Every organization needs to invest in order for it to grow, and investments are made through projects. Thus, investment management is performed by applying project management techniques. Different project management software programs are used to manage multiple projects. There is a lot of project management software on the market, and four pieces of the software were selected and analyzed. In this paper, the best management software rated by the beneficiaries of these projects in the United Arab Emirates are explored. The research required for this study was conducted in the United Arab Emirates. The MARCOS method was used to evaluate the program. The results showed that Smartsheet had been rated the best by users. This paper provides an overview of how multicriteria analysis methods can be used when ranking project management programs.

Early characterization of security requirements supports system designers to integrate security aspects into early architectural design. However, distinguishing security related requirements from other functional and non-functional requirements can be tedious and error prone. To address this issue, machine learning techniques have proven to be successful in the identification of security requirements. In this paper, we have conducted an empirical study to evaluate the performance of 22 supervised machine learning classification algorithms and two deep learning approaches, in classifying security requirements, using the publicly availble SecReq dataset. More specifically, we focused on the robustness of these techniques with respect to the overhead of the pre-processing step. Results show that Long short-term memory (LSTM) network achieved the best accuracy (84%) among non-supervised algorithms, while Boosted Ensemble achieved the highest accuracy (80%), among supervised algorithms.

The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes inspiration from the highly parallel, low‐power, high‐speed, and noise‐tolerant computing capabilities of the brain, may provide such a shift. Many researchers from across academia and industry have been studying materials, devices, circuits, and systems, to implement some of the functions of networks of neurons and synapses to develop neuromorphic computing platforms. These platforms are being designed using various hardware technologies, including the well‐established complementary metal‐oxide semiconductor (CMOS), and emerging memristive technologies such as SiOx‐based memristors. Herein, recent progress in CMOS, SiOx‐based memristive, and mixed CMOS‐memristive hardware for neuromorphic systems is highlighted. New and published results from various devices are provided that are developed to replicate selected functions of neurons, synapses, and simple spiking networks. It is shown that the CMOS and memristive devices are assembled in different neuromorphic learning platforms to perform simple cognitive tasks such as classification of spike rate‐based patterns or handwritten digits. Herein, it is envisioned that what is demonstrated is useful to the unconventional computing research community by providing insights into advances in neuromorphic hardware technologies.

Background Histone deacetylase 9 (HDAC9) plays an important role in transcriptional regulation, cell cycle progression and developmental events; moreover, it has been investigated as a candidate gene in a number of conditions, including the onset and progression of atherosclerosis. We hypothesized that the rs2107595 HDAC9 gene polymorphism may be associated with advanced carotid artery disease in a Slovenian cohort. We also investigated the effect of this polymorphism on HDAC9 receptor expression in the internal carotid artery (ICA) specimens obtained by endarterectomy. Methods This case-control study enrolled 619 unrelated Slovenian patients: 311 patients with ICA stenosis > 75% as the study group and 308 patients with ICA stenosis < 50% as the control group. Patient laboratory and clinical data were obtained from the medical records. The rs2107595 polymorphisms were genotyped using TaqMan SNP Genotyping assay. HDAC9 expression was assessed by immunohistochemistry in 30 ICA specimens from patients with ICA atherosclerosis > 75%, and the numerical areal density of HDAC9 positive cells was calculated. Results The occurrence of advanced ICA atherosclerosis in the Slovenian cohort was 3.81 times higher in the codominant genetic model (OR = 3.81, 95%CI = 1.06–13.77, p  = 0.04), and 3.10 times higher in the recessive genetic model (OR = 3.10, 95%CI = 1.16–8.27, p  = 0.02). In addition, the A allele of rs2107595 was associated with increased HDAC9 expression in the ICA specimens obtained by endarterectomy. Conclusions We observed a significant association between the AA genotype of rs2107595 with the advanced carotid artery disease in our Slovenian cohort, indicating that this polymorphism may be a genetic risk factor for ICA atherosclerosis.

Histone deacetylase 9 (HDAC9) plays an important role in transcriptional regulation, cell cycle progression and developmental events; moreover, it has been investigated as a candidate gene in a number of conditions, including the onset and progression of atherosclerosis. We hypothesized that the rs2107595 HDAC9 gene polymorphism may be associated with advanced carotid artery disease in a Slovenian cohort. We also investigated the effect of this polymorphism on HDAC9 receptor expression in the internal carotid artery (ICA) specimens obtained by endarterectomy. This case-control study enrolled 619 unrelated Slovenian patients: 311 patients with ICA stenosis > 75% as the study group and 308 patients with ICA stenosis < 50% as the control group. Patient laboratory and clinical data were obtained from the medical records. The rs2107595 polymorphisms were genotyped using TaqMan SNP Genotyping assay. HDAC9 expression was assessed by immunohistochemistry in 30 ICA specimens from patients with ICA atherosclerosis > 75%, and the numerical areal density of HDAC9 positive cells was calculated. The occurrence of advanced ICA atherosclerosis in the Slovenian cohort was 3.81 times higher in the codominant genetic model (OR = 3.81, 95%CI = 1.06–13.77, p = 0.04), and 3.10 times higher in the recessive genetic model (OR = 3.10, 95%CI = 1.16–8.27, p = 0.02). In addition, the A allele of rs2107595 was associated with increased HDAC9 expression in the ICA specimens obtained by endarterectomy. We observed a significant association between the AA genotype of rs2107595 with the advanced carotid artery disease in our Slovenian cohort, indicating that this polymorphism may be a genetic risk factor for ICA atherosclerosis.

We profiled nine pure clear cell carcinomas of the breast using massively parallel DNA and RNA sequencing (NGS), in situ hybridization (ISH), and immunohistochemistry (IHC). All cases were primary mammary clear cell carcinomas that were diagnosed in female patients (mean age: 53.4 years; range: 31‐69 years). Based on our findings, we conclude that the majority of clear cell carcinomas are ER/PR positive and consequently amenable to anti‐ER treatment modalities. A subset of clear cell carcinomas also harbored alterations in PIK3CA/PTEN/AKT pathway, particularly PTEN, indicating a potential benefit of PI3K/Akt/mTOR inhibitors. The status of I‐O biomarkers in clear cell carcinomas indicates a limited therapeutic benefit of immune checkpoint inhibitors (against PD‐1/PD‐L1).

Abstract Background We previously investigated the association between 5 “first-generation” measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Motivated by (approximate) dynamic programming and model predictive control problems, we analyse the stability of deterministic nonlinear discrete-time systems whose inputs minimize a discounted finite-horizon cost. We assume that the system satisfies stabilizability and detectability properties with respect to the stage cost. Then, a Lyapunov function for the closed-loop system is constructed and a uniform semiglobal stability property is ensured, where the adjustable parameters are both the discount factor and the horizon length, which corresponds to the number of iterations for dynamic programming algorithms like value iteration. Stronger stability properties such as global exponential stability are also provided by strengthening the initial assumptions. We give bounds on the discount factor and the horizon length under which stability holds and we provide conditions under which these are less conservative than the bounds of the literature for discounted infinite-horizon cost and undiscounted finite-horizon costs, respectively. In addition, we provide new relationships between the optimal value functions of the discounted, undiscounted, infinite-horizon and finite-horizon costs respectively, which are very different from those available in the approximate dynamic programming literature. These relationships rely on assumptions that are more likely to be satisfied in a control context. Finally, we investigate stability when only a near-optimal sequence of inputs for the discounted finite-horizon cost is available, covering approximate value iteration as a particular case.