Model-Driven End-to-End Learning for Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is envisioned to be one of the pillars of 6G. However, 6G is also expected to be severely affected by hardware impairments. Under such impairments, standard model-based approaches might fail if they do not capture the underlying reality. To this end, data-driven methods are an alternative to deal with cases where imperfections cannot be easily modeled. In this paper, we propose a model-driven learning architecture for joint single- target multi-input multi-output (MIMO) sensing and multi-input single-output (MISO) communication. We compare it with a standard neural network approach under complexity constraints. Results show that under hardware impairments, both learning methods yield better results than the model-based standard baseline. If complexity constraints are further introduced, model- driven learning outperforms the neural-network-based approach. Model-driven learning also shows better generalization performance for new unseen testing scenario

End-to-End Learning for Integrated Sensing and Communication

Integrated sensing and communication (ISAC) aims to unify radar and communication systems through a combination of joint hardware, joint waveforms, joint signal design, and joint signal processing. At high carrier frequencies, where ISAC is expected to play a major role, joint designs are challenging due to several hardware limitations. Model-based approaches, while powerful and flexible, are inherently limited by how well the models represent reality. Under model deficit, data-driven methods can provide robust ISAC performance. We present a novel approach for data-driven ISAC using an auto-encoder (AE) structure. The approach includes the proposal of the AE architecture, a novel ISAC loss function, and the training procedure. Numerical results demonstrate the power of the proposed AE, in particular under hardware impairments

Plan de negocio para el servicio de una plataforma tecnol?gica que facilite el control del proceso de gestaci?n de mujeres

Presentamos el plan de negocio para ?eMommy?, empresa que otorga el servicio de monitoreo y control autom?tico del proceso de gestaci?n de las mujeres, a trav?s de una app y con el uso intensivo de wearables que, busca identificar en forma oportuna se?ales de riesgo en la salud de la madre y el beb? a trav?s de una medici?n pre programada de tres signos vitales para la madre (Frecuencia cardiaca, temperatura, presi?n arterial) y el nivel de contracciones uterinas para el beb?. El alcance del trabajo es Lima metropolitana y la propuesta de plan de negocio es para la puesta en marcha de la empresa, y sus primeros a?os de funcionamiento. La presente tesis presenta el an?lisis contextual, estudio de mercado y propuesta de modelo de negocio, considerando un plan estrat?gico, plan de operaciones, plan de recursos humanos, plan de marketing, plan legal y plan de tecnolog?as de informaci?n para la empresa; adem?s en cada uno de los planes se incluyen gastos de implementaci?n que son consolidados en el plan financiero donde se proyectan ingresos con cifras validadas a trav?s de entrevistas a expertos, y encuestas en campo. El modelo de negocio considera las leyes y regulaciones establecidas por el estado peruano incluyendo la regulaci?n de protecci?n al consumidor, y seguridad de datos personales

Sex differences and HIV status of tuberculosis in adults at a rural hospital in southern Ethiopia: an 18-year retrospective cross-sectional study

Background. The aim of the study was to compare the epidemiology, clinical characteristics and treatment outcome of tuberculosis (TB), including HIV status, in women and men in southern rural Ethiopia. Methods. We conducted a register-based retrospective cohort study covering the period from September 1998 to August 2015. Results. We included records of 2252 registered TB patients: 1080 (48%) women and 1172 (52%) men. Median age was similar for women and men: 27.5 years and 25.0 years, respectively. Median weight in women was 43.0 kg (interquartile range IQR: 38.0, 49.0), significantly lower than in men (50.0 kg, IQR 44.0, 55.0; p = 0.01). Extrapulmonary TB was significantly more common in women than in men (34.1% versus 28.7%; p=0.006). Treatment outcomes were similar in both sexes: in 70.3% of women and 68.9% of men, TB mortality was slightly lower in women than men (4.7% vs. 6.5%; p=0.08). In patients with TB, female sex was independently associated with low weight (adjusted aOR: 0.91; 95% CI 0.90, 0.92), less mortality (aOR: 0.54; 95% CI 0.36, 0.81), and lymph node TB (aOR: 1.57; 95% CI 1.13, 2.19) Conclusion. Lymph node TB was more common in women. Treatment outcomes were similar in both sexes, but women had a lower mortality rate

Impact of safety-related dose reductions or discontinuations on sustained virologic response in HCV-infected patients: Results from the GUARD-C Cohort

BACKGROUND: Despite the introduction of direct-acting antiviral agents for chronic hepatitis C virus (HCV) infection, peginterferon alfa/ribavirin remains relevant in many resource-constrained settings. The non-randomized GUARD-C cohort investigated baseline predictors of safety-related dose reductions or discontinuations (sr-RD) and their impact on sustained virologic response (SVR) in patients receiving peginterferon alfa/ribavirin in routine practice. METHODS: A total of 3181 HCV-mono-infected treatment-naive patients were assigned to 24 or 48 weeks of peginterferon alfa/ribavirin by their physician. Patients were categorized by time-to-first sr-RD (Week 4/12). Detailed analyses of the impact of sr-RD on SVR24 (HCV RNA <50 IU/mL) were conducted in 951 Caucasian, noncirrhotic genotype (G)1 patients assigned to peginterferon alfa-2a/ribavirin for 48 weeks. The probability of SVR24 was identified by a baseline scoring system (range: 0-9 points) on which scores of 5 to 9 and <5 represent high and low probability of SVR24, respectively. RESULTS: SVR24 rates were 46.1% (754/1634), 77.1% (279/362), 68.0% (514/756), and 51.3% (203/396), respectively, in G1, 2, 3, and 4 patients. Overall, 16.9% and 21.8% patients experienced 651 sr-RD for peginterferon alfa and ribavirin, respectively. Among Caucasian noncirrhotic G1 patients: female sex, lower body mass index, pre-existing cardiovascular/pulmonary disease, and low hematological indices were prognostic factors of sr-RD; SVR24 was lower in patients with 651 vs. no sr-RD by Week 4 (37.9% vs. 54.4%; P = 0.0046) and Week 12 (41.7% vs. 55.3%; P = 0.0016); sr-RD by Week 4/12 significantly reduced SVR24 in patients with scores <5 but not 655. CONCLUSIONS: In conclusion, sr-RD to peginterferon alfa-2a/ribavirin significantly impacts on SVR24 rates in treatment-naive G1 noncirrhotic Caucasian patients. Baseline characteristics can help select patients with a high probability of SVR24 and a low probability of sr-RD with peginterferon alfa-2a/ribavirin

A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings

Increasing the energy efficiency of the built environment has become a priority worldwide and especially in Europe. Because of the relatively low turnover rate of the existing built environment, energy efficiency retrofitting appears to be a fundamental step in reducing its energy consumption. Last experiences have shown that there is a vast energy efficiency potential lying in the building stock, and it is mainly untapped. One of the reasons is a lack of robust methodologies able to evaluate the effect of applied energy efficiency measures and inform about the expected impact of potential retrofitting strategies. Nowadays, dynamic measured data coming from automated metering infrastructure provides valuable information to evaluate the effect of energy conservation strategies. For this reason, energy performance modeling and assessment methods based on this data are starting to play a major role. In this paper, several methodologies for the measurement and verification of energy savings, and for the prediction and recommendation of energy retrofitting strategies, are analysed in detail. Practitioners looking at different options for these two processes, will find in this review a thorough and detailed overview of the different methods that can be used. Guidance is also provided to determine which method could work best depending on the specific case under analysis. The reviewed approaches include statistical learning models, machine learning models, Bayesian methods, deterministic approaches, and hybrid techniques that combine deterministic and data-driven modeling. Existing research gaps are identified and prospects for future investigation are presented within the main conclusions of this research work

Medio ambiente y arqueología de las tierras bajas del caribe colombiano

Las tierras bajas del Caribe colombiano han sido objeto de investigación arqueológica durante los últimos cuarenta años. Los resultados de estos trabajos han sido utilizados para plantear modelos sobre el desarrollo de las sociedades prehispánicas de Colombia. Su localización geográfica en la esquina noroccidental de suramérica, la diversidad y riqueza de ambientes ecológicos y la cantidad relativamente grande de sitios arqueológicos, las han convertido en foco de gran atención. Allí se ha hallado la cerámica más antigua de América hasta el momento conocida, el mayor sistema hidráulico prehispánico del continente, evidencias indirectas del cambio de patrón de subsistencia de cacería-recolección a uno agrícola y del cambio de cultivo de raíces por el de maíz