Photosynthesis

Multi tool use

Folium ubi praecipue photosynthesis in plantis accidit
Photosynthesis in plantis, algis, bacteriis est conversio biochemica lucis et dioxidi carbonis et aquae in energiam chemicam, qua animantes utuntur. Chlorophyllum, quod colorem viridem plantis dat, lucem absorbit ut planta energiam habeat.
Reliquia photosynthesis sunt glucosium et oxygenium. Similis est respirationi animalium; quoniam autem animalia oxygenium inhalant et dioxidum carbonis emittunt, plantae contrarium faciunt. Duos ergo processus quasi cyclum habent. Praeterea, glucosium quod faciunt plantae alimentum animalibus fit.
Formula photosynthesis |
- 6 CO2(gas) + 12 H2O(fluidus) + photona → C6H12O6(aquaeus) + 6 O2(gas) + 6 H2O(fluidus)
- dioxidium carbonis + aqua + energia lucis→ glucosium + oxygenium + aqua
Bibliographia |
- Asimov, Isaac 1968. Photosynthesis. Novi Eboraci, Londini: Basic Books, Inc. ISBN 0-465-05703-9.
- Blankenship, R.E. 2008. Molecular Mechanisms of Photosynthesis, editio altera. Novi Eboraci: John Wiley & Sons Inc. ISBN 0-470-71451-4.
- Farineau, Jack, et Jean-François Morot-Gaudry. 2006. La photosynthèse: Processus physiques, moléculaires et physiologiques. Lutetiae: Editions Quae. ISBN 2-7380-1209-4.
- Häder, Donat-Peter, ed. 1999. Photosynthese. Stuttgardiae: Georg Thieme Verlag. ISBN 3-13-115021-1.
- Rabinowitch, E., et Govindjee. 1969. Photosynthesis. Londini: J. Wiley. ISBN 0-471-70424-5.
1eKPWAAyvjlfxU98WO09iYjhc4 TGUpxo,XgZqVFu5OarKzb,VCLS,FbBir fP8asPitnwIo k,eL1jPp9UBwfoizwXxRw
Popular posts from this blog
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
1
$begingroup$
This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
1
$begingroup$
I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...