Prostate cancer is the most dangerous cancer diagnosed in men worldwide. Prostate diagnosis has been affected by many factors, such as lesion complexity, observer visibility, and variability. Many techniques based on Magnetic Resonance Imaging (MRI) have been used for prostate cancer identification and classification in the last few decades. Developing these techniques is crucial and has a great medical effect because they improve the treatment benefits and the chance of patients\' survival. A new technique that depends on MRI has been proposed to improve the diagnosis. This technique consists of two stages. First, the MRI images have been preprocessed to make the medical image more suitable for the detection step. Second, prostate cancer identification has been performed based on a pre-trained deep learning model, InceptionResNetV2, that has many advantages and achieves effective results. In this paper, the InceptionResNetV2 deep learning model used for this purpose has average accuracy equals to 89.20%, and the area under the curve (AUC) equals to 93.6%. The experimental results of this proposed new deep learning technique represent promising and effective results compared to other previous techniques.

En Venezuela se ha abierto una vez más el debate por la calidad educativa, lo cual es un tema álgido porque es estratégico y tiene que ver con la formación de los ciudadanos y ciudadanas a dirigir la sociedad. Al gobierno nacional en el contexto del socialismo del Siglo XXI le corresponde promover un proyecto educativo de acuerdo al tipo de sociedad que se desee forjar,pero a su vez este debe dar respuesta a los organismos supranacionales que se han planteado metas educativas para el milenio que pasan por incorporar a toda la poblacion al sistema educativo en correspondencia el sistema economico como expresion de una verdadera inclusion social;de manera que el socialismo del Siglo XXI trasciende el plan nacional de desarrollo para ubicarse en el proceso de globalizacion e integracion latinoamericana.

Adult granulosa cell tumor (GCT) of the ovary is oftentimes a hormonally active, stromal cell neoplasm that is distinguished by its ability to secrete sex steroids such as estrogen and is mostly diagnosed in postmenopausal women. Patients may present with vaginal bleeding as a result of prolonged exposure to tumor-derived estrogen. In addition, GCT is a vascular tumor that may occasionally rupture and result in abdominal pain, hemoperitoneum, and hypotension, mimicking an ectopic pregnancy in younger patients. We report a rare case of a metastatic adult granulosa cell tumor of the ovary in a 25-year-old woman who presented with abdominal swelling and pain for the last 6 months with an ill-defined, firm left adnexal mass on pelvic examination with ascites. Cytological impression of the ascitic tap was suggestive of Granulosa cell Tumor. Histopathology of the mass confirmed the cytopathological diagnosis.

ABSTRACT\nAn attempt was made to understand the food habits of sloth bear inside a tea plantation between\nOctober 2011 and March 2012 in Kolacamby, Nilgiris District, Tamil Nadu, India. During the\nstudy period, 16 sloth bears were sighted in 12 encounters: eight adult, three cubs, and five subadults.\nAll the encounters were during the early morning and late evening hours. On most of the\noccasions sloth bears were found actively feeding termites and fruits of lantana camera. In total,\n136 scats of sloth bear were collected and analyzed. Food items found in the scats varied from\nplant to animal matter. Animal matters were more during the months of February and March while\nplant matters dominated the diet in the month of December. Lantana camara, Ficus sp., and\nCoffea arabica were found in the scats of sloth bear and of which Lantana and Ficus sp.\ndominated most of the scats. In the animal matters, ants were very frequent while the presence of\nhoney bee was very meager. The human–sloth bear conflict was very meager inside the garden.\nThe only negative impact of sloth bear for planters was the damage done to the root systems of\nplants because of digging by sloth bears.

With the increasing usage of internet there requires a significant system for effective communication. To provide an effective communication for the internet users, based on nature of their queries, shortest routing path is usually preferred for data forwarding. But when more number of data chooses the same path, in that case, bottleneck occurs in the traffic this leads to data loss or provides irrelevant data to the users. For monitoring the traffic occurrence over the network, several approaches are presented by the authors. However, existing Concept-based User Profiles (CUP) considered both the positive and negative preferences while constructing a user profile and the interestingness of the users’ were obtained using Ranking SVM (RSVM). But the traffic pattern was not observed as a result though the concept was obtained from similar user profiles, with the streaming of data differing heavily user profiles obtained resulted in redundancy. Similarly, Mining Group Movement Patterns (GMP), identified the group of objects with similar moving patterns based on the similarity factor which achieved good grouping quality, but the decision regarding when to group remain unaddressed. To solve the above said issue, a Rule Based System using Improved Apriori (RBS-IA) rule mining framework is used to integrate both the traffic control and decision making system to enhance the usage of internet trendier. At first, the network traffic data is analyzed and the incoming and outgoing data information is processed using apriori rule mining algorithm. After generating the set of rules, the network traffic condition is analyzed. Based on the traffic conditions, the decision rule framework is introduced which derives and assigns the set of suitable rules to the appropriate states of the network. The decision rule framework improves the effectiveness of network traffic control by updating the traffic condition states for identifying the relevant route path for packet data transmission. Experimental evaluation is conducted by extracting the Dodgers loop sensor data set from UCI repository to detect the effectiveness of the proposed Rule Based System using Improved Apriori (RBS-IA) rule mining framework. Performance evaluation shows that the proposed RBS-IA rule mining framework provides significant improvement in managing the network traffic control scheme. RBS-IA rule mining framework is evaluated over the factors such as accuracy of the decision being obtained, interestingness measure and execution time.

The aim of this study was to investigate the effect of lactation number and months on milk yield, somatic cell count (SCC) and udder measurements in Holstein cows. Thirty cows in first lactation and 49 cows in second lactation cows were used in the study. Daily milk yield, SCC and monthly udder measurements were determined. It was observed that the effect of lactation number on lactation milk yield (P<0.01) and SCC (P<0.05) was significant. \nThe effect of lactation number on udder measurements was significant (P<0.01) except front teat length (FTD). Influence of lactation months on milk yield and SCC was significant (P<0.01). The effect of lactation months on distance between front teats (DFT), distance between rear teats (DRT), front diameter teats (FTD), rear teat diameters (RTD) was significant (P<0.01), while the other udder measurements were non-significant (P>0.05). A negative correlation was found between SCC and milk yield, front teat clearance from ground (FTC) and rear teat clearance from ground (RTC). On the other hand, a positive correlation was also evident between RTD and distance between front and rear teats (DFR). Furthermore, there were positive correlation between milk yield and DFT, DFR, DRT and FTD, whereas a negative correlation was observed between milk yield and FTC. In conclusion, cows in second lactation showed importantly increased milk yield and SCC as compared to cows in first lactation, whereas FTC and RTC decreased and other udder measurements increased.

In this article, the Cauchy\'s integral and Laguerre polynomials have been used to derive a formula for inverse Laplace transform. Moreover, a number of identities involving Laguerre polynomials have been presented, and as an application of theorems and their results, a number of infinite integrals and illustrative examples are also provided.

Purpose of this paper is to introduce an invention in working principle of Allopathic, Homeopathic, Ayurvedic system of Medicines, with Vaccination, Physical Exercise, Yogic Exercise and Meditation etc. Development and use of Toxic substances from dead body of bad elements (Bacteria, virus, fungus, parasites etc) is very essence. This shows how minimum quantity of medicines recovers the diseases in a living being with the least side effects. It also identifies that by Physical Exercise, Yogic Exercise, Meditation etc., disease free condition can be prevailed. Thus Perfect School of Medicines is designed keeping in view of medicinal as well as toxic substances effect derived from dead bad elements.