Simple Series Research Articles

Consumer Credit: a Historical Review of the Impact on the Ecuadorian Economy, Period 2005 – 2024

Objective: Analyze consumer credit and its impact on the Ecuadorian economy, period 2005 – 2024. Theoretical Framework: The theoretical framework of the Keynesian school was used, in which the role of financial institutions is crucial for driving economic growth through the financing of consumption. Method: Quantitative research with a depth of descriptive analysis; 78 quarterly data points were used for Pearson's tests and for the simple time series regression model. Results and Discussion: The trend of consumer credit was positive during the research period; however, its economic contribution fluctuated according to the economic context or cycle. It was significant during times of boom, when it accounted for approximately 4.38% of PIB between 2011 and 2014. In contrast, during the 2005–2024 period, the results showed that it had a moderate impact on PIB, but it was not significant for economic growth, as the Ecuadorian economy operates in an imperfect competition market. Originality/Value: This study allows for the verification of the theoretical assumptions in the Ecuadorian case; additionally, it provides relevant conclusions that explain the model and characteristics of the market.

Anisotropic Thermal Transport in Tunable Self-Assembled Nanocrystal Supercrystals.

Realizing tunable functional materials with built-in nanoscale heat flow directionality represents a significant challenge that could advance thermal management strategies. Here we use spatiotemporally resolved thermoreflectance to visualize lateral thermal transport anisotropy in self-assembled supercrystals of anisotropic Au nanocrystals. Correlative electron and thermoreflectance microscopy reveal that nano- to mesoscale heat predominantly flows along the long-axis of the anisotropic nanocrystals, and does so across grain boundaries and curved assemblies while voids disrupt heat flow. We finely control the anisotropy via the aspect ratio of constituent nanorods, and it exceeds the aspect ratio for nanobipyramid supercrystals and certain nanorod arrangements. Finite element simulations and effective medium modeling rationalize the emergent anisotropic behavior in terms of a simple series resistance model, further providing a framework for estimating thermal anisotropy as a function of material and structural parameters. Self-assembly of colloidal nanocrystals promises an interesting route to direct heat flow in a wide range of applications that utilize this important class of materials.

Using ARIMA and ETS models for forecasting water level changes for sustainable environmental management

It is vital to provide useful hydrological forecasts for urban and agricultural water management, hydropower generation, flood protection and management, drought mitigation and alleviation, and river basin planning and management, among other things. This paper introduces a simple and flexible hydrological time series forecasting framework. Predicting water levels is crucial, given the need for sustainable environmental management. The prognosis should be reasonable to persuade individuals to take proper precautions. While many methods have been developed to predict water levels, here the effectiveness of two approaches to predicting river water levels was assessed. For this purpose, nine years of data were used, which were divided into input data (2014–2021) and validation data (2022), on water levels in the Morava e Binçës river for the Vitia station, in the form of monthly time series records, to identify the best model among those used and to identify the information necessary for water resource management and hazard control. Models Autoregressive Integrated Moving Average(ARIMA) and Error Trend and Seasonality, or Exponential Smoothing (ETS), were examined using the R package to determine the most accurate. The results indicate the applicability of both models, as evidenced by the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The predictive analysis based on historical water levels allowed the identification of distinct periods characterized by high and low water levels between 2022 and 2024, which is important for the area in question due to the numerous flood events occurring here.

Reservoir computing with logistic map.

Recent studies on reservoir computing essentially involve a high-dimensional dynamical system as the reservoir, which transforms and stores the input as a higher-dimensional state for temporal and nontemporal data processing. We demonstrate here a method to predict temporal and nontemporal tasks by constructing virtual nodes as constituting a reservoir in reservoir computing using a nonlinear map, namely, the logistic map, and a simple finite trigonometric series. We predict three nonlinear systems, namely, Lorenz, Rössler, and Hindmarsh-Rose, for temporal tasks and a seventh-order polynomial for nontemporal tasks with great accuracy. Also, the prediction is made in the presence of noise and found to closely agree with the target. Remarkably, the logistic map performs well and predicts close to the actual or target values. The low values of the root mean square error confirm the accuracy of this method in terms of efficiency. Our approach removes the necessity of continuous dynamical systems for constructing the reservoir in reservoir computing. Moreover, the accurate prediction for the three different nonlinear systems suggests that this method can be considered a general one and can be applied to predict many systems. Finally, we show that the method also accurately anticipates the time series of the all the three variable of Rössler system for the future (self-prediction).

A Perfect Infinite Series

Summary We show that the sum of the series ∑ n = 1 ∞ ( n 2 / 2 n ) is the perfect number 6, using simpler series with sums 1, 2, 3, which are the proper divisors of 6.

A novel capacitive sensor interface based on a simple capacitance-to-phase converter

Abstract A novel room temperature capacitive sensor interface circuit is proposed and successfully tested, which uses a modified All-Pass filter architecture combined with a simple series resonant tank circuit with a moderate Q-factor. It is fashioned from a discrete inductor with small dissipation resonating with a grounded capacitor acting as the sensing element to obtain a resolution of ∆C ~ 2 zF in a capacitance range of 10 – 30 pF. The circuit converts the change in capacitance to the change in the phase of a carrier signal in a frequency range with a central frequency set up by the tank circuit’s resonant frequency and is configured to act as a close approximation of the ideal All-Pass filter. This cancels out the effects of amplitude modulation when the carrier signal is imperfectly tuned to the resonance. The proposed capacitive sensor interface has been specifically developed for use as a front-end constituent in ultra-precision mechanical displacement measurement systems, such as accelerometers, seismometers, gravimeters and gravity gradiometers, where moving plate grounded air gap capacitors are frequently used. Some other applications of the proposed circuit are possible including the measurement of the electric field, where the sensing capacitor depends on the applied electric field, and cost effective capacitive gas sensors. In addition, the circuit can be easily adapted to function with very small capacitance values (1 - 2 pF) as is typical in MEMS-based transducers.

Design of an electrically small printed square loop antenna for closely spaced Tx/Rx systems

AbstractA highly miniaturised electrically small square loop antenna has been designed for operation at 2.5 GHz. The antenna is loaded using a simple series combination of two lumped inductors and two interdigitated capacitors in order to realise inherent impedance matching at a given miniaturisation level with respect to a specified source impedance, without using any external matching network. The designed antenna has an overall size of 0.061λ0 × 0.061λ0, which is approximately 75.6% miniaturised in terms of total loop length and 94% miniaturised in terms of overall footprint. The designed antenna is fabricated and the corresponding impedance matching and radiation patterns are measured, which are found to be in reasonable agreement with their simulated counterparts. Moreover, an investigation with two closely spaced electrically small SLAs, one for transmitting and the other for receiving, is carried out in this work in pursuit of maximising the isolation, which plays a crucial role in the Tx/Rx systems.

Wavelet Transform-Based Inertial Neural Network for Spatial Positioning Using Inertial Measurement Units

As the demand for spatial positioning continues to grow, positioning methods based on inertial measurement units (IMUs) are emerging as a promising research topic due to their low cost and robustness against environmental interference. These methods are particularly well suited for global navigation satellite system (GNSS)-denied environments and challenging visual scenarios. While existing algorithms for position estimation using IMUs have demonstrated some effectiveness, there is still significant room for improvement in terms of estimation accuracy. Current approaches primarily treat IMU data as simple time series, neglecting the frequency-domain characteristics of IMU signals. This paper emphasizes the importance of frequency-domain information in IMU signals and proposes a novel neural network, WINNet (Wavelet Inertial Neural Network), which integrates time- and frequency-domain signals using a wavelet transform for spatial positioning with inertial sensors. Additionally, we collected ground-truth data using a LiDAR setup and combined it with the TLIO dataset to form a new IMU spatial positioning dataset. The experimental results demonstrate that our proposed method outperforms the current state-of-the-art inertial neural network algorithms in terms of the ATE, RTE, and drift error metrics overall.

Research on topology technology of integrated battery energy storage system with reconfigurable battery and converter

In traditional battery energy storage systems (BESS), batteries are usually connected in a simple series or parallel form, and separate converters and balancing modules are typically used for energy exchange between the battery and external sources, as well as for balancing energy between batteries. This paper proposes an integrated battery energy storage system (IBESS) with reconfigurable batteries and DC/DC converters, resulting in a more compact structure. The IBESS can reconfigure the connection of energy storage batteries based on the battery's status and external demand. The DC/DC converters can operate in different modes such as boost, buck, or buck-boost converters. The IBESS has five working modes: discharging mode, balancing mode, battery discharging and balancing mode, constant current and constant voltage (CCCV) charging mode and backup mode. To verify the feasibility of the proposed energy storage system, a model with four battery modules was built using MATLAB/SIMULINK, and the operation of all working modes was demonstrated. The simulation results verified the system's performance and reliability, demonstrating its flexibility and efficiency in different operating modes.

Single-nucleus RNA sequencing and lipidomics reveal characteristics of transcriptional and lipid composition in porcine longissimus dorsi muscle

BackgroundGlobal per capita meat consumption continues to rise, especially pork. Meat quality is influenced by the content of intramuscular fat (IMF) as a key factor. The longissimus dorsi muscle of Dahe pigs (DHM, IMF: 7.98% ± 1.96%) and Dahe black pigs (DHBM, IMF: 3.30% ± 0.64%) was studied to explore cellular heterogeneity and differentially expressed genes (DEGs) associated with IMF deposition using single-nucleus RNA sequencing (snRNA-seq). The lipid composition was then analyzed using non-targeted lipidomics.ResultsA total of seven cell subpopulations were identified, including myocytes, fibroblast/fibro/adipogenic progenitors (FAPs), satellite cells, endothelial cells, macrophages, pericytes, and adipocytes. Among them, FAPs and adipocytes were more focused because they could be associated with lipid deposition. 1623 DEGs in the FAPs subpopulation of DHBM were up-regulated compared with DHM, while 1535 were down-regulated. These DEGs enriched in the glycolysis/gluconeogenesis pathway. 109 DEGs were up-regulated and 806 were down-regulated in the adipocyte subpopulation of DHBM compared with DHM, which were mainly enriched in the PPAR signaling pathway and fatty acid (FA) biosynthesis. The expression level of PPARG, ABP4, LEP, and ACSL1 genes in DHM was higher than that in DHBM. Lipidomics reveals porcine lipid composition characteristics of muscle tissue. A total of 41 lipid classes and 2699 lipid species were identified in DHM and DHBM groups. The top ten relative peak areas of lipid classes in DHM and DHBM were triglyceride (TG), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), diglyceride (DG), cardiolipin (CL), ceramides (Cer), Simple Glc series (Hex1Cer), sphingomyelin (phSM), and phosphatidylinositol (PI). The relative peak areas of 35 lipid species in DHM were lower than DHBM, and 28 lipid species that were higher. There was a significant increase in the TG fatty acyl chains C6:0, C17:0, and C11:4, and a significant decrease in C16:0, C18:1, C18:2, and C22:4 in DHBM (p < 0.05).ConclusionsC16:0 FA may downregulate the expression level of PPARG gene, which leads to the downregulation of fat metabolism-related genes such as ACSL, PLIN2, and FABP4 in DHBM compared with DHM. This may be the reason that the lipid deposition ability of Dahe pigs is stronger than that of Dahe black pigs, which need further investigation.

Collaborative Counseling to Build a Social Construct to Overcome Alcoholic Addiction

Alcohol consumption by teenagers is influenced by environmental factors. To overcome alcohol addiction among teenagers, a social construction needs to be built. So efforts are needed to overcome alcohol addiction, namely through collaborative counseling. In Collaborative Counseling the relationships and conversations create something different bringing together the collection, application, innovation and expansion of ideas involving working professionals from various disciplines, contexts and cultures, by detailing what they actually do every day for individuals, couples, families and groups . This research uses a Mixed Method with the Triangular Design type, namely collecting quantitative and qualitative data simultaneously. Quantitative research was conducted to answer the first research question, how addicted the sample was to alcohol during the research. By using Time-series Design with a simple interrupted Time Series approach with a sample size of 8 people. The qualitative research used in this research is a phenomenological approach, namely research that answers what certain phenomena are about. This research will also be used to interpret meaning in context. From the results obtained in this research, it was found that Collaborative Counseling was successful in eliminating addiction in the research sample.

INSIHGT: A scalable and homogeneous 3D multiplexed molecular mapping platform for spatial biology and precision medicine.

e15180 Background: The dynamic interplay between cancer cells and their microenvironment is a determinant of disease evolution and response to treatment. However, the current state of three-dimensional (3D) tumor microenvironment analysis is hindered by inadequate penetration of antibodies into thick tissue sections, leading to a substantial gap in acquiring unbiased, precise 3D multiplexed immunohistochemistry (IHC) images. Methods: We developed INSIHGT to surmount these limitations by enabling multi-round, multiplexed 3D IHC in standard formalin-fixed tissues. This fully automatable, fast-track method requires a simple series of chemical cocktail exchanges, translating to a tissue-to-image time of 6 days for 1 cm³ samples and as little as 6 hours for biopsy specimens. INSIHGT offers a scalable and efficient solution for detailed 3D spatial mapping of cancerous cells and their interactions within their native context. Results: 3D IHC with INSIHGT shows ideal penetration homogeneity, which quantitatively matches reference signals in 1cm3 samples. We further validated INSIHGT with 309 commercially available primary antibodies and is compatible with simultaneous fluorescent in situ hybridization (FISH) to detect RNA transcripts or DNA chromosomal abnormalities. Notably, the quality of post-INSIHGT traditional histological analyses, such as H&amp;E and standard IHC, was not altered. We demonstrated a 3D mapping of over 20 markers in a 1 mm-thick tumor sample across seven INSIHGT cycles, and an atlas of multiple tumour samples with 3D IHC &amp; H&amp;E. The large datasets seamlessly integrates with single-cell segmentation and analysis workflows, yielding comprehensive maps that elucidate protein expression, cell morphology, spatial positioning, and potential cell-cell interactions. Conclusions: INSIHGT provides an unparalleled level of visualization and analytical detail concerning the spatial dynamics within the tumor microenvironment at a single-cell resolution. As a transformative next generation histopathology platform, it can uncover new structural and molecular details within clinical specimens, accelerating biomarker discovery and novel diagnostic assays development, thereby enriching the field of tumor biology and propelling the progress of personalized oncology treatments.

Efficient semianalytical investigation of a fractional model describing human cornea shape

Purpose: This study presents a novel application of the semianalytical residual power series method to investigate a one-dimensional fractional anisotropic curvature equation describing the human cornea, the outermost layer of the eye. The fractional boundary value problem, involving the fractional derivative of curvature, poses challenges that conventional methods struggle to address. Methods: The analytical results are obtained by utilizing the simple and efficient residual power series method. The proposed method is accessible to researchers in all medical fields and is extendable to various models in disease spread and control. Results: The derived solution is a crucial outcome of this study. Through the application of the proposed method to the corneal shape model, an explicit formula for the curvature profile is obtained. To validate the solution, direct comparisons are made with numerical solutions for the integer case and other analytical solutions available in the literature for the fractional case. Conclusion: Our findings highlight the potential of the proposed method to significantly contribute to the diagnosis and treatment of various ophthalmological conditions.

Fast, Simple, and Accurate Time Series Analysis with Large Language Models: An Example of Mean-motion Resonances Identification

Classical machine learning has been actively utilized in astronomy to address various challenges, including predicting orbital stability, classifying asteroids, galaxies, and other objects, and analyzing images. However, the emerging trend in artificial intelligence involves the use of large language models such as GPT-4 and ChatGPT. These models are trained on a large corpus of text and can perform a wide range of natural language processing tasks, including text generation, translation, summarization, and classification. Surprisingly, these capabilities present significant potential for application in astronomy. This paper demonstrates how the new model gpt-4-vision-preview can analyze visual patterns and accurately classify asteroids as resonant or nonresonant with high accuracy. This process requires no training, fine-tuning, or coding beyond writing the appropriate prompt in natural language. Moreover, this approach can be extended to other common problems within astronomy.

Interoceptive posture awareness and accuracy: a novel photographic strategy towards making posture actionable.

Interoception, sometimes referred to as the 'hidden sense,' communicates the state of internal conditions for autonomic energy regulation and is important for human motor control as well as self-awareness. The insula, the cortex of interoception, integrates internal senses such as hunger, thirst and emotions. With input from the cerebellum and proprioceptive inputs, it creates a vast sensorimotor network essential for static posture and dynamic movement. With humans being bipedal to allow for improved mobility and energy utilization, greater neuromotor control is required to effectively stabilize and control the four postural zones of mass (i.e., head, torso, pelvis, and lower extremities) over the base of support. In a dynamic state, this neuromotor control that maintains verticality is critical, challenging energy management for somatic motor control as well as visceral and autonomic functions. In this perspective article, the authors promote a simple series of posture photographs to allow one to integrate more accurate alignment of their postural zones of mass with respect to the gravity line by correlating cortical interoception with cognitive feedback. Doing this focuses one on their body perception in space compared to the objective images. Strengthening interoceptive postural awareness can shift the net result of each zone of postural mass during day-to-day movement towards stronger posture biomechanics and can serve as an individualized strategy to optimize function, longevity, and rehabilitation.

Long-term impact of COVID-19 pandemic on antibiotic use in primary care: lessons to optimize antimicrobial use

ABSTRACT Background Lockdowns due to the COVID-19 pandemic was associated with changes in the pattern of use of antimicrobials, but persistence of changes after lockdowns has not been described. The objective was to describe the number of patients with dispensed antibiotic treatment and consumption of antibiotics in outpatients from primary care in Catalonia 18 months after the end of the emergency period. Research design and methods Data for the COVID-19 pandemic period was obtained from March 2020 to December 2021. Four high transmission rate (Rt > 100) periods were established. To compare data, a simple Bayesian structural time series model was used. Results The observed number of patients with dispensed antibiotics decreased respect to the estimated, especially during the four high transmission rate periods: April–May 2020 (lockdown period) (−42.57% and −42.68%); December 2020-February 2021 (−41.65%, −49.97% and −43.64%); October 2021 (−16.23%), and December 2021 (−20.16%). Overall antibiotic consumption was reduced by 23.37% (p = 0.002). These differences were mainly observed in those ≤ 15 years. Conclusions We describe the reduction in the number of patients with dispensed antibiotics and antibiotic consumption after the COVID-19 lockdown persisted in a period of recovery of healthcare accessibility. This information may help to improve antimicrobial use at the primary care level.

Copula‐based Bayesian reliability assessment for series systems

AbstractBayesian reliability assessment plays an integral role in determining the success of product development and deployment into the market, especially when limited information is available to estimate the reliability of products. Nevertheless, the Bayesian reliability approach has untapped research potential when it is used to evaluate systems consisting of dependent components, that is, a situation that reflects real‐world conditions. This study addresses the research gap by applying a copula to encode the dependency structure between the failure rates of the components, particularly for the simple series systems. Unfortunately, this study found that Bayesian aggregation error still occurs when information is used at different levels. By employing Monte Carlo simulation and classification tree learning, this study also investigates the key factors affecting such error over a wide range of possible scenarios and derives useful guidelines for reliability practitioners so that they can choose a more suitable analysis under certain circumstances.

Simulation in pediatric minimally invasive surgery: adaptation of a simple series of exercises as part of the process of an initial implementation of a resident training program.

the simulation in minimally invasive surgery is fundamental for surgeon in training to learning and training skills, especially in pediatrics, due to the particularities, reduced spaces, specific and rare procedures. The aim of this study was to propose an adapted series of exercises and to simply evaluate the performance of pediatric surgery residents in the initial implementation of a training program. seven basic skills exercises in video surgery, based on series and programs already published and using low-cost materials, were performed by six residents in 2 moments, with an interval of 15 days and evaluated by simple instrument. there was no difficulty with models. Considering the individual averages of the seven exercises together in the two moments, five of the six residents increased the score in the second moment. The average score per exercise increased in five of the seven tasks. Despite the small number of participants and repetition, it has already been possible to observe a trend of better performance with decreased time of all residents after a single repetition. All considered the exercises capable of training essential skills of the specialty, with simple and inexpensive materials. given the challenges of simulated training in pediatric video surgery, it is known the benefit of a continuous program, with exercises that can simulate real situations. A pre-established schedule, more participants and repetitions, supervision of experienced surgeons and validated instruments are fundamental to evaluate surgeons in training and show statistical benefits of simulated exercises in this series.

Tourism, Inequality and Segregation in The North Lombok Regency

The aim of this research is to look at the effects of tourism spatially and examine its impact on the aggregate welfare of the population. Therefore, the author asks two fundamental questions in this research. First, is the rapid demand for tourism capable of creating new regional growth poles spatially? Second, is increasing tourism receipts able to create welfare effects. The method used in this research is simple time series correlation and regression. The findings in this research are that the dependent variables tend to have a strong influence on education and employment indicators. Tourism seems to only have a false effect on economic activity in North Lombok Regency. It is proven that since this district was expanded, there have been no significant growth poles in this region. Regional and economic segregation is still clearly visible today.

Using responsive feedback from routine monitoring data to guide course corrections for a family planning intervention in Nigeria.

This paper aims to promote the use of simple interrupted time series (ITS) analyses of routine data as a responsive feedback tool to improve public health programs. Although advanced ITS techniques exist, their use is often not feasible due to limitations in funding or research capacity. We propose an Excel-based analysis that requires minimal resources or statistical expertise, and illustrate it by measuring the effect of a radio campaign to promote a family planning call center in Nigeria on the demand for family planning information. We used a single group interrupted time series design (ITS) as a responsive feedback mechanism to determine whether the radio campaign influenced use of the Honey&Banana call center. ITS is ideal when there is no control group. ITS uses the pre-intervention trend to predict what would have happened if the intervention were absent. After conducting ITS analyses, the results show that the number of calls requesting family planning information increased throughout the campaign period, with a gain of about 500 additional calls per month, and then decreased after the campaign ended. However, the number of calls gained from the campaign was substantially lower than anticipated. While end-of-project impact evaluations are necessary, there should be regular feedback system to provide program implementers with information about the status of the project, such as failures, successes, and areas of improvements. This would allow implementers to make necessary adjustments as needed throughout the intervention period. The finding that the radio campaign was not living up to expectations helped Honey&Banana program implementers to end the campaign prematurely and re-allocate resources to a more promising activity. Our research shows that basic Excel-based ITS analysis of routine data can be a useful tool for receiving regular feedback to guide programming improvements for organizations that have limited resources and/or research capacity.