Enhancing FP-Growth Performance Using Multi-threading based on Comparative Study

The time required for generating frequent patterns plays an important role in mining association rules, especially when there exist a large number of patterns and/or long patterns. Association rule mining has been focused as a major challenge within the field of data mining in research for over a decade. Although tremendous progress has been made, algorithms still need improvements since databases are growing larger and larger. In this research we present a performance comparison between two frequent pattern extraction algorithms implemented in Java, they are the Recursive Elimination (RElim) and FP-Growth, these algorithms are used in finding frequent itemsets in the transaction database. We found that FP-growth outperformed RElim in term of execution time. In this context, multithreading is used to enhance the time efficiency of FP-growth algorithm. The results showed that multithreaded FP-growth is more efficient compared to single threaded FP-growth

Molecular Characterization of Cryptosporidium Species and Giardia duodenalis from Symptomatic Cambodian Children

Background: In a prospective study, 498 single faecal samples from children aged under 16 years attending an outpatient clinic in the Angkor Hospital for Children, northwest Cambodia, were examined for Cryptosporidium oocysts and Giardia cysts using microscopy and molecular assays. Methodology/Principal Findings: Cryptosporidium oocysts were detected in 2.2% (11/498) of samples using microscopy and in 7.7% (38/498) with molecular tests. Giardia duodenalis cysts were detected in 18.9% (94/498) by microscopy and 27.7% (138/498) by molecular tests; 82% of the positive samples (by either method) were from children aged 1–10 years. Cryptosporidium hominis was the most common species of Cryptosporidium, detected in 13 (34.2%) samples, followed by Cryptosporidium meleagridis in 9 (23.7%), Cryptosporidium parvum in 8 (21.1%), Cryptosporidium canis in 5 (13.2%), and Cryptosporidium suis and Cryptosporidium ubiquitum in one sample each. Cryptosporidium hominis and C. parvum positive samples were subtyped by sequencing the GP60 gene: C. hominis IaA16R6 and C. parvum IIeA7G1 were the most abundant subtypes. Giardia duodenalis was typed using a multiplex real-time PCR targeting assemblages A and B. Assemblage B (106; 76.8% of all Giardia positive samples) was most common followed by A (12.3%) and mixed infections (5.1%). Risk factors associated with Cryptosporidium were malnutrition (AOR 9.63, 95% CI 1.67–55.46), chronic medical diagnoses (AOR 4.51, 95% CI 1.79–11.34) and the presence of birds in the household (AOR 2.99, 95% CI 1.16–7.73); specifically C. hominis (p = 0.03) and C. meleagridis (p<0.001) were associated with the presence of birds. The use of soap was protective against Giardia infection (OR 0.74, 95% CI 0.58–0.95). Conclusions/Significance: This is the first report to describe the different Cryptosporidium species and subtypes and Giardia duodenalis assemblages in Cambodian children. The variety of Cryptosporidium species detected indicates both anthroponotic and zoonotic transmission in this population. Interventions to improve sanitation, increase hand washing after defecation and before preparing food and promote drinking boiled water may reduce the burden of these two parasites

Coronavirus Disease 2019 Disease Severity in Children Infected With the Omicron Variant

SHORT SUMMARY: Severe acute respiratory syndrome coronavirus 2 infection from the Omicron variant in children/adolescents is less severe than infection from the Delta variant. Those 6 to <18 years also have less severe disease than those <6 years old. BACKGROUND: There are limited data assessing coronavirus 2019 (COVID-19) disease severity in children/adolescents infected with the Omicron variant. METHODS: We identified children and adolescents <18 years of age with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with Delta and propensity score-matched controls with Omicron variant infection from the National COVID-19 Database in Qatar. Primary outcome was disease severity, determined by hospital admission, admission to the intensive care unit (ICU), or mechanical ventilation within 14 days of diagnosis, or death within 28 days. RESULTS: Among 1735 cases with Delta variant infection between 1 June and 6 November 2021, and 32 635 cases with Omicron variant infection between 1 January and 15 January 2022, who did not have prior infection and were not vaccinated, we identified 985 propensity score-matched pairs. Among those who were Delta infected, 84.2% had mild, 15.7% had moderate, and 0.1% had severe/critical disease. Among those who were Omicron infected, 97.8% had mild, 2.2% had moderate, and none had severe/critical disease (P < .001). Omicron variant infection (vs Delta) was associated with significantly lower odds of moderate or severe/critical disease (adjusted odds ratio [AOR], 0.12; 95% confidence interval [CI], .07-.18). Those aged 6-11 and 12 to <18 years had lower odds of developing moderate or severe/critical disease compared with those younger than age 6 years (aOR, 0.47; 95% CI, .33-.66 for 6-11 year olds; aOR, 0.45; 95% CI, .21-.94 for 12 to <18 year olds). CONCLUSIONS: Omicron variant infection in children/adolescents is associated with less severe disease than Delta variant infection as measured by hospitalization rates and need for ICU care or mechanical ventilation. Those 6 to <18 years of age also have less severe disease than those <6 years old

Life Cycle Management of Infrastructures

By definition, life cycle management (LCM) is a framework “of concepts, techniques, and procedures to address environmental, economic, technological, and social aspects of products and organizations in order to achieve continuous ‘sustainable’ improvement from a life cycle perspective” (Hunkeler et al.\ua02001). Thus, LCM theoretically integrates all sustainability dimensions, and strives to provide a holistic perspective. It also assists in the efficient and effective use of constrained natural and financial resources to reduce negative impacts on society (Sonnemann and Leeuw\ua02006; Adibi et al.\ua02015). The LCM of infrastructures is the adaptation of product life cycle management (PLM) as techniques to the design, construction, and management of infrastructures. Infrastructure life cycle management requires accurate and extensive information that might be generated through different kinds of intelligent and connected information workflows, such as building information modeling (BIM)

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

اقتراح أوسمة للنصوص العربية القصيرة باستخدام تحليل الدلالات الكامنة على الويكيبيديا العربية

Social media sites enable users to share items, such as texts and images, and annotate them with freely chosen keywords called tags. However, freedom comes at a cost: uncontrolled vocabulary can result in tag redundancy, ambiguity, sparsity, miss-spilling, and idiosyncrasy, thus impeding more effective organization/retrieval of resources in tagging systems. This work proposes an Arabic Language tag recommender system that exploits the Arabic Wikipedia as background knowledge. Latent semantic analysis was employed to discover hidden semantics between the short text and Wikipedia articles. Apache Spark was used to handle the massive content of Wikipedia and the complex computations of latent semantic analysis which is used to analyze Wikipedia articles into three matrices. Given an Arabic short text as input, the system compares it to the body of the articles and scores them according to their relevance to the short text. Candidate tags are determined from top-scored articles by exploiting articles' titles and categories. The proposed system was assessed over a dataset of 100 tweets covering three different domains. Generated tags were rated by two human experts in each domain. Our system achieved 84.39% mean average precision and 96.53% mean reciprocal rank, revealing the system adequacy and accuracy for tagging Arabic short texts while still has difficulties regarding Arabic language, and affected by frequencies of rare terms. A thorough analysis and discussion of the evaluation results are also presented to address the limitations and strengths as well as the recommendations for future improvements. Keywords: Short text, tag recommender, Arabic Language, Wikipedia, Latent Semantic Analysis, Sparkتتيح المواقع الاجتماعية للمستخدمين مشاركة المواد كالنصوص والصور، وتتيح حرية إضافة كلمات رئيسية لها تسمى أوسمة. ولكنَّ الحرية لها مساوئ منها: التكرار الناتج عن عدم ضبط الكلمات، الغموض، التشتت، الأخطاء الإملائية، والتفرّد، مما يعيق عمليات تنظيم واسترجاع البيانات في هذه الأنظمة. نهدف في هذا العمل إلى عرض نظام اقتراح أوسمة للنصوص العربية القصيرة بالاستفادة من الويكيبيديا العربية كمصدرٍ للمعلومات، بحيث يتم توظيفُ تحليلِ الدلالاتِ الكامنةِ لاكتشافِ التشابه بين النص القصير ومقالات الويكيبيديا. وقد استخدم "أباتشي سبارك" للتعامل مع الحجم الضخم لمحتويات الويكيبيديا والعمليات الحسابية المعقدة لتحليل الدلالات الكامنة المستخدم لتحليل محتوى مقالات الويكيبيديا إلى ثلاث مصفوفات، وعند إدخال نص عربي قصير، يقوم النظام بمقارنته مع محتوى المقالات ويعطي كل مقالةٍ وزناً حسب علاقتها وتشابهها مع النص المدخل، ثم يتم اختيار الأوسمة المرشحة من عناوين وتصنيفات المقالات الأكثر شبهًا بالنص. تم تقييم النظام المقترح اعتماداً على مجموعة من 100 نص قصير تم جمعها من موقع تويترفي ثلاث مجالات مختلفة و قام خبيران في كل مجال بتقييم الأوسمة التي أنتجها النظام. وقد حقق النظام المقترح 84.39% mean average precision و 96.53% mean reciprocal rank، مما يظهر مناسبة النظام ودقته لتوسيم النصوص العربية في حين أنه يواجه صعوبات تتعلق باللغة العربية وبتكرارات الكلمات النادرة. كما تم عرض تحليلٍ دقيقٍ ومناقشةٍ لنتائج التقييم تتناول نقاط القوة والقصور في النظام إضافة ًإلى توصياتٍ لتطوير العمل مستقبلاً. كلمات مفتاحية: نصوص قصيرة، اقتراح أوسمة، اللغة العربية، ويكيبيديا، تحليل الدلالات الكامنة، سبار