Densitometry marks delineating the affected area in keratoconus: clinical suitability of a new descriptive system based on its repeatability and reproducibility

Abstract We investigate the impact of the US drone program in Pakistan on insurgent violence. Using details about US-Pakistan counterterrorism cooperation and geocoded violence data, we show that the program was associated with monthly reductions of around nine to thirteen insurgent attacks and fifty-one to eighty-six casualties in the area affected by the program. This change was sizable, as in the year before the program, the affected area experienced around twenty-one attacks and one hundred casualties per month. Additional quantitative and qualitative evidence suggests that this drop is attributable to the drone program. However, the damage caused in strikes during the program cannot fully account for the reduction. Instead, anticipatory effects induced by the program played a prominent role in subduing violence. These effects stemmed from the insurgents’ perception of the risk of being targeted in drone strikes; their efforts to avoid targeting severely compromised their movement and communication abilities, in addition to eroding within-group trust. These findings contrast with prominent perspectives on air-power, counterinsurgency, and US counterterrorism, suggesting select drone deployments can be an effective tool of counterinsurgency and counterterrorism.

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Difference in the Cesium Body Contents of Affected Area Residents Depending on the Evacuation Timepoint Following the 2011 Fukushima Nuclear Disaster

Health Physics ◽

10.1097/hp.0000000000001249 ◽

2020 ◽

Vol 119 (6) ◽

pp. 733-745 ◽

Cited By ~ 1

Author(s):

Yu Igarashi ◽

Eunjoo Kim ◽

Shozo Hashimoto ◽

Kotaro Tani ◽

Kazuaki Yajima ◽

...

Keyword(s):

Affected Area ◽

Nuclear Disaster ◽

Fukushima Nuclear Disaster

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Does Head Orientation Influence 3D Facial Imaging? A Study on Accuracy and Precision of Stereophotogrammetric Acquisition

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084276 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4276

Author(s):

Giuditta Battistoni ◽

Diana Cassi ◽

Marisabel Magnifico ◽

Giuseppe Pedrazzi ◽

Marco Di Blasio ◽

...

Keyword(s):

Head Rotation ◽

Anthropometric Measurements ◽

Head Orientation ◽

3D Images ◽

Face Shape ◽

Operator Error ◽

Accuracy And Precision ◽

Error Magnitude ◽

Repeatability And Reproducibility ◽

Head Positions

This study investigates the reliability and precision of anthropometric measurements collected from 3D images and acquired under different conditions of head rotation. Various sources of error were examined, and the equivalence between craniofacial data generated from alternative head positions was assessed. 3D captures of a mannequin head were obtained with a stereophotogrammetric system (Face Shape 3D MaxiLine). Image acquisition was performed with no rotations and with various pitch, roll, and yaw angulations. On 3D images, 14 linear distances were measured. Various indices were used to quantify error magnitude, among them the acquisition error, the mean and the maximum intra- and inter-operator measurement error, repeatability and reproducibility error, the standard deviation, and the standard error of errors. Two one-sided tests (TOST) were performed to assess the equivalence between measurements recorded in different head angulations. The maximum intra-operator error was very low (0.336 mm), closely followed by the acquisition error (0.496 mm). The maximum inter-operator error was 0.532 mm, and the highest degree of error was found in reproducibility (0.890 mm). Anthropometric measurements from alternative acquisition conditions resulted in significantly equivalent TOST, with the exception of Zygion (l)–Tragion (l) and Cheek (l)–Tragion (l) distances measured with pitch angulation compared to no rotation position. Face Shape 3D Maxiline has sufficient accuracy for orthodontic and surgical use. Precision was not altered by head orientation, making the acquisition simpler and not constrained to a critical precision as in 2D photographs.

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Biodiversity of butterflies in endosulfan-affected areas of Kerala, India

The Journal of Basic and Applied Zoology ◽

10.1186/s41936-020-00192-w ◽

2020 ◽

Vol 81 (1) ◽

Author(s):

K. N. Raghavendra ◽

Kumar Arvind ◽

G. K. Anushree ◽

Tony Grace

Keyword(s):

Monsoon Season ◽

Winter Season ◽

Wiener Index ◽

Long Term Effects ◽

Affected Area ◽

Butterfly Assemblages ◽

Abundance And Diversity ◽

The One ◽

One Way Anova

Abstract Background Butterflies are considered as bio-indicators of a healthy and diversified ecosystem. Endosulfan was sprayed indiscriminately in large plantations of Kasaragod district, Kerala which had caused serious threats to the ecosystem. In this study, we surveyed the butterflies for their abundance and diversity in three differentially endosulfan-affected areas viz., Enmakaje—highly affected area, Periye—moderately affected area, Padanakkad—unaffected area, carried out between the end of the monsoon season and the start of the winter season, lasting approximately 100 days. Seven variables viz., butterfly abundance (N), species richness (S), Simpson’s reciprocal index (D), the Shannon–Wiener index (H′), the exponential of the Shannon–Wiener index (expH′), Pielou’s evenness (J) and species evenness (D/S), related to species diversity were estimated, followed by the one-way ANOVA (F = 25.01, p < 0.001) and the Kruskal-Wallis test (H = 22.59, p < 0.001). Results A population of three different butterfly assemblages comprised of 2300 butterflies which represented 61 species were encountered. Our results showed that Enmakaje displayed significantly lower butterfly diversity and abundance, compared to the other two communities. Conclusion So far, this is the first study concerning the effect of endosulfan on the biodiversity of butterfly in the affected areas of Kasaragod, Kerala, India. This study may present an indirect assessment of the persisting effects of endosulfan in the affected areas, suggesting its long-term effects on the ecosystem.

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LeLePhid: An Image Dataset for Aphid Detection and Infestation Severity on Lemon Leaves

Data ◽

10.3390/data6050051 ◽

2021 ◽

Vol 6 (5) ◽

pp. 51

Author(s):

Jorge Parraga-Alava ◽

Roberth Alcivar-Cevallos ◽

Jéssica Morales Carrillo ◽

Magdalena Castro ◽

Shabely Avellán ◽

...

Keyword(s):

Image Segmentation ◽

Plant Disease ◽

Automatic Identification ◽

Health State ◽

Classification Problems ◽

Affected Area ◽

White Spots ◽

The World ◽

Image Dataset ◽

Plant Sap

Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed to understand citrus pest dynamics and management. This article presents a dataset that contains 665 healthy and unhealthy lemon leaf images. The latter are leaves with the presence of aphids, and visible white spots characterize them. Moreover, each image includes a set of annotations that identify the leaf, its health state, and the infestation severity according to the percentage of the affected area on it. Images were collected manually in real-world conditions in a lemon plant field in Junín, Manabí, Ecuador, during the winter, by using a smartphone camera. The dataset is called LeLePhid: lemon (Le) leaf (Le) image dataset for aphid (Phid) detection and infestation severity. The data can facilitate evaluating models for image segmentation, detection, and classification problems related to plant disease recognition.

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