Essential primary thrombocytosis in a diabetic patient

Essential thrombocytosis also referred to as essential thrombocythemia, idiopathic thrombocytosis, primary thrombocytosis and hemorrhagic thrombocythemia is an uncommon myeloproliferative disorder of unknown cause in which marked proliferation of the megakaryocytes in the bone marrow leads to elevation of the platelet count. We report here a case of type 2 diabetic patient with essential thrombocytosis

Kajian Pemberian Zat Pengatur Tumbuh Terhadap Pertumbuhan Stek Tanaman Buah Naga (Hylocereus Costaricensis)

Tanaman buah naga ( Hylocereus costaricensis) merupakan salah satu tanaman yang berasal dari family Cactaceae yang tergolong baru di masyarakat Indonesia. Kebutuhan buah naga di Indonesia cukup besar, namun kebutuhan tersebut belum mampu dipenuhi oleh produsen. Tujuan penelitian ini adalah untuk mengetahui adanya interaksi antar kombinasi perlakuan yang tepat dalam perbanyakan tanaman buah naga. Penelitian ini dilaksanakan pada bulan Mei sampai Juli 2014 dalam green house STPP Malang dengan menggunakan Rancangan Acak Kelompok Faktorial (RAKF) dengan faktor 1: bahan stek yaitu B1 batang ujung dan B2 batang bawah dan faktor 2: konsentrasi ZPT sebagai perlakuan(1 kontrol dan 6 perlakuan) dan 3 ulangan, yaitu : N0 : Kontrol (Tanpa ZPT), N1 : 25 mg/10 ml, N2 : 50 mg/10 ml, N3 : 75 mg/10 ml, N4 : 100 mg/10 ml, N5 : 125 mg/10 ml, dan N6 : 150 mg/10 ml. Pengamatan yang dilakukan secara distruktif dan non distruktif. Hasil penelitian menunjukkan adanya interaksi nyata pada kombinasi perlakuan bahan stek dengan konsentrasi ZPT terhadap pertumbuhan buah naga pada parameter pengamatan saat muncul tunas (hst), persentase tanaman berakar, Jumlah tunas dan panjang tunas, Sedangkan untuk parameter pengamatan persentase tanaman hidup (%), persentase tanaman berakar, jumlah akar, persentase tanaman bertunas, serta bobot basah, menunjukan hasil yang tidak berbeda nyata terhadap perlakuan kombinasi bahan stek dan konsentrasi ZPT. Pada parameter pengamatan persentase tanaman hidup perlakuan kombinasi N4B1, N5B1, N6B1, N1B2, N3B2, N4B2, dan N5B2 menunjukkan persentase tanaman hidup 100%

COMPUTATIONAL MOLECULAR MODELLING OF 2-AMINOBENZIMIDAZOLE DERIVATIVES: STRONG SUCCESSOR OF HYPOGLYCAEMIC AGENT

Objective: The present study was aimed to design different analogues of 2-aminobenzimidazole and find the binding ability by Insilico method. Methods: Various soft wares like Chemsketch, Molinspiration, PASS, and Discovery studio were used to design the proposed derivatives. Evaluation of binding activity against different receptors was detected and checked their physicochemical properties for binding. Results: In this study, we designed different analogs of 2-aminobenzimidazole into a ligand having a binding affinity with alpha-glucosidase, Dipeptidyl–peptidase 4(DPP4), Peroximase proliferator-activated receptor gamma (PPARγ), and Insulin-like growth factor 1(IGF-1) receptor. The designed ten derivatives showed a significant binding capacity to the concerned receptors. Conclusion: These results pointed that the designed proposed derivatives promising hypoglycaemic activity

Cloud Service Selection System Approach based on QoS Model: A Systematic Review

The Internet of Things (IoT) has received a lot of interest from researchers recently. IoT is seen as a component of the Internet of Things, which will include billions of intelligent, talkative "things" in the coming decades. IoT is a diverse, multi-layer, wide-area network composed of a number of network links. The detection of services and on-demand supply are difficult in such networks, which are comprised of a variety of resource-limited devices. The growth of service computing-related fields will be aided by the development of new IoT services. Therefore, Cloud service composition provides significant services by integrating the single services. Because of the fast spread of cloud services and their different Quality of Service (QoS), identifying necessary tasks and putting together a service model that includes specific performance assurances has become a major technological problem that has caused widespread concern. Various strategies are used in the composition of services i.e., Clustering, Fuzzy, Deep Learning, Particle Swarm Optimization, Cuckoo Search Algorithm and so on. Researchers have made significant efforts in this field, and computational intelligence approaches are thought to be useful in tackling such challenges. Even though, no systematic research on this topic has been done with specific attention to computational intelligence. Therefore, this publication provides a thorough overview of QoS-aware web service composition, with QoS models and approaches to finding future aspects

Perubahan Spatio-temporal B-value Gempa Mikro Di Lapangan Panasbumi X

Telah dilakukan penelitian mengenai karakteristik gempa mikro di lapangan panasbumi X. Penelitian ini dilakukan untuk mengetahui karakteristik gempa mikro terkait dengan variasi spatio-temporal parameter b-value. Data yang digunakan merupakan data sekunder milik PT Pertamina Geothermal Energy sebanyak 138 kejadian gempa mikro yang terjadi selama periode 2013-2014. Perhitungan parameter b-valuedilakukan dengan metode maximum likelihood di program ZMAP dengan analisa variasi secara spasial dan temporal. Hasil perhitungan b-value di lapangan panasbumi X cukup tinggi yaitu sekitar 1 – 3 dan mengindikasikan bahwa keadaan batuan daerah penelitian heterogen serta cenderung tidak mengakumulasikan stress sehingga banyak gempa mikro yang terjadi. Variasi spasial b-value menunjukkan bahwa di sekitar sumur injeksi b-value cenderung tinggi (1.9 – 2.1) akibat peningkatan tekanan dibandingkan dengan di area sumur produksi dengan b-value 1.6 – 1.8. Variasi temporal b-valuemenunjukkan dua pola seismisitas di lapangan panasbumi X yaitu penurunan b-value diikuti dengan gempa berukuran besar (bulan April, Agustus, September dan Desember 2013 serta Februari 2014) serta ketika b-value meningkat banyak gempa mikro yang terjadi (bulan April 2013 serta Januari dan April 2014)

Single Arc Truncated Suspended Rectangular Microstrip Antenna

Today antenna designers are paying more focus on microstrip patch antennas, because of its numerous advantages in field of communication, such as high reliability, light weight, ease of fabrication etc. In this paper design of Single Arc Truncated Suspended Rectangular Microstrip Antenna (SATSRMSA) is presented which operates for dual bands. The substrate material of FR-4 with relative permittivity 4.4 and loss tangent of 0.0245 is used in th0is proposed antenna. The return loss and radiation pattern have been measured by using Vector Network Analyzer. The proposed antenna may find application in microwave communication systems operating in the frequency range of 3 to 16 GHz

Comparison of neonatal outcome parameters between thick and thin meconium stained liquor: a prospective study

Background: Meconium stained liquor is a commonly observed phenomenon in the day-to-day obstetric practice, the incidence being 12-22%. Meconium stained liquor can be considered as a normal physiological event in a term fetus in the absence of fetal heart rate abnormalities. It has greater significance as one of the parameters of fetal distress, when associated with abnormal fetal heart rate pattern. The aim of the present study was to study the association of, fetal heart rate abnormalities, mode of delivery and neonatal outcome with different grades of meconium stained liquor.Methods: A prospective study was conducted in one hundred and fifty cases of meconium stained liquor beyond 37 weeks gestation admitted to the labor room in a tertiary care Centre. Depending on the consistency of meconium, the patients were divided into two groups namely, Thick meconium stained liquor (group K) and Thin meconium stained liquor (group N). Maternal conditions, Intrapartum fetal heart rate pattern, Apgar scores and neonatal morbidities were studied in relation to the grade of meconium. The proportions between the two groups were compared using chi-square test and Fisher’s exact t-test.Results: The incidence of post term pregnancy (p=0.004), unbooked (p=0.007) status and oligohydramnios (p=0.01) were significantly higher among group K when compared to group N. Non-reassuring fetal heart rate pattern (p=0.002) and Apgar score ≤7 (p=0.02) were significantly higher in group K. In group K, non-reassuring fetal heart rate pattern and reduced beat to beat variability were significantly associated with low Apgar score (p=0.01).Conclusions: Neonatal outcomes like low Apgar score, meconium aspiration syndrome are strongly associated with thick meconium stained liquor. Visual grading of liquor into thick and thin meconium stained may help in timely obstetric intervention leading to a better neonatal outcome

Detection of Diseases in Flora Through Leaf Image Classification by Convolution Neural Network

The quality of human existence and economic standing are significantly impacted by agriculture. It is the foundation of a nation's economic structure. Therefore, early diagnosis of plant diseases is crucial in both the agricultural sector and in people's daily life. Hunger and starvation are caused by agricultural losses due to plant diseases, especially in less developed nations where access to disease-controlling measures is limited and yearly losses of 30 to 50 percent for main crops are not unusual. Due to inadequate diagnosis of plant diseases, many plants die. Initially, diagnosis of plant disease was performed using MATLAB and machine learning algorithms including SVM. But these diagnoses did not provide accurate results. Also, in previous works website has not been created. To overcome this problem, a CNN model has been proposed that detects plant diseases. This CNN model has been deployed to the website. On this website, the image can be uploaded, and the disease gets predicted according to the image. The detected disease gets displayed on the website. To the CNN model, 15 cases have been fed, including both healthy and unhealthy leaves. The proposed model achieves a greater accuracy of more than 95%. This work offers a major benefit to the farmers by helping them in detecting plant diseases without requiring any special hardware or software

An Adaptive Technique for Crime Rate Prediction using Machine Learning Algorithms

Any country must give the investigation and preventive of crime top priority. There are a rising amount of cases that are still pending due to the rapid increase in criminal cases in India and elsewhere. It is proving difficult to classify and address the rising number of criminal cases. Understanding a place's trends in criminal activity is essential to preventing it from occurring. Crime-solving organisations will be more effective if they have a clear awareness of the patterns of criminal behavior that are present in a particular area. Women's safety and protection are of highest importance despite the serious and persistent problem of crime against them. This study offers predictions about the kinds of crimes that might occur in a particular location using ensemble methods. This facilitates the categorization of criminal proceedings and subsequent action in a timely manner. We are applying machine learning methods like KNN, Linear regression, SVM, Lasso, Decision tree and Random forest in order to assess the highest accuracy