"Rancang Bangun Prototype Smart Parking Berbasis Internet of Things (Iot)"

Perancangan prototype smart parking bertujuan untuk merancang alat monitoring kondisi lokasi parkir roda empat baik dari segi ketersediaan lokasi parkir berbasis Internet of Things (IoT) maupun keteraturan pengguna dalam memarkirkan kendaraannya. Deteksi tempat parkir yang kosong menggunakan sensor infra merah. Ketika terdapat mobil yang menghalangi pancaran cahaya infra merah cahaya tersebut akan dipantulkan dan diterima oleh receiver sensor infra merah, kemudian sinyal output sensor infra merah diteruskan ke server IoT dengan aplikasi blynk menggunakan perangkat wifi yang terintegrasi pada mikrokontroler NodeMCU ESP8266. Aplikasi ini kemudian akan menampilkan lokasi parkir yang kosong  atau yang sedang terisi. Setiap slot tempat parkir pada prototipe menggunakan pembatas yang dilengkapi dengan sensor kontak. Sensor ini membangkitkan alarm saat pengendara memarkirkan mobilnya melewati pembatas parkir. Hasil perancangan ini menunjukkan Pada Aplikasi Blynk apabila suatu slot parkir mendeteksi kerberadaan mobil ditampilkan indikator LED akan bewarna hijau dan jika tidak ada mobil maka bewarna hitam. Modul WiFi ESP8266 dapat terhubung dengan Aplikasi Blynk dan mengirimkan data dengan delay 5.21 - 6.66 detik. Kemudian alarm akan berbunyi ketika kendaraan melewati pembatas parkir

Statins in Candidemia: clinical outcomes from a matched cohort study

<p>Abstract</p> <p>Background</p> <p>HMG CoA reductase inhibitors (statins) in patients with bacteremic sepsis have shown significant survival benefits in several studies. There is no data on the effect of statins in candidemic patients, however in-vitro models suggest that statins interfere with ergesterol formation in the wall of yeasts.</p> <p>Methods</p> <p>This retrospective matched- cohort study from 1/2003 to 12/2006 evaluated the effects of statins on patients with candidemia within intensive care units. Statin-users had candidemia as a cause of their systemic inflammatory response and were on statins throughout their antifungal therapy, while non-statin users were matched based on age +/- 5 years and co-morbid factors. Primary analysis was 30-day survival or discharge using bivariable comparisons. Multivariable comparisons were completed using conditional logistic regression. All variables with a p-value less than 0.10 in the bivariable comparisons were considered for inclusion in the conditional logistic model.</p> <p>Results</p> <p>There were 15 statin-users and 30 non-statin users that met inclusion criteria, all with similar demographics and co-morbid conditions except the statin group had more coronary artery disease (P < 0.01) and peripheral vascular disease (P = 0.03) and lower median APCAHE II scores (14.6 vs 17, p = 0.03). There were no differences in duration of candidemia, antifungal therapy or <it>Candida </it>species between the groups. Statins were associated with lower mortality on bivariable (OR 0.09, 95% CI 0.11-0.75, p = 0.03) and multivariable (OR 0.22, 95% CI 0.02-2.4, p = 0.21) analyses compared to controls; although, in the latter the protective effect lacked statistical signficance.</p> <p>Conclusion</p> <p>In our small, single-center matched-cohort study, statins may provide a survival benefit in candidemia, however further studies are warranted to validate and further explore this association.</p

Analysing Predictive Coding Algorithms for Document Review

Abstract: Lawsuits and regulatory investigations in today's legal environment demand corporations to engage in increasingly intense data-focused engagements to find, acquire, and evaluate vast amounts of data. In recent years, technology-assisted review (TAR) has become a more crucial part of the document review process in legal discovery. Attorneys now have been using machine learning techniques like text classification to identify responsive information. In the legal domain, text classification is referred to as predictive coding or technology assisted review (TAR). Predictive coding is used to increase the number of relevant documents identified, while reducing human labelling efforts and manual review of documents. Deep learning models mixed with word embeddings have demonstrated to be more effective in predictive coding in recent years. Deep learning models, on the other hand, have a lot of variables, making it difficult and time-consuming for legal professionals to choose the right settings. In this paper, we will look at a few predictive coding algorithms and discuss which one is the most efficient among them. Keywords: Technology-assisted-review, predictive coding, machine learning, text classification, deep learning, CNN , Unscented Kalman Filter, Logistic Regression, SVM</jats:p

Analisis risiko kegiatan analisis kesehatan di laboratorium hematologi parahita

xv, 57 hlm. : ilus, ; 27 cm + lampira

Evaluasi Program Pembelajaran “Sains” Di Kelompok B TK Alam Kabupaten Klaten

Penelitian ini bertujuan untuk Mengetahui: (1) efektivitas Context yang mendukung program pembelajaran Sains yang di selenggarakan di TK Alam Kabupaten Klaten, (2) kualitas komponen Input dalam implementasi program pembelajaran Sains yang di selenggarakan di TK Alam Kabupaten Klaten, (3) efektivitas komponen Procces dalam program pembelajaran Sains yang di selenggarakan di TK Alam Kabupaten Klaten dan (4) Memperoleh hasil implementasi program pembelajaran Sains terhadap aspek perkembangan anak usia dini di TK Alam Kabupaten Klaten. Penelitian ini merupakan penelitian evaluasi dengan pendekatan kuantitatif. Model evaluasi yang digunakan yaitu model evaluasi (Context, Input, Procces, Product) CIPP. Penelitian ini di lakukan di TK Alam Kabupaten Klaten pada bulan Juni-Agustus 2017. Populasi dalam penelitian antara lain: TK Alam Harapan Kita Kota Klaten, TK Alam Aqila Kecamatan Wonosari Klaten, dan TK Alam Bengawan Solo Kecamatan Juwiring Klaten. Sampel penelitian ini terdiri dari 3 kepala sekolah, 12 guru, 6 orang tua, dan 15 peserta didik. Teknik pengumpulan data yang digunakan dalam penelitian ini berupa angket, observasi, dan dokumentasi. Penelitian ini menggunakan teknik analisis data deskriptif. Hasil penelitian menunjukkan bahwa: (1) Hasil evaluasi contexs program pembelajaran Sains di Kelompok B TK Alam Kabupaten Klaten dalam kategori efektif dengan skor rata-rata 2.74. (2) Hasil evaluasi input untuk mendukung program pembelajaran Sains di Kelompok B TK Alam Kabupaten Klaten dalam kategori efektif dengan skor rata-rata sebesar 2.67. (3) Hasil evaluasi procces pada program pembelajaran Sains di kelompok B TK Alam Kabupaten Klaten dalam kategori efektif dengan skor rata-rata yang mencapai 2,92.(4) Hasil evaluasi product program pembelajaran Sains di Kelompok B TK Alam Kabupaten Klaten dalam kategori efektif dengan skor rata-rata 2.7

Biological consequences of statins in Candida species and possible implications for human health

The statins, simvastatin and atorvastatin are the most widely prescribed drugs. Statins lower cholesterol levels through their action on HMG-CoA (3-hydroxy-3-methylglutaryl-CoA) reductase, an essential enzyme for the biosynthesis of cholesterol. Fungal HMG-CoA reductases are also inhibited by statins, resulting in reduced levels of ergosterol (the fungal equivalent of cholesterol) and concomitant growth inhibition. This effect occurs in a range of fungal species and possibly affects fungal colonization of people on statin therapy. Furthermore, it may suggest that statins could have a role in new antifungal therapies. Possibly associated with the reduction in ergosterol levels, statins also inhibit respiratory growth. In the yeast, Candida glabrata, passage with statins dramatically increased the frequencies of petite mutants that were devoid of mitochondrial DNA, suggesting that statins caused a defect in the maintenance of mitochondrial DNA. These observations in C. glabrata may provide further insights into side effects of statins in humans undergoing treatment for hypercholesterolemia. In addition, C. glabrata may be highly useful for the preliminary screening of agents to reduce statin side effects

Iron-Export Ferroxidase Activity of β-Amyloid Precursor Protein Is Inhibited by Zinc in Alzheimer's Disease

SummaryAlzheimer's Disease (AD) is complicated by pro-oxidant intraneuronal Fe2+ elevation as well as extracellular Zn2+ accumulation within amyloid plaque. We found that the AD β-amyloid protein precursor (APP) possesses ferroxidase activity mediated by a conserved H-ferritin-like active site, which is inhibited specifically by Zn2+. Like ceruloplasmin, APP catalytically oxidizes Fe2+, loads Fe3+ into transferrin, and has a major interaction with ferroportin in HEK293T cells (that lack ceruloplasmin) and in human cortical tissue. Ablation of APP in HEK293T cells and primary neurons induces marked iron retention, whereas increasing APP695 promotes iron export. Unlike normal mice, APP−/− mice are vulnerable to dietary iron exposure, which causes Fe2+ accumulation and oxidative stress in cortical neurons. Paralleling iron accumulation, APP ferroxidase activity in AD postmortem neocortex is inhibited by endogenous Zn2+, which we demonstrate can originate from Zn2+-laden amyloid aggregates and correlates with Aβ burden. Abnormal exchange of cortical zinc may link amyloid pathology with neuronal iron accumulation in AD