Visible Patches Research Articles

DDAE: Towards Deep Dynamic Vision BERT Pretraining

Recently, masked image modeling (MIM) has demonstrated promising prospects in self-supervised representation learning. However, existing MIM frameworks recover all masked patches equivalently, ignoring that the reconstruction difficulty of different patches can vary sharply due to their diverse distance from visible patches. In this paper, we propose a novel deep dynamic supervision to enable MIM methods to dynamically reconstruct patches with different degrees of difficulty at different pretraining phases and depths of the model. Our deep dynamic supervision helps to provide more locality inductive bias for ViTs especially in deep layers, which inherently makes up for the absence of local prior for self-attention mechanism. Built upon the deep dynamic supervision, we propose Deep Dynamic AutoEncoder (DDAE), a simple yet effective MIM framework that utilizes dynamic mechanisms for pixel regression and feature self-distillation simultaneously. Extensive experiments across a variety of vision tasks including ImageNet classification, semantic segmentation on ADE20K and object detection on COCO demonstrate the effectiveness of our approach.

MAR: Masked Autoencoders for Efficient Action Recognition

Standard approaches for video action recognition usually operate on full input videos, which is inefficient due to the widespread spatio-temporal redundancy in videos. The recent progress in masked video modelling, specifically VideoMAE, has shown the ability of vanilla Vision Transformers (ViT) to complement spatio-temporal contexts using limited visual content. Inspired by this, we propose Masked Action Recognition (MAR), which reduces redundant computation by discarding a proportion of patches and operating only on a portion of the videos. MAR includes two essential components: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cell running masking</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">bridging classifier</i> . Specifically, to enable the ViT to perceive the details beyond the visible patches, cell running masking is used to preserve the spatio-temporal correlations in videos. This ensures that the patches at the same spatial location can be observed in turn for easy reconstructions. Additionally, we notice that, although the partially observed features can reconstruct semantically explicit invisible patches, they fail to achieve accurate classification. To address this issue, we propose a bridging classifier that can help fill the semantic gap between the ViT encoded features used for reconstruction and the specialized features used for classification. Our proposed MAR can reduce the computational cost of ViT by 53%. Extensive experiments have demonstrated that MAR consistently outperforms existing ViT models by a notable margin. Notably, we found that a ViT-Large model fine-tuned by MAR achieves comparable performance to a ViT-Huge model fine-tuned by standard training methods on both Kinetics-400 and Something-Something v2 datasets. Moreover, the computation overhead of our ViT-Large model is only 14.5% of that of the ViT-Huge model. Codes have been made available <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/alibaba-mmai-research/Masked-Action-Recognition</uri> .

MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features.

Medical time series data are indispensable in healthcare, providing critical insights for disease diagnosis, treatment planning, and patient management. The exponential growth in data complexity, driven by advanced sensor technologies, has presented challenges related to data labeling. Self-supervised learning (SSL) has emerged as a transformative approach to address these challenges, eliminating the need for extensive human annotation. In this study, we introduce a novel framework for Medical Time Series Representation Learning, known as MTS-LOF. MTS-LOF leverages the strengths of Joint-Embedding SSL and Masked Autoencoder (MAE) methods, offering a unique approach to representation learning for medical time series data. By combining these techniques, MTS-LOF enhances the potential of healthcare applications by providing more sophisticated, context-rich representations. Additionally, MTS-LOF employs a multi-masking strategy to facilitate occlusion-invariant feature learning. This approach allows the model to create multiple views of the data by masking portions of it. By minimizing the discrepancy between the representations of these masked patches and the fully visible patches, MTS-LOF learns to capture rich contextual information within medical time series datasets. The results of experiments conducted on diverse medical time series datasets demonstrate the superiority of MTS-LOF over other methods. These findings hold promise for significantly enhancing healthcare applications by improving representation learning. Furthermore, our work delves into the integration of Joint-Embedding SSL and MAE techniques, shedding light on the intricate interplay between temporal and structural dependencies in healthcare data. This understanding is crucial, as it allows us to grasp the complexities of healthcare data analysis.

One-for-All: Proposal Masked Cross-Class Anomaly Detection

One of the most challenges for anomaly detection (AD) is how to learn one unified and generalizable model to adapt to multi-class especially cross-class settings: the model is trained with normal samples from seen classes with the objective to detect anomalies from both seen and unseen classes. In this work, we propose a novel Proposal Masked Anomaly Detection (PMAD) approach for such challenging multi- and cross-class anomaly detection. The proposed PMAD can be adapted to seen and unseen classes by two key designs: MAE-based patch-level reconstruction and prototype-guided proposal masking. First, motivated by MAE (Masked AutoEncoder), we develop a patch-level reconstruction model rather than the image-level reconstruction adopted in most AD methods for this reason: the masked patches in unseen classes can be reconstructed well by using the visible patches and the adaptive reconstruction capability of MAE. Moreover, we improve MAE by ViT encoder-decoder architecture, combinational masking, and visual tokens as reconstruction objectives to make it more suitable for anomaly detection. Second, we develop a two-stage anomaly detection manner during inference. In the proposal masking stage, the prototype-guided proposal masking module is utilized to generate proposals for suspicious anomalies as much as possible, then masked patches can be generated from the proposal regions. By masking most likely anomalous patches, the “shortcut reconstruction” issue (i.e., anomalous regions can be well reconstructed) can be mostly avoided. In the reconstruction stage, these masked patches are then reconstructed by the trained patch-level reconstruction model to determine if they are anomalies. Extensive experiments show that the proposed PMAD can outperform current state-of-the-art models significantly under the multi- and especially cross-class settings. Code will be publicly available at https://github.com/xcyao00/PMAD.

Usage of Dermoscopy as an Effective Diagnostic Tool in Pityriasis Alba: A Prospective Observational Study Among Children in a Suburban Hospital in South India.

Hypopigmented patches in patients with skin of color are usually a cause of concern. Pityriasis alba is a common skin condition that causes visible patches of hypopigmentation in children and adolescents. In addition to the cosmetic impairment, parents are concerned about the diagnosis of vitiligo and leprosy which also cause hypopigmented patches and have negative social implications. Dermoscopy is a useful diagnostic aid that is acquiring prominence in diagnosing a variety of skin diseases. Few studies exist that validate the use of dermoscopy as an effective tool in the diagnosis of Pityriasis alba. To evaluate the effectiveness of dermoscopy by correlating the clinical features of Pityriasis alba with dermoscopic images. Hypopigmented patches in 16 patients that were clinically diagnosed as Pityriasis alba were examined with a DermLiteDL200 Hybrid dermoscope (Dermlite, CA, USA). All the dermoscopic images were photographically recorded and the findings were noted and correlated with the clinical stages of the disease. Out of the 40 patches examined in 16 patients,dermoscopic images of white structureless spots, scaling, indistinct borders and normally pigmented hairs were consistently present in all the patches to propose theseas the four dermoscopic criteria for the diagnosis of Pityriasis alba. Areas of light brown pigmentation, 17 (42.5%), erythema, 3 (7.5%), and faint pigmented network,11 (27.5%) were the other features noted in some of the patches. In an ethnic South Indian population where the skin color is predominantly brown, hypopigmented patches are visibly obvious and concerning. Pityriasis alba, Pityriasis versicolor, Vitiligo, Nevus depigmentosus, and Leprosy are the five common conditions seen among children of which Pityriasis alba is the most prevalent. Offering the right diagnosis is essential for the correct management as well as excluding more serious conditions such as leprosy and vitiligo. In this study, Dermoscopy provided a valuable diagnostic aid in achieving this objective.

An Information Entropy Masked Vision Transformer (IEM-ViT) Model for Recognition of Tea Diseases

Tea is one of the most popular drinks in the world. The rapid and accurate recognition of tea diseases is of great significance for taking targeted preventive measures. In this paper, an information entropy masked vision transformation (IEM-ViT) model was proposed for the rapid and accurate recognition of tea diseases. The information entropy weighting (IEW) method was used to calculate the IE of each segment of the image, so that the model could learn the maximum amount of knowledge and information more quickly and accurately. An asymmetric encoder–decoder architecture was used in the masked autoencoder (MAE), where the encoder operated on only a subset of visible patches and the decoder recovered the labeled masked patches, reconstructing the missing pixels for parameter sharing and data augmentation. The experimental results showed that the proposed IEM-ViT had an accuracy of 93.78% for recognizing the seven types of tea diseases. In comparison to the currently common image recognition algorithms including the ResNet18, VGG16, and VGG19, the recognition accuracy was improved by nearly 20%. Additionally, in comparison to the other six published tea disease recognition methods, the proposed IEM-ViT model could recognize more types of tea diseases and the accuracy was improved simultaneously.

Visible Patches for Haptic Rendering of Point Clouds.

Unsorted three dimensional (3D) points are commonly acquired from modern tools and they become popular in many virtual reality applications. In order to produce the haptic feedback to enrich the interaction with the captured models, the point clouds are usually converted to structured meshes or implicit representations. The conversion is either time-consuming or not precise, making the haptic rendering with a low fidelity especially for small haptic proxies. We propose to locally reconstruct the points to balance the performance and quality for the haptic rendering of point clouds. We introduce visible patches on the point clouds by noticing that only the points which are visible to the haptic proxy form the candidate contact region. A computational model for the visible patches is introduced and a virtual coupling model is built to update the visible patches online for haptic rendering. The cases with noises and nonuniform samples are also discussed. We demonstrate our method on a set of synthesized and captured 3D point clouds. Various experimental results are collected and show the efficiency of our method.

Sponge microbiome stability during environmental acquisition of highly specific photosymbionts.

In this study, we used in situ transplantations to provide the first evidence of horizontal acquisition of cyanobacterial symbionts by a marine sponge. The acquisition of the symbionts by the host sponge Petrosia ficiformis, which was observed in distinct visible patches, appeared several months after transplantation and at different times on different sponge specimens. We further used 16S rRNA gene amplicon sequencing of genomic DNA (gDNA) and complementary DNA (cDNA) and metatranscriptomics to investigate how the acquisition of the symbiotic cyanobacterium Candidatus Synechococcus feldmannii perturbed the diverse microbiota associated with the host P. ficiformis. To our surprise, the microbiota remained relatively stable during cyanobacterial symbiont acquisition at both structural (gDNA content) and activity (cDNA expression) levels. At the transcriptomic level, photosynthesis was the primary function gained following the acquisition of cyanobacteria. Genes involved in carotene production and oxidative stress tolerance were among those highly expressed by Ca. S. feldmannii, suggesting that this symbiont may protect itself and its host from damaging light radiation.

Overalls - Complex Document(s): a Never-ending Artistic Research Process

I want to show that a pair of overalls can be a document in many senses, and thus demonstrate that the complementary relationship between materiality, sociality and conceptuality is a very complex relationship. I will use an artistic approach to show the complex relationship and make an exposition of verbal text and images, consisting of 4 parts: 1. Origin of overalls A short history of overalls - denim pants first with suspenders and later with bibs. They go back to the 18th century, were mass-produced by Levi Strauss and Lee and became popular work garment and later for leisure and fashion for both men and women. 2. "Broken in" overalls A document of use and often hard work, shown in faded denim. They can be used for generations, with overalls handed over from father to sons or daughters 3. Mending overalls A document of repairing overalls by mending and patching, documenting traditions for mending clothes 4. Overalls as wearable art A document of art shown by the visible mending and patches making overalls into pieces of art work 5. Document theory Overalls - a showcase of the complexity of the complementary relationship between materiality, sociality and conceptuality

Simulated elephant-induced habitat changes can create dynamic landscapes of fear

Landscapes of fear have become widely studied in the northern hemisphere, but are still largely understudied in the more complex, diverse carnivore-prey communities of Africa. Habitat changes brought about by a megaherbivore, the African elephant (Loxodonta africana), can modify the perceived landscape of fear by predation vulnerable prey species (impala Aepyceros melampus and warthog Phacochoerus africanus) in contrast with non-prey species (white rhinoceros Ceratotherium simum). We hypothesized that by opening up woody vegetation, elephants may modify perceived risk at a landscape-scale, but also at a fine scale by depositing escape impediments in the form of coarse woody debris. We experimentally tested this in Hluhluwe-iMfolozi Park, South Africa, by simulating elephant-induced habitat changes on patch scale (opening up woody vegetation) and within-patch scale (deposition of coarse woody debris) and monitoring the herbivore visitation using camera traps. We compared visitation on the edge of grazing lawns (in proximity of dense vegetation) and the centre (open, highly visible patches), either with or without coarse woody debris and with or without fresh predator scat. We found that mesoherbivore prey species showed contrasting responses, with warthog avoiding plots close to dense vegetation and plots with coarse woody debris. Impala reduced their visitation to dense vegetation patches only during risky times, at night, especially in the presence of predator scat, but did not clearly avoid plots with coarse woody debris. Our study indicates that, in African savannas, the perceived landscape of fear is a highly dynamic phenomenon varying in both space and time and being species-specific. Elephant induced habitat changes may shape landscapes of fear in complex and contrasting ways.

Floral micromorphology of the bird-pollinated carnivorous plant species Utricularia menziesii R.Br. (Lentibulariaceae).

Bird pollination is rare among species in the genus Utricularia, and has evolved independently in two lineages of this genus. In Western Australia, the Western Spinebill, Acanthorhynchus superciliosus, visits flowers of Utricularia menziesii (section Pleiochasia: subgenus Polypompholyx). This study aimed to examine the micromorphology of U. menziesii flowers to assess traits that might be linked to its pollination strategy. Light microscopy, histochemistry and scanning electron microscopy were used. Nectar sugar composition was analysed using high-performance liquid chromatography. The flowers of U. menziesii fulfil many criteria that characterize bird-pollinated flowers: red colour, a large, tough nectary spur that can withstand contact with a hard beak, lack of visual nectar guides and fragrance. Trichomes at the palate and throat may act as tactile signals. Spur nectary trichomes did not form clearly visible patches, but were more frequently distributed along vascular bundles, and were small and sessile. Each trichome comprised a single basal cell, a unicellular short pedestal cell (barrier cell) and a multicelled head. These trichomes were much smaller than those of the U. vulgaris allies. Hexose-dominated nectar was detected in flower spurs. Fructose and glucose were present in equal quantities (43 ± 3.6 and 42 ± 3.6 g L-1). Sucrose was only detected in one sample, essentially at the limit of detection for the method used. This type of nectar is common in flowers pollinated by passerine perching birds. The architecture of nectary trichomes in U. menziesii was similar to that of capitate trichomes of insect-pollinated species in this genus; thus, the most important specializations to bird pollination were flower colour (red), and both spur shape and size modification. Bird pollination is probably a recent innovation in the genus Utricularia, subgenus Polypompholyx, and is likely to have evolved from bee-pollinated ancestors.

Abstract 1167: A syngeneic MIND model for triple-negative breast cancer: A novel metastatic mouse model for disease progression and therapeutic studies

Abstract Background and Objective: In the era of targeted therapy mouse models have significantly contributed to our understanding of cancer biology. Insight into the molecular pathways has opened new avenues for cancer therapeutic strategies. Majority of the available mouse models depict a portion of the breast cancer progression cascade to be investigated. Some mimic the tumorigenesis at an early stage, some portray the later stage of metastatic process. Additionally, most of the mouse models lack the ability to depict the functional contribution of immune system during metastatic progression because very often they deal with immune-compromised mice. Hence a mouse model that can represent all the stages of breast cancer tumorigenesis and metastasis in native microenvironment in presence of immunity is exceptionally essential. This notion gave us an idea to develop a syngeneic mice model that will epitomize all the breast cancer progression stages and in very short time. Methods: A modified mouse mammary intraductal (MIND) method was adopted for this study. MVT-1 and 4T1 cells were injected into cleaved nipples of 4th inguinal mammary glands of FVB/N and BALB/c wild-type female mice, respectively. The concentration of cells was 10,000 cells/µL. The final volume did not exceed 5 µL per injection per gland. Tissues were harvested at required time points. Histopathology was confirmed by haematoxylin-eosin staining and was further confirmed by immunohistochemical markers for cell proliferation, epithelial-to-mesenchymal transition (EMT), invasion, intravasation, extravasation and metastasis. Results and Conclusions: Primary tumor had been established by the end of first week of injection and was confirmed by histopathology and whole mount analysis of 4th inguinal mammary gland. During second week after cell inoculation, cells had gone through EMT and had prepared and started invasion. Invasion was followed by intravasation and metastasis. Microscopic metastatic patches in the lungs were observed during third week and visible patches were observed during fourth week after injection. The main advantage of this model is short time span. Our model becomes more relevant as the origin of primary tumor and metastasis takes place in same animal, closely resembling biologic progression of breast cancer with the ability to depict the functional contribution of immune system during metastatic progression. A syngeneic mice model like ours can recapitulate the successive stages of breast cancer tumor progression and metastasis and could give the entire picture of metastatic process. We believe that our syngeneic mouse model will facilitate “drug-hunters” and basic science researchers towards developing improved breast cancer treatment. Citation Format: Arnab Ghosh, Sandipto Sarkar, Fariba Behbod, Snigdha Banerjee, Ossama W. Tawfik, Sushanta K. Banerjee. A syngeneic MIND model for triple-negative breast cancer: A novel metastatic mouse model for disease progression and therapeutic studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1167.

I couldn't help but notice: Irrelevant object-scene inconsistencies influence search for highly visible gabor patches

I couldn't help but notice: Irrelevant object-scene inconsistencies influence search for highly visible gabor patches

Ungulates rely less on visual cues, but more on adapting movement behaviour, when searching for forage.

Finding suitable forage patches in a heterogeneous landscape, where patches change dynamically both spatially and temporally could be challenging to large herbivores, especially if they have no a priori knowledge of the location of the patches. We tested whether three large grazing herbivores with a variety of different traits improve their efficiency when foraging at a heterogeneous habitat patch scale by using visual cues to gain a priori knowledge about potential higher value foraging patches. For each species (zebra (Equus burchelli), red hartebeest (Alcelaphus buselaphus subspecies camaa) and eland (Tragelaphus oryx)), we used step lengths and directionality of movement to infer whether they were using visual cues to find suitable forage patches at a habitat patch scale. Step lengths were significantly longer for all species when moving to non-visible patches than to visible patches, but all movements showed little directionality. Of the three species, zebra movements were the most directional. Red hartebeest had the shortest step lengths and zebra the longest. We conclude that these large grazing herbivores may not exclusively use visual cues when foraging at a habitat patch scale, but would rather adapt their movement behaviour, mainly step length, to the heterogeneity of the specific landscape.

Pose-invariant face recognition with homography-based normalization

Pose-invariant face recognition (PIFR) refers to the ability that recognizes face images with arbitrary pose variations. Among existing PIFR algorithms, pose normalization has been proved to be an effective approach which preserves texture fidelity, but usually depends on precise 3D face models or at high computational cost. In this paper, we propose an highly efficient PIFR algorithm that effectively handles the main challenges caused by pose variation. First, a dense grid of 3D facial landmarks are projected to each 2D face image, which enables feature extraction in an pose adaptive manner. Second, for the local patch around each landmark, an optimal warp is estimated based on homography to correct texture deformation caused by pose variations. The reconstructed frontal-view patches are then utilized for face recognition with traditional face descriptors. The homography-based normalization is highly efficient and the synthesized frontal face images are of high quality. Finally, we propose an effective approach for occlusion detection, which enables face recognition with visible patches only. Therefore, the proposed algorithm effectively handles the main challenges in PIFR. Experimental results on four popular face databases demonstrate that the propose approach performs well on both constrained and unconstrained environments.

Radionuclide tagged blood cell patch to monitor spine coverage for spontaneous diffuse CSF leaks

We present a 14-year-old female patient with a 2 yr history of positional headache secondary to spontaneous diffuse cerebrospinal fluid (CSF) leaks. We treated the leak with an epidural blood patch which was radioactively labeled by a well- established nuclear medicine technique. Because spontaneous CSF leaks were frequently multifocal or diffuse throughout the spine, the extent of coverage or distribution of an epidural patch was generally determined by best estimate. Traditional radiographic contrast media mixed with the blood cellshad been used to monitor the patch coverage and it is questionable whether the contrast can be representative of the cell distribution. We applied a nuclear medicine technique to label the autologous red blood cells to monitor the range of spinal cord coverage of each epidural patch. After two visible epidural patches covered both the lumbar and thoracic spine, computed tomography myelogram demonstrated significantly decreased leakage when compared to the pre-patch images. However, the patient's symptoms remained essentially unchanged in the long term, which is consistent with refractory spontaneous CSF leaks. We believe that this sophisticated nuclear medicine blood labeling technique is a simple and accurate way to monitor the true cell coverage of the spine and the pattern of distribution.

Multimodal image matching via dual‐codebook‐based self‐similarity hypercube feature descriptor and voting strategy

An effective feature descriptor is proposed for multimodal local-image patch matching. The conventional self-similarity hypercube (SSH) fails in multimodal image matching due to different intensities of multimodal images. To mitigate this problem, a dual-codebook clustering is proposed for generating the descriptors. It is based on extracting a codebook, respectively, from visible and thermal images but sharing the same k -means clustering index of the local features of visible and thermal image patches. The experimental results show that the proposed approach effectively solves the multimodal image quantisation problem. Moreover, a voting strategy based on the proposed similarity family function facilitates the multimodal image matching more robustly compared with the conventional state-of-the-art methods.

Rapidly estimating numerosity independent of size-related distance or occlusion

Finding objects in natural environments presents a challenge for even simple objects with known properties. Because of occlusion and distance, the number and extent (visual angle) of visible surfaces do not directly convey the number of objects seen. Are those three reddish surfaces one nearby partially occluded apple or three distant apples? Resolving such ambiguities seems effortless for human observers. To benchmark human performance, we asked subjects to indicate which of two briefly pictured trees had more apples. Trees were generated in a virtual environment, and pairs were constructed with variations in occlusion, distance, or number of visible apples. Preliminary results show good performance (>95% correct) on the task, despite some less fruit-laden trees having double the visible apple area of their partners. Subjects did not simply respond to the extent of visible apple surfaces; their judgments were robust to variations in occlusion or visual angle. We believe this is the result of a multi-stage process similar to Xu and Chun's (TiCS, 2009) "individuation and identification" stages, where proto-objects with low-level features are first spatially localized then further refined into identifiable objects. We created a simple algorithm to investigate this hypothesis. First, it segments pixels with "tree-like" color (RGB values) by blurring and thresholding. It then tags apple-colored pixels within these tree-like regions. These pixels are convolved with a circular template whose radius depends on the area of the tree-like region. Local maximums give locations of apples that might explain the observed pixels, given the estimated tree size. This system can distinguish between a cluster of patches representing a single heavily-occluded apple nearby, versus multiple apples at a distance. It performs comparably to humans on our task, suggesting that subjects group proto-objects derived from visible patches into individual apples as a basis for numerosity judgments. Meeting abstract presented at VSS 2014

Evaluation of the susceptibility of apple genotypes in Queretaro, Mexico to powdery mildew (Podosphaera leucotricha)

The aim of this study was to evaluate the susceptibility to powdery mildew of apple (Malus domestica Borkh) genotypes introduced in Queretaro, Mexico. For this study, a total of 38 apple genotypes were used: 33 for the field assay and 14 for the greenhouse assay (with nine overlapping varieties). During the field assay, fungus incidence and severity were evaluated in adult plants grafted on the clonal rootstock MM 106, and this test was performed on four consecutive evaluations from May to September 2012. On the last sample, the conidial density was also determined on leaves with visible patches of powdery mildew. For the greenhouse bioassay, apple genotypes, grafted in January 2012 on MM 106, were inoculated on their adaxial side with 200μL of 7×104 conidia/mL (14,000 conidia). The incidence and severity of the fungus on the new shoots were evaluated in August and in October. In addition, the conidial densities per cm2 of leaf area and per leaf were determined for the last sample, and the correlation between the parameters evaluated was examined in each assay and between assays. ‘Rayada’ and ‘411’ showed the highest incidence (59.4 and 40.6%, respectively) and severity (120.0 and 128.3mm2, respectively) to powdery mildew in the field bioassay, in which most genotypes showed no visible damage caused by the fungus. ‘Lourdes’ and ‘436’ were the most resistant genotypes to powdery mildew in the greenhouse bioassay (no incidence, or severity), which means that they are recommended for cultivation in humid environments, and/or where little agronomic management is undertaken. The situation was different for ‘424,’ ‘428’, and ‘Royal Gala’ (with incidence rates of 32.6, 27.5, and 25.5%, and severity rates of 86.6, 229.5 and 168.8mm2, respectively), which, given their agronomic and quality advantages, could be grown under a strict phytosanitary program, or be used as an inoculum for experimental purposes. Significant correlations (P≤0.05) between incidence and severity were obtained in most cases, but no significant correlation with respect to powdery mildew susceptibility under field and greenhouse conditions was found.

Enhancing counselling strategies for leprosy patients through the Participation Scale

Counsellors provide psychological support, appropriate education and coping skills to persons affected by adverse events. Counselling of leprosy patients is essential to enable them to cope with perceived stigma as well as managing severe enacted stigma at home, place of work or elsewhere. Professional counselling was instituted at the Leprosy Mission Community Hospital in Naini, Allahabad District, India, in 2004. In this paper we describe how the use of the Participation Scale helped in developing Counselling strategies for a variety of leprosy patients. A random sample of 250 leprosy patients visiting the hospital for the first time during 2011-2012 were chosen, 50 each from those with only hidden patches (Grade 0a), patients with visible patches (Grade 0b), those with only anaesthesia or weakness (Grade I), patients with paralytic deformities (Grade 2a), and patients with visible disabilities and ulcers Grade 2b). The P-scale consisting of 18 items was administered in the local language (Hindi) and used by the Counsellor along with relevant clinical and socioeconomic details. There were 84 women and 166 men, distributed in all the five categories. Overall, 142 patients out of 250 (56.8%) had no participation restrictions; 39 (15.6%) had mild social restrictions; 20 (8.0%) had moderate, 28 (11.2%) had severe and 21 (84%) had extreme participation restrictions. Paradoxically, there were some cases without severe deformity who are also subjected to restrictions. Patients in Grades 0a and 0b, had practically no severe or even moderate restrictions in their social participation, but their perceived stigma was high, requiring suitable leprosy education, family counselling and coping skills to feel confident that they were capable of normal work like any of their peers. Counselling became more intensive in Grade 1 and for almost all in Grade 2, who experienced moderate to severe restrictions in meeting new people, participating in social activities and indulging in socioeconomic activities. Counselling for such groups of patients required multiple approaches, including in-depth leprosy education for regular treatment, self-care measures, mobilisation of coping skills, self-confidence and acceptance counselling, and follow-up counselling for thos released from treatment after multidrug therapy. The P-scale provides essential information to enable a Counsellor to offer more meaningful and balanced counselling to leprosy-affected people, especially in coping with enacted stigma. Education oriented counselling and psychological supportive counselling are necessary adjuncts for clinical care and treatment. Client-oriented counselling allows clients to freely express their fears and anxieties, and promotes coping skills and confidence.