROUND: The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. RESULTS: The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. CONCLUSIONS: The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

The plastic mulch films used in agriculture are considered to be a major source of the plastic residues found in soil. Mulching with low-density polyethylene (LDPE) is widely practiced and the resulting macro- and microscopic plastic residues in agricultural soil have aroused concerns for years. Over the past decades, a variety of biodegradable (Bio) plastics have been developed in the hope of reducing plastic contamination of the terrestrial ecosystem. However, the impact of these Bio plastics in agroecosystems have not been sufficiently studied. Therefore, we investigated the impact of macro (around 5 mm) and micro (<1 mm) sized plastic debris from LDPE and one type of starch-based Bio mulch film on soil physicochemical and hydrological properties. We used environmentally relevant concentrations of plastics, ranging from 0 to 2% (w/w), identified by field studies and literature review. We studied the effects of the plastic residue on a sandy soil for one month in a laboratory experiment. The bulk density, porosity, saturated hydraulic conductivity, field capacity and soil water repellency were altered significantly in the presence of the four kinds of plastic debris, while pH, electrical conductivity and aggregate stability were not substantially affected. Overall, our research provides clear experimental evidence that microplastics affect soil properties. The type, size and content of plastic debris as well as the interactions between these three factors played complex roles in the variations of the measured soil parameters. Living in a plastic era, it is crucial to conduct further interdisciplinary studies in order to have a comprehensive understanding of plastic debris in soil and agroecosystems.

The influences of processing and storage on the quality indices and nutritional content of fresh-cut fruits were evaluated in comparison to whole fruits stored for the same duration but prepared on the day of sampling. Fresh-cut pineapples, mangoes, cantaloupes, watermelons, strawberries, and kiwifruits and whole fruits were stored for up to 9 days in air at 5 degrees C. The postcutting life based on visual appearance was shorter than 6 days for fresh-cut kiwifruit and shorter than 9 days for fresh-cut pineapple, cantaloupe, and strawberry. On the other hand, fresh-cut watermelon and mango pieces were still marketable after 9 days at 5 degrees C. Losses in vitamin C after 6 days at 5 degrees C were < or = 5% in mango, strawberry, and watermelon pieces, 10% in pineapple pieces, 12% in kiwifruit slices, and 25% in cantaloupe cubes. No losses in carotenoids were found in kiwifruit slices and watermelon cubes, whereas losses in pineapples were the highest at 25% followed by 10-15% in cantaloupe, mango, and strawberry pieces after 6 days at 5 degrees C. No significant losses in total phenolics were found in any of the fresh-cut fruit products tested after 6 days at 5 degrees C. Light exposure promoted browning in pineapple pieces and decreased vitamin C content in kiwifruit slices. Total carotenoids contents decreased in cantaloupe cubes and kiwifruit slices, but increased in mango and watermelon cubes in response to light exposure during storage at 5 degrees C for up to 9 days. There was no effect of exposure to light on the content of phenolics. In general, fresh-cut fruits visually spoil before any significant nutrient loss occurs.

One of the main sources of plastic pollution in agricultural fields is the plastic mulch used by farmers to improve crop production. The plastic mulch is often not removed completely from the fields after harvest. Over time, the plastic mulch that is left of the fields is broken down into smaller particles which are dispersed by the wind or runoff. In the Region of Murcia in Spain, plastic mulch is heavily used for intensive vegetable farming. After harvest, sheep are released into the fields to graze on the vegetable residues. The objective of the study was to assess the plastic contamination in agricultural soil in Spain and the ingestion of plastic by sheep. Therefore, three research questions were established: i) What is the plastic content in agricultural soils where plastic mulch is commonly used? ii) Do livestock ingest the microplastics found in the soil? iii) How much plastic could be transported by the livestock? To answer these questions, we sampled top soils (0–10 cm) from 6 vegetable fields and collected sheep faeces from 5 different herds. The microplastic content was measured using density separation and visual identification. We found ~2 × 103 particles∙kg−1 in the soil and ~103 particles∙kg−1 in the faeces. The data show that plastic particles were present in the soil and that livestock ingested them. After ingesting plastic from one field, the sheep can become a source of microplastic contamination as they graze on other farms or grasslands. The potential transport of microplastics due to a herd of 1000 sheep was estimated to be ~106 particles∙ha−1∙y−1. Further studies should focus on: assessing how much of the plastic found in faeces comes directly from plastic mulching, estimating the plastic degradation in the guts of sheep and understanding the potential effects of these plastic residues on the health of livestock.

Concretes with a high thermal energy storage capacity were fabricated by mixing microencapsulated\nphase change materials (MPCM) into Portland cement concrete (PCC) and geopolymer concrete (GPC).\nThe effect of MPCM on thermal performance and compressive strength of PCC and GPC were investigated. It was found that the replacement of sand by MPCM resulted in lower thermal conductivity and higher thermal energy storage, while the specific heat capacity of concrete remained practically stable when the phase change material (PCM) was in the liquid or solid phase. Furthermore, the thermal conductivity of GPC as function of MPCM concentration was reduced at a higher rate than that of PCC. The power consumption needed to stabilize a simulated indoor temperature of 23°C was reduced after the addition of MPCM. GPC exhibited better energy saving properties than PCC at the same conditions.\nA significant loss in compressive strength was observed due to the addition of MPCM to concrete.\nHowever, the compressive strength still satisfies the mechanical European regulation (EN 206-1, compressive strength class C20/25) for concrete applications. Finally, MPCM-concrete provided a good thermal stability after subjecting the samples to 100 thermal cycles at high heating/cooling rates.

The primary driver for development of organic photovoltaic (OPV) technologies is the prospect of very low cost module manufacture leading to affordable solar electricity. This paper presents an economic assessment of OPV based on an existing pre-industrial manufacturing process and the associated detailed material inventory. Using life cycle costing techniques, the life cycle investment cost for a 1kWp, grid-connected OPV system is calculated, taking into account the materials, direct process energy, labour, balance of system components, design and maintenance costs. Assuming values for the performance ratio of the PV system, insolation level, inflation and interest rates, the levelised electricity cost (LEC) is calculated. Under an average solar irradiance of 1700 kWh/m2/year, typical of southern Europe, a LEC of between 0.19 €/kWh and 0.50 €/kWh was calculated for a 1kWp system, based on modules containing 7% efficient cells and assuming a 5 year module lifetime. The OPV module is found to make up the majority of the system cost while the material costs constitute the largest contribution to the cost of the OPV module. The influence of OPV module lifetime is studied using sensitivity. This paper demonstrates that competitive solar electricity from OPV is within reach if efficiencies of ca. 7% already demonstrated in lab scale devices can be achieved in large area modules and if lifetimes of at least 5 years can be achieved.

BACKGROUND: Identification of genes with invariant levels of gene expression is a prerequisite for validating transcriptomic changes accompanying development. Ideally expression of these genes should be independent of the morphogenetic process or environmental condition tested as well as the methods used for RNA purification and analysis. RESULTS: In an effort to identify endogenous genes meeting these criteria nine reference genes (RG) were tested in two Petunia lines (Mitchell and V30). Growth conditions differed in Mitchell and V30, and different methods were used for RNA isolation and analysis. Four different software tools were employed to analyze the data. We merged the four outputs by means of a non-weighted unsupervised rank aggregation method. The genes identified as optimal for transcriptomic analysis of Mitchell and V30 were EF1alpha in Mitchell and CYP in V30, whereas the least suitable gene was GAPDH in both lines. CONCLUSIONS: The least adequate gene turned out to be GAPDH indicating that it should be rejected as reference gene in Petunia. The absence of correspondence of the best-suited genes suggests that assessing reference gene stability is needed when performing normalization of data from transcriptomic analysis of flower and leaf development.

The purpose of this study is to examine the relationship between absorptive capacity and company innovativeness and to identify potential contexts and capabilities that can act as catalysts for these relationships. We also examine the relationship between absorptive capacity and the existence and enhancement of innovativeness. These relationships are examined through an empirical investigation of 286 large Spanish companies. Our results show that absorptive capacity is an important dynamic determinant for developing a company's innovativeness. Moreover, this relationship is best explained by two related constructs. First, the company's unlearning context is a crucial determinant for both potential capacity and realized absorptive capacity. Second, the results also indicate a tangible means for managers to enhance their absorptive capacity through information systems capabilities.

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.