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Introducción: La mastitis granulomatosa es una enfermedad inflamatoria crónica benigna de etiología desconocida y buen pronóstico, sin embargo, es una entidad de difícil diagnóstico debido a sus hallazgos inespecíficos y variabilidad en los diagnósticos diferenciales. Objetivo: Brindar herramientas útiles en el diagnóstico oportuno de mastitis granulomatosa con sus principales hallazgos imagenológicos. Materiales y métodos: Se realizó un análisis retrospectivo de los hallazgos imagenológicos en 17 mujeres con diagnóstico histopatológico de mastitis granulomatosa entre enero del 2017 y marzo del 2019 con una revisión bibliográfica del tema. Resultados: De 17 pacientes con resultado histopatológico de mastitis granulomatosa, 15 fueron valoradas inicialmente con ultrasonografía, encontrando que el 53,3% presentaron masa heterogénea hipoecoica, seguido de extensiones tubulares en un 46,6%, además un 26,6% presentó masa circunscrita, colección y adenopatías axilares hallazgos acordes con la literatura mundial. Solo a una paciente se le realizó mamografía, en la cual se encontró una asimetría focal de la densidad del tejido mamario siendo el hallazgo más frecuente. Se realizó a una paciente resonancia magnética con realce no masa y fístula cutánea como complicación, que equivale al 6,6%. Conclusión: Nuestros hallazgos imagenológicos son concordantes con la literatura mundial y se logró identificar las características radiológicas centrados principalmente en ultrasonido.

The accurate recognition of activities is fundamental for following up on the health progress of people with dementia (PwD), thereby supporting subsequent diagnosis and treatments. When monitoring the activities of daily living (ADLs), it is feasible to detect behaviour patterns, parse out the disease evolution, and consequently provide effective and timely assistance. However, this task is affected by uncertainties derived from the differences in smart home configurations and the way in which each person undertakes the ADLs. One adjacent pathway is to train a supervised classification algorithm using large-sized datasets; nonetheless, obtaining real-world data is costly and characterized by a challenging recruiting research process. The resulting activity data is then small and may not capture each person’s intrinsic properties. Simulation approaches have risen as an alternative efficient choice, but synthetic data can be significantly dissimilar compared to real data. Hence, this paper proposes the application of Partial Least Squares Regression (PLSR) to approximate the real activity duration of various ADLs based on synthetic observations. First, the real activity duration of each ADL is initially contrasted with the one derived from an intelligent environment simulator. Following this, different PLSR models were evaluated for estimating real activity duration based on synthetic variables. A case study including eight ADLs was considered to validate the proposed approach. The results revealed that simulated and real observations are significantly different in some ADLs (p-value < 0.05), nevertheless synthetic variables can be further modified to predict the real activity duration with high accuracy (R2(pred)>90%).

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

Methodology: In a project named Carmen (after its initials in Spanish)a screening program was performed in twenty neighborhoodson women who do not have social security or insurance. We wantto show the results of the fi rst phase of this study made in 2005(clinical, mammographic and ultrasonographic findings) in Bucaramanga. Results: A total of 1.054 procedures were performed on527 women whose average age was 53,9. (SD: 11 years). Themain complaint was breast pain, 13,1% (138 patients), 1,6% (17patients) of the women surveyed reported to have a lump, aftermedical examination a lump was confirmed in 20% of the patients.Comparing de clinical findings, mammography and breast ultrasound211 lumps were diagnosticated by physical exam, mammographyonly shows 14 and breast ultrasound 52 of these masses 44masses in mammography and 152 masses in breast ultrasounddidn´t find at the physical exam. The calcifications were the mostfrequent find, 4% were classified malignant. Cysts were found in1,2% of the fatty breast, 14,5%, 37,7% and 41,8% in dense breast(mild, moderate and severe) respectively. Comparing the clinicalfindings, mammography and breast ultrasound the clinical examis not good for use in screening alone. Conclusion: The use ofbreast ultrasound with mammography increase the detection ofbreast lesions and provide a better description of masses.

Breast ultrasound is the second most used imaging method aftermammography in the evaluation of breast lesions because of itslow cost, accessibility, absence of ionize radiation and ability todifferentiate a solid from a cystic lesion. Also it assesses with accuracy the subcutaneous cellular tissue and the axilar region allowingto detect sebaceous cysts, lymph nodes or abscess. The currentindications include the evaluation of a palpable lesion in a womanless than 30 years old , to characterize cystic lesions, to evaluate palpable and non palpable abnormalities in older women, to guide interventional procedures, and to evaluate breast implants and the breast in pregnant women. The main disadvantages are the difficulty to reproduce the findings, the higher false positive rate and the fact that it is operator dependent. Ultrasound BI-RADS is very importantto grade the lesions and to standarize the procedures. The purposeof this article is to review the mammary ultrasound indications, lesion characterization and to give suggestions according to these findings.