THE ROLE OF LIGHT IN THE FRUITING OF PANUS FRAGILIS

The role of light in the fruiting of Panus fragilis was explored under controlled temperature and light cycles. No fruiting occurred in the absence of light. A daily light cycle of 1.5 h at 792 ft-c was sufficient to produce fruiting initials, but not mature sporophores. Only at the longest daily light cycle tested, 12 h at 792 ft-c, were mature sporophores produced. The time required was 22–31 days with a daily fluctuating temperature cycle of 22 °C for 12 h followed by 8 °C for 12 h. The development of a pink pigment associated with fruiting initials and young sporophores was strongest at the longer light cycles and almost absent in the short cycles.

Download Full-text

The role of light and Gibberellic Acid on cardinal temperatures and thermal time required for germination of Charnushka (Nigella sativa) seed

Industrial Crops and Products ◽

10.1016/j.indcrop.2019.02.025 ◽

2019 ◽

Vol 132 ◽

pp. 140-149 ◽

Cited By ~ 4

Author(s):

Zeinab Savaedi ◽

Ghasem Parmoon ◽

Seyed Amir Moosavi ◽

Abdolmehdi Bakhshande

Keyword(s):

Gibberellic Acid ◽

Nigella Sativa ◽

Thermal Time ◽

Time Required ◽

Cardinal Temperatures ◽

Nigella Sativa Seed ◽

Role Of Light

Download Full-text

Locomotor activity in the Namaqua rock mouse (Micaelamys namaquensis): entrainment by light manipulations

Canadian Journal of Zoology ◽

10.1139/cjz-2014-0161 ◽

2014 ◽

Vol 92 (12) ◽

pp. 1083-1091 ◽

Cited By ~ 6

Author(s):

I. van der Merwe ◽

N.C. Bennett ◽

A. Haim ◽

M.K. Oosthuizen

Keyword(s):

Locomotor Activity ◽

Activity Rhythm ◽

Light Cycle ◽

Nocturnal Activity ◽

Dark Cycle ◽

Subjective Night ◽

Activity Onset ◽

Role Of Light ◽

Constant Dark

The locomotor activity rhythms of wild-caught Namaqua rock mice (Micaelamys namaquensis (A. Smith, 1834)) were examined under four light-cycle regimes to quantitatively describe the daily expression of locomotor activity and to study the innate relationship between activity and the light–dark cycle. Activity was always significantly higher at night than during the day; we note four trends. (1) The LD1 light cycle (12 h light : 12 h dark) established a distinct light-entrained and strongly nocturnal activity rhythm (99.11% nocturnal activity). The activity onset was prompt (zeitgeber time (ZT) 12.2 ± 0.04) and activity continued without any prominent peaks or extended times of rest until the offset of activity at ZT 23.73 ± 0.08. (2) Evidence for the internal maintenance of locomotor activity was obtained from the constant dark cycle (DD) in which locomotor activity free ran (mean τ = 23.89 h) and 77.58% of the activity was expressed during the subjective night. (3) During re-entrainment (LD2; 12 h light : 12 h dark), a nocturnal activity rhythm was re-established (98.65% nocturnal activity). (4) The inversion of the light cycle (DL; 12 h dark : 12 h light) evoked a shift in activity that again revealed dark-induced locomotor activity (95.69% nocturnal activity). Females were consistently more active than males in all of the light cycles, but only under the DD and LD2 cycles were females significantly more active than males. Although this species is considered nocturnal from field observations, information regarding its daily expression of activity and the role of light in its entrainment is lacking. To the best of our knowledge, this study is the first to report quantitatively on the species’ daily rhythm of activity and to investigate its relationship to the light–dark cycle.

Download Full-text

The Role of Light Anhydrous Silicic Acid on Physical Stability of Troglitazone Solid Dispersion

10.26226/morressier.57d6b2b5d462b8028d88d31e ◽

2016 ◽

Author(s):

Toshiyuki Nakahashi

Keyword(s):

Silicic Acid ◽

Solid Dispersion ◽

Physical Stability ◽

Role Of Light

Download Full-text

Towards 6G IoT: Tracing Mobile Sensor Nodes with Deep Learning Clustering in UAV Networks

Sensors ◽

10.3390/s21113936 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3936

Author(s):

Yannis Spyridis ◽

Thomas Lagkas ◽

Panagiotis Sarigiannidis ◽

Vasileios Argyriou ◽

Antonios Sarigiannidis ◽

...

Keyword(s):

Deep Learning ◽

Heuristic Method ◽

Sensor Nodes ◽

Convolutional Network ◽

Received Signal Strength Indicator ◽

Anchor Nodes ◽

Time Required ◽

Rf Signal ◽

Deep Learning Model

Unmanned aerial vehicles (UAVs) in the role of flying anchor nodes have been proposed to assist the localisation of terrestrial Internet of Things (IoT) sensors and provide relay services in the context of the upcoming 6G networks. This paper considered the objective of tracing a mobile IoT device of unknown location, using a group of UAVs that were equipped with received signal strength indicator (RSSI) sensors. The UAVs employed measurements of the target’s radio frequency (RF) signal power to approach the target as quickly as possible. A deep learning model performed clustering in the UAV network at regular intervals, based on a graph convolutional network (GCN) architecture, which utilised information about the RSSI and the UAV positions. The number of clusters was determined dynamically at each instant using a heuristic method, and the partitions were determined by optimising an RSSI loss function. The proposed algorithm retained the clusters that approached the RF source more effectively, removing the rest of the UAVs, which returned to the base. Simulation experiments demonstrated the improvement of this method compared to a previous deterministic approach, in terms of the time required to reach the target and the total distance covered by the UAVs.

Download Full-text