Spectral examination of Byzantine Chant archetype

In this article, a particular hypostasis of Byzantine chant was chosen to be spectrally examined, from the multitude of possible variants: a melodic structure accompanied by a simple bass drone called Ison, placed bellow the melody and sung by male choir. This model is referred to in this paper as Byzantine chant archetype and is further approached from the spectral listening perspective. Psychoacoustic analysis criteria were used, such as: holistic/analytic listening, sound fusion/fissioning, sensory consonance/dissonance, harmonic entropy, etc. The research is an attempt to demonstrate that Byzantine chant with Ison presents an ideal situation for sound fusion perception and holistic listening. The persistence of the fundamental pitch (Ison) over the melodic structure acts in favor of partials fusion of the two layers into one perceptual entity. Starting with Western medieval organum, polyphonic practice broke with the monolithic perceptual entity provided by the Ison by simply moving the bass line and later filling it in with chords resulting from the multipart structure. The perception mode shifted from sound fusion to sound fissioning. The way we hear the polyphonic texture is of an analytic nature (analytic listening mode). It appears that Western music culture developed a more analytic model of hearing while the Eastern one relied more on a holistic listening type

ENHANCING THE EFFICIENCY OF INDOOR LOCAL VENTILATION USING CROSS-FLOW FANS: CASE STUDY FOR A SMOKING CABIN

The paper presents an original solution for increasing air quality and reducing energy consumption of the local indoor ventilation by using cross-flow fans. The solution is a combination between the local exhaust ventilation (LEV) technique from industry, negative-pressure isolation rooms used in hospitals, and air curtains (AC) used for isolating of indoor/outdoor spaces. The solution provides a high air flow rate at low velocity due to the high value of the flow coefficient of the cross flow fans and, in the same time, allows modular setup according to local space geometry. A case study is proposed regarding the isolation of a smoking area where smell and airborne particles appear. A 3D numerical simulation was performed, in which one cross-flow fan with long axial length was considered. The optimum air flow rate and flow pattern was obtained in order to isolate the local space. The results show that a new approach for reducing sick building syndrome could be addressed by providing modular and local ventilation using cross-flow fans

ENHANCING THE EFFICIENCY OF INDOOR LOCAL VENTILATION USING CROSS-FLOW FANS: CASE STUDY FOR A SMOKING CABIN

The paper presents an original solution for increasing air quality and reducing energy consumption of the local indoor ventilation by using cross-flow fans. The solution is a combination between the local exhaust ventilation (LEV) technique from industry, negative-pressure isolation rooms used in hospitals, and air curtains (AC) used for isolating of indoor/outdoor spaces. The solution provides a high air flow rate at low velocity due to the high value of the flow coefficient of the cross flow fans and, in the same time, allows modular setup according to local space geometry. A case study is proposed regarding the isolation of a smoking area where smell and airborne particles appear. A 3D numerical simulation was performed, in which one cross-flow fan with long axial length was considered. The optimum air flow rate and flow pattern was obtained in order to isolate the local space. The results show that a new approach for reducing sick building syndrome could be addressed by providing modular and local ventilation using cross-flow fans

Pedestrian-level ventilation in an urban environment adjacent to a river channel: A case study for Bucharest city – Romania

Increasing evapotranspiration in cities, derived from vegetation and water bodies, can effectively mitigate the effect of urban heat island (UHI). This paper presents a study on an urban ventilation solution for Bucharest City in Romania. The solution is based on lifting air volumes from the free surface of Dambovita River, which crosses the city center where UHI has a significant impact, to the roadway and pedestrian level by using cross-flow fans mounted on floating panels planted with vegetation, which are placed at the river banks. The electric motors of the cross-flow fans are powered by PV solar cells. The real optimal value of evapotranspiration (ETRO) was computed for the case of lucerne in order to assess the air temperature at the surface of the floating panel and a numerical study was performed in order to obtain the velocities of the air flow and the temperature field in a domain containing the free surface of the river, the floating panel surface, and the roadway surface (at pedestrian level). It was observed that, at low flow rates, the cooler air reaches the roadway surface in a compact jet due to the Coanda effect - the coherent air jet is of about 30–40 cm above the ground level. For a day with clear sky and no wind conditions a decrease in the air temperature of 4–5 °C can be obtained at the pedestrian level, within a layer of 1 m height. The study opens the possibility to approach such issues at a greater scale in order to assess the viability of appropriate solutions for cooling down the urban heat island as well

The stability of the radiative regime in Bucharest during 2017-2018

The paper presents an analysis of the solar irradiation and the stability of the solar radiative regime, available for Bucharest and the southern area of Romania. The study is based on meteorological data measured at 3.6 seconds, on several consecutive days of each season, in the years 2017 and 2018. Data acquisition was performed at Technical University of Civil Engineering Bucharest. The daily mean values for sunshine number and sunshine stability number are computed and analysed. The analyses carried out in this research are useful for applications of solar energy and conversion to thermal energy in hot air solar collectors to estimate the temperature variation at the collector air outlet as well as for photovoltaic panels to estimate the resulting electrical energy

Evaluation of six methylation markers derived from genome-wide screens for detection of cervical precancer and cancer

Aim: To evaluate the triage performance of six host-cell DNA methylation markers derived from two genome-wide discovery screens for detection of cervical precancer (cervical intraepithelial neoplasia 3 [CIN]) and cancer. Materials & methods: Human papillomavirus-positive cervical scrapes of controls (≤CIN1; n = 352) and women diagnosed with CIN3 (n = 175) or cervical cancer (n = 50) were analyzed for methylation of ASCL1, LHX8, ST6GALNAC5, GHSR, SST and ZIC1. Results: Methylation levels increased significantly with disease severity (all markers p 0.800 after leave-one-out cross-validation. Bi-marker panel ASCL1/LHX8 had highest area under the curve (0.882), and detected 83.4% of CIN3 and all cervical cancers at specificity of 82.4%. Conclusion: All six methylation markers showed an equivalent, high performance for the triage of human papillomavirus-positive women using cervical scrapes with complementarity between markers

Sparse classification with paired covariates

Funder: Department of Epidemiology and Biostatistics, Amsterdam UMC, VU University AmsterdamAbstractThis paper introduces the paired lasso: a generalisation of the lasso for paired covariate settings. Our aim is to predict a single response from two high-dimensional covariate sets. We assume a one-to-one correspondence between the covariate sets, with each covariate in one set forming a pair with a covariate in the other set. Paired covariates arise, for example, when two transformations of the same data are available. It is often unknown which of the two covariate sets leads to better predictions, or whether the two covariate sets complement each other. The paired lasso addresses this problem by weighting the covariates to improve the selection from the covariate sets and the covariate pairs. It thereby combines information from both covariate sets and accounts for the paired structure. We tested the paired lasso on more than 2000 classification problems with experimental genomics data, and found that for estimating sparse but predictive models, the paired lasso outperforms the standard and the adaptive lasso. The R package is available from cran.</jats:p

Solar Air Collectors for Space Heating and Ventilation Applications—Performance and Case Studies under Romanian Climatic Conditions

Solar air collectors have various applications: on the one hand, they can be used for air heating in cold seasons; on the other hand they can be used in summer to evacuate the warm and polluted air from residential, offices, industrial, and commercial buildings. The paper presents experimental results of a solar collector air, under the climatic conditions of the Southeastern Europe. The relationships between the direct solar irradiation, the resulting heat flow, the air velocity at the outlet, the air flow rate, the nominal regime of the collector and the efficiency of conversion of solar energy into thermal energy are all highlighted. Thus, it was shown that after a maximum 50 min, solar air collectors, with baffles and double air passage can reach over 50% efficiency for solar irradiation of 900–1000 W/m2. The article also presents a mathematical model and the results of a computational program that allows sizing solar collectors for the transfer of air, with the purpose of improving the natural ventilation of buildings. The article is completed with case studies, sizing the area to be covered with solar collectors, to ensure ventilation of a house with two floors or for an office building. In addition, the ACH (air change per hour) coefficient was calculated and compared

Sparse classification with paired covariates

Funder: Department of Epidemiology and Biostatistics, Amsterdam UMC, VU University AmsterdamAbstract: This paper introduces the paired lasso: a generalisation of the lasso for paired covariate settings. Our aim is to predict a single response from two high-dimensional covariate sets. We assume a one-to-one correspondence between the covariate sets, with each covariate in one set forming a pair with a covariate in the other set. Paired covariates arise, for example, when two transformations of the same data are available. It is often unknown which of the two covariate sets leads to better predictions, or whether the two covariate sets complement each other. The paired lasso addresses this problem by weighting the covariates to improve the selection from the covariate sets and the covariate pairs. It thereby combines information from both covariate sets and accounts for the paired structure. We tested the paired lasso on more than 2000 classification problems with experimental genomics data, and found that for estimating sparse but predictive models, the paired lasso outperforms the standard and the adaptive lasso. The R package palasso is available from cran