Deep Learning for Predicting Congestive Heart Failure

Congestive heart failure (CHF) is one of the most debilitating cardiac disorders. It is a costly disease in terms of both lives and financial outlays, given the high rate of hospital re-admissions and mortality. Heart failure (HF) is notoriously difficult to identify on time, and is frequently accompanied by additional comorbidities that further complicate diagnosis. Many decision support systems (DSS) have been developed to facilitate diagnosis and to raise the standard of screening and monitoring operations, even for non-expert staff. This is confirmed in the literature by records of highly performing diagnosis-aid systems, which are unfortunately not very relevant to expert cardiologists. In order to assist cardiologists in predicting the trajectory of HF, we propose a deep learning-based system which predicts severity of disease progression by employing medical patient history. We tested the accuracy of four models on a labeled dataset, composed of 1037 records, to predict CHF severity and progression, achieving results comparable to studies based on much larger datasets, none of which used longitudinal multi-class prediction. The main contribution of this work is that it demonstrates that a fairly complicated approach can achieve good results on a medium size dataset, providing a reasonably accurate means of determining the evolution of CHF well in advance. This potentially constitutes a significant aid for healthcare managers and expert cardiologists in designing different therapies for medication, healthy lifestyle changes and quality of life (QoL) management, while also promoting allocation of resources with an evidence-based approach. © 2022 by the authors

Analisis Capital Budgeting Untuk Menilai Kelayakan Investasi Aktiva Tetap (Studi Pada CV. Alfa 99 Malang)

Business organizations have profit-seeking. How to make a profit, among others by maximizing sales, production, and streamline production time. But sometimes the capacity of existing assets are not able to meet the market demand so must invest fixed assets. CV. Alfa 99 are companies that need investment assets in the form of the machine because the machine owned still manual. The investment plan will be done CV. Alfa 99 feasible. Rated ARR of 74% over the cost of capital is 21.51%. Based on the calculation of the PP is feasible because it happened in the 2nd, 6th month and the 25th day is less than 8 years. The value of the B/C ratio is more than 1 is 2.44. The result of the calculation of NPV is Rp. 349 176 495. IRR above the expected cost of capital company that is 49.12%. The method is suitable as a reference by the CV. Alfa 99 ie NPV and payback period

Biological Control Efforts of Water hyacinth (Eichhornia crassipes (Mart.) Solm) on Kainji Lake, Nigeria

Biological control of water hyacinth (Eichhornia crassipes (Mart.) Solm) was monitored on Kainji Lake between 1995 and 1999. The two most important host specific natural enemies of water hyacinth (Neochetina eichhorniae and N. bruchi) were used and impacts of the weevils on water hyacinth were monitored on tri-monthly basis. The manual control initiated by the National Institute for Freshwater Fisheries Research (NIFFR) encouraged the fishermen to physically remove water hyacinth from their shores and open water. The lake hydrology, most especially during the drawdown period when the water volume is reduced tremendously, allows water hyacinth plants to be stranded by the bank of the lake thereby leading to massive destruction of the weed population and consequently the weevils population stability. The floristic composition of macrophyte intimately mixed with the water hyacinth was also monitored during the low and high water regimes. Among the prominent plant species found with water hyacinth included Echinochloa stagnina, Mimosa pigra, Polygonium senegalensis Polygonium lanigarium. Sesbania dalzelli, and Vosia cuspidata were found competing with the much favoured Echinochloa spp which serves as forage to livestock around the lake; However, no incidence of weevil attack was observed on any of the vegetation mixed with water hyacinth. Keywords: Biocontol, Kainji Lake, Water hyacinth, Weevils

Applicazioni di livello “0” della metodologia utilizzata per la valutazione del rischio sismico di Sistemi Urbani, utilizzando l’analogia delle reti neuronali

Questa ricerca, condotta nell’ambito del Progetto RELUIS – Linea 10, ha riguardato la messa a punto di un modello di rischio sismico per Sistemi Urbani con approccio multilivello, utilizzando l’analogia con le reti neuronali. Il primo passo è stata l’elaborazione del livello 0, basato su banche-dati, disponibili a livello nazionale, relative alla pericolosità sismica di base e locale (INGV) e a dati di censimento dei comuni italiani (ANCITEL 2001; ISTAT 2001) per la descrizione fisica e funzionale dei centri abitati/sistemi urbani analizzati. Per semplicità e per omogeneità tra i molti dati elaborati sono stati trascurati due aspetti rilevanti per il modello di rete neuronale, che intervengono invece ai livelli successivi, ovvero l’aspetto della “soglia” di perdita di capacità di una componente di sottosistema (sia per evoluzione che per connessione) e l’aspetto della “capacità iniziale” di una componente di sottosistema prima dell’evento sismico. La valutazione della perdita di capacità complessiva di un Sistema Urbano a livello 0 è stata quindi calcolata come l’insieme delle perdite di tutti i sistemi combinati tra loro (con opportuni pesi) e quindi con un valore complessivo

Butterflies as bioindicators of metal contamination

Anthropogenic trace metal contamination has significantly increased and has caused many hazardous consequences for the ecosystems and human health. The Terni basin valley (Central Italy) shows a heavy load of pollutants from industrial activities, while the characteristic orography structure of the valley favours air stagnation, thus limiting air pollution dispersal. The present study conducted in 2014 aimed to determine the concentration of ten metals in five species of butterflies at nine sites in the Terni valley along a 21-km-long transect, including both relatively pristine and industrial areas. At sites where soil contamination was high for a given metal, such as for chromium as in the case of site 4 (the closest to the steel plant) and for lead as in the case of site 2 (contaminated by a firing range), higher levels of contamination were observed in the tissues of butterflies. We found a correlation between soil contamination and the concentration of Cr, Al and Sr in the tissues of some species of butterflies. The sensitivity to contamination differed among the five species; in particular, Coenonympha pamphilus was generally the species that revealed the highest concentrations of all the ten trace metals at the sites closer to the industrial area. It is known that C. pamphilus is a sedentary species and that its host plants are the Poaceae, capable of accumulating high quantities of metals in their rhizosphere region, thus providing the link with soil contamination. Therefore, monitoring the metal concentration levels in butterflies might be a good indicator and a control tool of environmental quality, specifically in areas affected by high anthropogenic pollution loads linked to a specific source

TOTAL PHENOLIC CONTENT, ANTIOXIDANT AND ANTICANCER ACTIVITIES OF FOUR SPECIES OF SENNA Mill. FROM NORTHEAST BRAZIL

Objective: The present investigation evaluated the antioxidant and anticancer properties and total phenolic contents of four species of Senna: S. gardneri, S. macranthera, S. splendida and S. trachypus from northeast Brazil. Methods: Ethanolic extracts of leaves and roots of the four Senna species were screened for phytochemical procedures. An in-vitro antioxidant study was conducted by means of DPPH and ABTS radical scavenging assays. Anticancer activity was evaluated using the MTT 3-(4,5-dimethylthiazole-2-yl)-2,5- diphenyltetrazolium bromide) method against the HCT-116, SF-295 and OVCAR-8 cancer cell lines. Total phenolic contents were determined using a Folin-Ciocalteau colorimetric assay. Results: Anthraquinones, flavonoids, phenolics, steroids, tannins, triterpenoids, xanthones, and glycosides were detected in all Senna extracts. The results for the antioxidant activity showed that the highest percentage of scavenger radicals was present in the extract from roots of Senna trachypus (StR), which showed higher levels than the two standards used. The highest percentage of inhibition of the cancer cell lines tested was obtained with the leaf extracts of S. gardneri (SgL) and S. splendida (SsL). Conclusion: The ethanolic extracts of the four species of Senna showed antioxidant activity in both assays, and this activity can be attributed to the presence of phenolic compounds such as flavonoids and anthraquinones. S. trachypus showed a higher antioxidant potential than the standards, as well as a higher total phenolic content. Only two of the plants showed promising results for anticancer activity

Solar neutrino detection in a large volume double-phase liquid argon experiment

Precision measurements of solar neutrinos emitted by specific nuclear reaction chains in the Sun are of great interest for developing an improved understanding of star formation and evolution. Given the expected neutrino fluxes and known detection reactions, such measurements require detectors capable of collecting neutrino-electron scattering data in exposures on the order of 1 ktonne yr, with good energy resolution and extremely low background. Two-phase liquid argon time projection chambers (LAr TPCs) are under development for direct Dark Matter WIMP searches, which possess very large sensitive mass, high scintillation light yield, good energy resolution, and good spatial resolution in all three cartesian directions. While enabling Dark Matter searches with sensitivity extending to the "neutrino floor" (given by the rate of nuclear recoil events from solar neutrino coherent scattering), such detectors could also enable precision measurements of solar neutrino fluxes using the neutrino-electron elastic scattering events. Modeling results are presented for the cosmogenic and radiogenic backgrounds affecting solar neutrino detection in a 300 tonne (100 tonne fiducial) LAr TPC operating at LNGS depth (3,800 meters of water equivalent). The results show that such a detector could measure the CNO neutrino rate with ~15% precision, and significantly improve the precision of the 7Be and pep neutrino rates compared to the currently available results from the Borexino organic liquid scintillator detector.Comment: 21 pages, 7 figures, 6 table