Venous lesions in Beh?et''s disease

This study examined 117 patients with mild cervical atypia or atypical squamous cells of uncertain significance; it was found that 25% had histologically proven CIN lesions by colposcopically-directed punch biopsy or cone biopsy. 18% were found to have at least CIN 2 lesions and there was 1 case of invasive cancer. These data strongly support the recommendation of early colposcopic referral in patients with mild cervical atypia.     

Pretreatment of Steel Racetracks by Using a Sand-Blasting Technique with a Special Emphasis on Si3N4 Powder—Part Three

Additional rolling fatigue experiments as well as pure sliding, bending, and scratching tests of the Si₃ N ₄ sand-blasted steel surface have been carried out. Acquired results reconfirm the extraordinary tenacity of the self-attaching Si₃ N ₄ surface layer in terms of both anti-fatigue and antiwear characteristics, especially in the “hybrid” ball bearing. It appears that this Si₃ N ₄ sand layer can be identified as a complex, self-organizing, and adaptive system.     

RETRACTED ARTICLE: Document image analysis: issues,comparison of methods and remaining problems

Image analysis is an interesting research area with a large variety of challenging applications. Researchers have worked from decades on this topic, as witnessed by the scientific literature. However, document image analysis is the special case in image analysis as their spatial properties are different from natural images. Therefore, the main focus of this paper is to describe image denoising issues in general and document image issues in particular. Since the field of document processing is relatively new, it is also dynamic, so current methods have room for improvement and innovations are still being made. Several algorithms proposed in the literature are described. Critical discussions are reported about the current status of the field and open problems are highlighted. It is also demonstrated that, there are rarely definitive techniques for all cases of a certain problem. We surveyed the state of art, analyzed recent trends and tried to identify challenges for future research in this field.     

Production of aromatics by catalytic fast pyrolysis of cellulose in a bubbling fluidized bed reactor

Catalytic fast pyrolysis of cellulose was studied at 500°C using a ZSM‐5 catalyst in a bubbling fluidized bed reactor constructed from a 4.92‐cm ID pipe. Inert gas was fed from below through the distributor plate and from above through a vertical feed tube along with cellulose. Flowing 34% of the total fluidization gas through the feed tube led to the optimal mixing of the pyrolysis vapors into the catalyst bed, which experimentally corresponded to 29.5% carbon aromatic yield. Aromatic yield reached a maximum of 31.6% carbon with increasing gas residence time by changing the catalyst bed height. Increasing the hole‐spacing in the distributor plate was shown to have negligible effect on average bubble diameter and hence did not change the product distribution. Aromatic yields of up to 39.5% carbon were obtained when all studied parameters were optimized. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1320–1335, 2014     

Atmospheric pressure photoionization mass spectrometry

Atmospheric pressure photoionization (APPI) is the last arrival in the family of atmospheric pressure ionization (API) methods to couple mass spectrometry (MS) to liquid-phase separation techniques. The basic idea was to further extend the fields of application of liquid chromatography (LC)-MS to those molecules that are not, or are poorly amenable, to electrospray (ESI) or APCI. The present review explores the literature. After a short introduction with an historical background and the premises for its development, we describe the technique, its physical principles, and the factors that affect its efficiency. The review also presents a survey of applications in different fields.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Pollen morphological investigations of family Cactaceae and its taxonomic implication by light microscopy and scanning electron microscopy

The family Cactaceae is the diversified group of angiosperm plants whose pollen statistics has been used for taxonomic identification. In this article, we present the pollen morphology of eight species belong to seven taxonomically complex genera of Cactaceae including Astrophytum, Cylindropuntia, Echinocereus, Echinopsis, Mammillaria, Opuntia, and Thelocactus using light and scanning electron microscopy. The pollen grains were acetolyzed, measured, described, and electron photomicrographs were taken. Cactaceae can be characterized by presenting different palynomorphological features including pollen type, sculpturing, polar and equatorial diameter, aperture orientation, exine thickness, P/E ratio, and echini features. Four types of pollen shapes, that is, prolate spheroidal (three species), subprolate (two species), prolate (two species), and oblate spheroidal in Echinocereus reichenbachii were observed. The polar and equatorial diameter observed maximum in O. ficus indica 116.95 and 112.27 μm while minimum in M. compressa 38.42 and 21.05 μm. Pollen of two types, tricolpate in members of subfamily Cactioideae and pantoporate in the Opuntioideae were examined. The fertility percentage has been observed maximum in Opuntia macrocentra (83.84%) and minimum in Opuntia ficus‐indica (57.89%). Exine sculpturing showing great variations such as granulate, reticulate, granulate perforate and micro‐echinate foveolate ornamentation was examined only in Echinopsis eyriesii. A key to species, based on pollen micromorphological attributes, has been constructed for correct identification of complex cactus species.     

Automated techniques for blood vessels segmentation through fundus retinal images: A review

Retina is the interior part of human's eye, has a vital role in vision. The digital image captured by fundus camera is very useful to analyze the abnormalities in retina especially in retinal blood vessels. To get information of blood vessels through fundus retinal image, a precise and accurate vessels segmentation image is required. This segmented blood vessel image is most beneficial to detect retinal diseases. Many automated techniques are widely used for retinal vessels segmentation which is a primary element of computerized diagnostic systems for retinal diseases. The automatic vessels segmentation may lead to more challenging task in the presence of lesions and abnormalities. This paper briefly describes the various publicly available retinal image databases and various machine learning techniques. State of the art exhibited that researchers have proposed several vessel segmentation methods based on supervised and supervised techniques and evaluated their results mostly on publicly datasets such as digital retinal images for vessel extraction and structured analysis of the retina. A comprehensive review of existing supervised and unsupervised vessel segmentation techniques or algorithms is presented which describes the philosophy of each algorithm. This review will be useful for readers in their future research.     

Taxonomic study of subfamily Nepetoideae (Lamiaceae) by polynomorphological approach

The present study is insight into pollen morphology for characterizing species and their utility in the taxonomic separation of certain taxa of subfamily Nepetoideae (Lamiaceae) from Pakistan. The pollen micromorphology of 11 species of the Nepetoideae was analyzed and documented using light microscopy and scanning electron microscopy (SEM) for both qualitative and quantitative characteristics. Most species have hexazonocolpate pollen grains but trizonocolpate and tetrazonocolpate pollen with circular and oval amb were also rarely observed in Mentha spicata. The basic pollen shape in most of the studied species was subspheroidal but prolate grains were also observed in M. spicata, S. coccinea, and S. plebeia. The exine sculpturing of Nepetoideae pollen was taxonomically very informative particularly at subfamily level. Observations of exine sculpturing with SEM revealed various types of pollen grains: reticulate, bireticulate, microreticulate, perforate, aerolate, and gammate. The bireticulate type further subdivided into three subtypes based on the number of secondary lumina in each primary lumen and is characterized by varying characteristics of the secondary reticulum and primary muri. A significant variation was observed in colpus surface ornamentation. The maximum polar diameter was found in O. americanum (58 ± 5.8 μm) and the maximum equatorial diameter observed in O. basilicum (50.25 ± 1.37 μm). Pollen features of the studied species were discussed and compared based on the current taxonomical concepts. The results showed that pollen traits of the subfamily Nepetoideae was found significant to classify the taxa. Furthermore, pollen features provide additional evidence to distinguish macromorphologically similar taxa from each other.     

Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito. The parasite transferred into complex life round in which it is grown and reproduces into the human body. The detection and recognition of Plasmodium species are possible and efficient through a process called staining (Giemsa). The staining process slightly colorizes the red blood cells (RBCs) but highlights Plasmodium parasites, white blood cells and artifacts. Giemsa stains nuclei, chromatin in blue tone and RBCs in pink color. It has been reported in numerous studies that manual microscopy is not a trustworthy screening technique when performed by nonexperts. Malaria parasites host in RBCs when it enters the bloodstream. This paper presents segmentation of Plasmodium parasite from the thin blood smear points on region growing and dynamic convolution based filtering algorithm. After segmentation, malaria parasite classified into four Plasmodium species: Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, and Plasmodium malaria. The random forest and K‐nearest neighbor are used for classification base on local binary pattern and hue saturation value features. The sensitivity for malaria parasitemia (MP) is 96.75% on training and testing of the proposed approach while specificity is 94.59%. Beside these, the comparisons of the two features are added to the proposed work for classification having sensitivity is 83.60% while having specificity is 94.90% through random forest classifier based on local binary pattern feature.