Co‐existing monophasic teratoma and uterine adenocarcinoma in a female dog

Ovarian teratomas are occasionally reported in dogs; the rarest type is the monophasic teratoma,composed of tissues originating from only one germ layer. Canine endometrial adenocarcinomas are also rare in dogs and mainly affect geriatric females. This report describes case of co-existing ovarian teratoma and uterine adenocarcinoma in a 10-year old nulliparous female Boxer presented with lethargy, anorexia and purulent vaginal discharge. Abdominal ultrasonography evidenced pyometra and a mass in the left ovary. This was composed of a uniform whitish tissue with multiple cystic structures. The histology revealed an atrophy of the ovarian parenchyma, compressed by a proliferation of well-differentiated nervous tissue staining positively to vimentin, S100 and neuronal specific enolase (NSE), and negatively to keratin and inhibin. The left uterine horn, whose diameter was markedly increased, showed foci of endometrial cellular atypia, evident nucleoli and mitoses, at light microscopy. To our best knowledge, this is the first report of a coexisting ovarian monophasic teratoma and endometrial adenocarcinoma, two rare reproductive neoplasia in dogs

Variability of sclerosis along the longitudinal hippocampal axis in epilepsy: A post mortem study

Detailed neuropathological studies of the extent of hippocampal sclerosis (HS) in epilepsy along the longitudinal axis of the hippocampus are lacking. Neuroimaging studies of patients with temporal lobe epilepsy support that sclerosis is not always localised. The extent of HS is of relevance to surgical planning and poor outcomes may relate to residual HS in the posterior remnant. In 10 post mortems from patients with long histories of drug refractory epilepsy and 3 controls we systematically sampled the left and right hippocampus at seven coronal anatomical levels along the body to the tail. We quantified neuronal densities in CA1 and CA4 subfields at each level using Cresyl Violet (CV), calretinin (CR), calbindin (CB) and Neuropeptide Y (NPY) immunohistochemistry. In the dentate gyrus we graded the extent of granule cell dispersion, patterns of CB expression, and synaptic reorganisation with CR and NPY at each level. We identified four patterns of HS based on patterns of pyramidal and interneuronal loss and dentate gyrus reorganisation between sides and levels as follows: (1) symmetrical HS with anterior–posterior (AP) gradient, (2) symmetrical HS without AP gradient, (3) asymmetrical HS with AP gradient and (4) asymmetrical cases without AP gradient. We confirmed in this series that HS can extend into the tail. The patterns of sclerosis (classical versus atypical or none) were consistent between all levels in less than a third of cases. In conclusion, this series highlights the variability of HS along the longitudinal axis. Further studies are required to identify factors that lead to focal versus diffuse HS

Surveillance and control of the yarn input tension on circular weft knitting machines : new approaches

The Yarn Input Tension - YIT is one of the most important parameters in weft knitting industry. This parameter must be maintained between limits in order to produce knitted fabric without faults. However, YIT is not the only parameter to control and monitor for preventing faults. The knitting elements and the knitting machine itself should be monitored to improve productivity and quality. The monitoring of the YIT can be used to detect the faults and at the same time controlled inside tight limits to prevent machine’s premature stop due to yarn break . This paper will present the recent developments made for monitoring and control the YIT. A surveillance system will be presented, a low cost force sensor will be suggested to substitute the present industrial solutions, and a new actuator for control of the YIT will be introduced.FCT - Fundação para a Ciência e a Tecnologia POSI/SRI/39824/200

Using multivariate statistics on detection of particular signals during production of knitwear

This paper reports the recent developments in the pursuit to correctly locate, identify and distinguish faults during production of weft knitted fabrics. For this purpose a major textile parameter – yarn input tension (YIT) - is analyzed by means of signal processing techniques. An overview of the entire process of gathering the information and fault detection is presented. For the purpose of distinguishing faults, Multivariate statistical methods, namely cluster and discriminant analysis are used, results presented and discussed. Finally, some conclusions are drawn from the obtained results and future developments are addressed.Fundação para a Ciência e a Tecnologia (FCT) - project POSI/SRI/39824/2001

A system for knitting process monitoring and fault detection on weft circular knitting machines

From the production manager point of view, the knowledge of how well a knitting machine is working during production is very important. This information allows the manager to schedule all plans and also to know the overall production level of a manufacturing plant. For this purpose there are many system information packages. One of the most important items for production is the number of faults occurred while producing a fabric, since it directly influences productivity. With this subject in mind, this paper presents a system with a special emphasis on surveillance of the knitting process in order to detect, identify and locate faults during production, by monitoring the yarn input tension. The system also provides the user with a valuable set of information related with production. Finally, the paper presents some of the techniques used to detect the faults.Fundação para Ciência e Tecnologia (FCT) project POSI/SRI/39824/200

Knitting process surveillance using time and frequency analysis

This paper will present and discuss the two major techniques used when inspecting an important parameter of the weft knitting industry: yarn input tension. The two techniques are frequency and time analysis. In this paper, the major features of each technique will be discussed and some examples will be presented.Fundadação para a Ciência e a Tecnologia (FCT

A new system for monitoring and analysis of the knitting process

Production monitoring is an important task for proper production planning. For this task the information that a system of this nature can possibly gather assumes significant importance. Among all the information available during production, the detection of faults assumes a crucial role since it directly affects the quality and productivity. This paper presents a system which was developed with the purpose of performing the analysis in real time of the knitting process, supplying the parameters of major concern for production and furthermore, allowing the detection, identification and location of faults.Fundação para a Ciência e a Tenologia (FCT)projecto POSI/SRI/39824/200

Plants used by chimpanzees and humans in Cantanhez, Guinea-Bissau. Field guide

This is the final version. Available from LAE/CRIA via the link in this recordThe Portuguese version of this field guide is available in ORE: http://hdl.handle.net/10871/121034FC

Techniques for unveiling faults during knitting production

Detection of faults during production of knitted fabric is crucial for improved quality and productivity. The yarn input tension is an important parameter that can be used for this purpose. This paper will present and discuss a computer-based monitoring system which was developed for the detection of faults and malfunctions during the production of weft knitted fabric, using the yarn input tension. In particular, it will present the method used to unveil the appearance of faults, based on two different approaches: comparison with a previously acquired waveform and a particular pattern matching technique - Average Magnitude Cross-Difference.Fundação para a Ciência e a Tecnologia (FCT)

Textile-based pressure sensors for step detection: a preliminary assessment

This paper presents the development and performance assessment of textile-based sensor based on a three layer architecture for the step detection. Two different transducing elements (EeonTex™ LG-SLPA and velostat) and electrodes (Satatex Techniktex P-130 and Elitex yarns) were selected for the construction of the sensors. The performance of the resulting sensors was assessed based on a dynamometer cyclic compression/decompression test with different compressions loads and at different speeds. Additionally, a real-life experiment was conducted to evaluate the sensor response during walking. The results show that all sensors configurations have a non-linear resistance-force relation. The best sensor configuration for the step detection was the combination of EeonTex™ LG-SLPA as a transducing element and the Elitex yarns for the electrodes. In this configuration, the resistance magnitude varies in an order of hundreds of kohms between the stance and the swing phases.This work was partially financed by FEDER funds through the Competitively Factors Operational Programme—COMPETE and by national founds through FCT -Foundation for Science and Technology within the scope of Project POCI-01-0145-FEDER-007136 and Project PEstOE/EEI/UI0319/2014. Authors would like to thanks André Paiva and Sérgio Branco for their collaboration in sensors production and data acquisition, respectively.info:eu-repo/semantics/publishedVersio