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Differences in family functioning before and during the COVID-19 pandemic: an observational study in Peruvian families

The COVID-19 pandemic has had a major impact on family relationships, as several families have lost family members due to COVID-19 pandemic and become physically and emotionally estranged due to lockdown measures and critically economic periods. Our study contrasted two hypotheses: (1) family functioning changed notably before and after the COVID-19 pandemic initiation in terms of cohesion, flexibility, communication and satisfaction; (2) balanced families have a greater capacity to strictly comply with quarantine (i.e., social confinement), compared to unbalanced families. We performed an observational study comparing family functioning between two independent groups, evaluated before and during the first wave of the COVID-19 pandemic in Peru. A total of 7,980 participants were included in the study. For the first hypothesis, we found that, during the pandemic, families became more balanced in terms of cohesion (adjusted before-during mean difference or β1= 1.4; 95% CI [1.0–1.7]) and flexibility (β2= 2.0; 95% CI [1.6–2.4]), and families were less disengaged (β3= −1.9; 95% CI [−2.3 to −1.5]) and chaotic (β4= −2.9; 95% CI [−3.3 to −2.4]). Regarding the second hypothesis, we confirmed that families with balanced cohesion (adjusted prevalence ratio or aPR = 1.16; 95% CI [1.12–1.19) and flexibility (aPR = 1.23; 95% CI [1.18–1.27]) allowed greater compliance with quarantine restrictions; while disengaged (aPR = 0.91; 95% CI [0.88–0.93]) and chaotic families (aPR = 0.89; 95% CI [0.87–0.92]) were more likely to partially comply or not comply with the quarantine. Finally, family communication (aPR = 1.17; 95% CI [1.11–1.24]) and satisfaction (aPR = 1.18; 95% CI [1.11–1.25]) also played a role in favouring quarantine compliance. This new evidence enlightens the family systems theory while informing future interventions for improving compliance with quarantine measures in the context of social confinement.

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Auditoria de la Calidad para Fidelizar, Formalizar Servicios de Taxi en Economía Informal, Huaraz, 2023

El propósito de la investigación consistió en determinar la relación entre la auditoria de la calidad de servicio y la fidelidad del cliente en el transporte de taxi operando en una economía informal, 2023; asimismo describir la situación actual de la auditoría de calidad del servicio, la fidelidad de clientes y la formalización del transporte de taxis en el distrito de Huaraz, el enfoque fue cuantitativo, con diseño no experimental, documental, descriptiva y correlacional. La población conformada por 42,426 personas y la muestra fue de 384 encuestados, se empleó el muestreo no probabilístico por conveniencia, la recopilación de datos se obtuvo por medio de un cuestionario. Para determinar y demostrar que la relación es directa se aplicó el estadístico d de Somers. Se concluye que la relación es directa entre la auditoria de la calidad de servicio y la fidelidad del cliente. En lo que respecta al panorama actual, los datos muestran que la auditoría de calidad del servicio como la fidelización en el sector de transporte exhiben cifras negativas. Además, se observa que el 65% de los vehículos de taxis en Huaraz operan en una economía informal, se resalta la necesidad apremiante de impulsar la formalización de este sector.

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Gestión y Desafíos del Turismo en Huaraz, Perú: Impacto, Coordinación y Propuestas para Promover Alianzas

El objetivo de la presente investigación fue analizar el impacto del turismo y la gestión de la actividad turística; así como evaluar la gestión y coordinación en el sector turístico de Huaraz; además de formular propuestas para fortalecer la creación de redes y colaboración, la investigación fue exploratoria, descriptiva y no experimental desarrollada entre 2018 y 2020 que usó una metodología de carácter mixto. Se realizó trabajo de campo en la ciudad de Huaraz, Perú entre agosto y noviembre de 2019 con la aplicación de una encuesta (N=266) y entrevistas en profundidad (N=17) a operadores turísticos, hoteles, restaurantes, empresas de transporte y autoridades públicas, además de la realización de un focus group con guías de montaña. En el marco teórico se discuten distintas definiciones de colaboración y cómo ésta se manifiesta en formas diversas de organización. Luego, a partir de la recolección de información se discuten distintos problemas de colaboración en la industria como la falta de regulación a la informalidad y fiscalización, duplicación de actividades, falta de promoción de destinos, y la necesidad de una mejor calidad de prestación de servicios coordinados entre distintas empresas, así como el cuidado del medioambiente por parte de la cadena de proveedores de servicios turísticos. Finalmente, en el artículo se discuten algunas ideas para tejer redes de colaboración que puedan hacerse cargo de estas dificultades.

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Auditoria de la Calidad para Fidelizar, Formalizar Servicios de Taxi en Economía Informal, Huaraz, 2023

El propósito de la investigación consistió en determinar la relación entre la auditoria de la calidad de servicio y la fidelidad del cliente en el transporte de taxi operando en una economía informal, 2023; asimismo describir la situación actual de la auditoría de calidad del servicio, la fidelidad de clientes y la formalización del transporte de taxis en el distrito de Huaraz, el enfoque fue cuantitativo, con diseño no experimental, documental, descriptiva y correlacional. La población conformada por 42,426 personas y la muestra fue de 384 encuestados, se empleó el muestreo no probabilístico por conveniencia, la recopilación de datos se obtuvo por medio de un cuestionario. Para determinar y demostrar que la relación es directa se aplicó el estadístico d de Somers. Se concluye que la relación es directa entre la auditoria de la calidad de servicio y la fidelidad del cliente. En lo que respecta al panorama actual, los datos muestran que la auditoría de calidad del servicio como la fidelización en el sector de transporte exhiben cifras negativas. Además, se observa que el 65% de los vehículos de taxis en Huaraz operan en una economía informal, se resalta la necesidad apremiante de impulsar la formalización de este sector.

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Prevalence of Antimicrobial Resistance in Gram-Negative Bacteria Bloodstream Infections in Peru and Associated Outcomes: VIRAPERU Study.

Surveillance of antimicrobial resistance among gram-negative bacteria (GNB) is of critical importance, but data for Peru are not available. To fill this gap, a non-interventional hospital-based surveillance study was conducted in 15 hospitals across Peru from July 2017 to October 2019. Consecutive unique blood culture isolates of key GNB (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter spp.) recovered from hospitalized patients were collected for centralized antimicrobial susceptibility testing, along with linked epidemiological and clinical data. A total of 449 isolates were included in the analysis. Resistance to third-generation cephalosporins (3GCs) was present in 266 (59.2%) GNB isolates. Among E. coli (n = 199), 68.3% showed 3GC resistance (i.e., above the median ratio for low- and middle-income countries in 2020 for this sustainable development goal indicator). Carbapenem resistance was present in 74 (16.5%) GNB isolates, with wide variation among species (0% in E. coli, 11.0% in K. pneumoniae, 37.0% in P. aeruginosa, and 60.8% in Acinetobacter spp. isolates). Co-resistance to carbapenems and colistin was found in seven (1.6%) GNB isolates. Empiric treatment covered the causative GNB in 63.3% of 215 cases. The in-hospital case fatality ratio was 33.3% (92/276). Pseudomonas aeruginosa species and carbapenem resistance were associated with higher risk of in-hospital death. In conclusion, an important proportion of bloodstream infections in Peru are caused by highly resistant GNB and are associated with high in-hospital mortality.

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The Comprehension of Expository Texts In Students: A Systematic Review Study Between 2017-2022

The present study aims to systematize the scientific literature regarding the comprehension of expository texts in students. The study used the PRISMA method to identify studies in the Scopus, Web of Science (WoS), EBSCO, Scielo and ERIC databases in the period 2017-2022. A total of 1421 records were identified, which went through inclusion and exclusion criteria, where finally 14 included studies remained. These studies sought to answer the research question: What are the most used strategies for the compression of expository texts in students? The data collected based on the systematization of the studies was structured into 2 matrices based on the authors, countries according to the corresponding author, keywords, dimensions, instruments used, approaches, application strategies and the conclusions of the studies in order to find possible methodological or conclusion similarities, verifying strengths or weaknesses that have been presented by studies on the comprehension of expository texts in students. The results analyzed show that Argentina is the country with the highest frequency of publications regarding correspondence between authors. Similarly, among the keywords that stand out we have expository text, reading comprehension, oral comprehension, learning strategies, self-regulation, reading strategies, writing strategies. According to the content studied, it is concluded that, among the most frequent strategies for the compression of expository texts, is the use of paraphrasing, literalness, macro-rules, the memorization technique, paper or digital notes, organizers graphics and digital strategies. In addition, comprehension difficulties were found in the studies due to the complex structure of the expository texts. On the other hand, a strong relationship was identified between self-regulation and comprehension of expository texts, the greater the regulation of student learning, the greater the general comprehension of expository texts.

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Antispasmodic Effect of Valeriana pilosa Root Essential Oil and Potential Mechanisms of Action: Ex Vivo and In Silico Studies.

Infusions of Valeriana pilosa are commonly used in Peruvian folk medicine for treating gastrointestinal disorders. This study aimed to investigate the spasmolytic and antispasmodic effects of Valeriana pilosa essential oil (VPEO) on rat ileum. The basal tone of ileal sections decreased in response to accumulative concentrations of VPEO. Moreover, ileal sections precontracted with acetylcholine (ACh), potassium chloride (KCl), or barium chloride (BaCl2) were relaxed in response to VPEO by a mechanism that depended on atropine, hyoscine butylbromide, solifenacin, and verapamil, but not glibenclamide. The results showed that VPEO produced a relaxant effect by inhibiting muscarinic receptors and blocking calcium channels, with no apparent effect on the opening of potassium channels. In addition, molecular docking was employed to evaluate VPEO constituents that could inhibit intestinal contractile activity. The study showed that α-cubebene, β-patchoulene, β-bourbonene, β-caryophyllene, α-guaiene, γ-muurolene, valencene, eremophyllene, and δ-cadinene displayed the highest docking scores on muscarinic acetylcholine receptors and voltage-gated calcium channels, which may antagonize M2 and/or M3 muscarinic acetylcholine receptors and block voltage-gated calcium channels. In summary, VPEO has both spasmolytic and antispasmodic effects. It may block muscarinic receptors and calcium channels, thus providing a scientific basis for its traditional use for gastrointestinal disorders.

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Classification of Tweets Related to Natural Disasters Using Machine Learning Algorithms

Identifying and classifying text extracted from social networks, following the traditional method, is very complex. In recent years, computer science has advanced exponentially, helping significantly to identify and classify text extracted from social networks, specifically Twitter. This work aims to identify, classify and analyze tweets related to real natural disasters through tweets with the hashtag #NaturalDisasters, using Machine learning (ML) algorithms, such as Bernoulli Naive Bayes (BNB), Multinomial Naive Bayes (MNB), Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF). First, tweets related to natural disasters were identified, creating a dataset of 122k geolocated tweets for training. Secondly, the data-cleaning process was carried out by applying stemming and lemmatization techniques. Third, exploratory data analysis (EDA) was performed to gain an initial understanding of the data. Fourth, the training and testing process of the BNB, MNB, L, KNN, DT, and RF models was initiated, using tools and libraries for this type of task. The results of the trained models demonstrated optimal performance: BNB, MNB, and LR models achieved a performance rate of 87% accuracy; and KNN, DT, and RF models achieved performances of 82%, 75%, and 86%, respectively. However, the BNB, MNB, and LR models performed better with respect to performance on their respective metrics, such as processing time, test accuracy, precision, and F1 score. Demonstrating, for this context and with the trained dataset that they are the best in terms of text classifiers.

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