Technical Portfolio Research Articles

Growing our Technical Portfolio through Cooperation with Other IEEE Entities

The IEEE Communications Society (ComSoc) is the leading global professional organization for creating advanced communications technologies and services, covering all aspects of communications from the theoretical foundation of data transmission and signal processing up to the communication infrastructures for distributed applications, services, their communication networks, and management. To continue advancing communications technologies and markets, it is important for ComSoc to evolve its technological portfolio by continuously supporting new activities that will provide significant benefit to IEEE members, the public, and the technical community. In particular, ComSoc will address those technologies and application areas that stretch across the scope of multiple IEEE operating units (i.e., Societies and Councils). In this issue of the President's Page, I am pleased to introduce Heiner Stüttgen, the Chair of Technology, Evolution, and Initiatives Standing Committee (TE&I) for 2022–2023, to share with you the details.

Building an efficient portfolio by using the weighted moving average in the light of the global pandemic (COVID19) (An applied study in the Iraq stock market)

The research aims to study how to build an efficient portfolio by using the weighted moving average in the light of the global pandemic and compare it with the efficient portfolio for the previous period before the global pandemic. The rapid spread of Corona virus (COVID-19) is having major impacts on the financial markets around the world. However, the global pandemic caused a great risk, which led the investors to suffer huge losses in a very short period of time, in addition, to the global Covid-19 pandemic, the economic recession and the drop in oil prices led to a drop in the share prices of companies, as well as most of the companies listed in the Iraq Stock Market (Iraq Stock Exchange), trading in their shares decreased after the appearance of the first case in Iraq in 25/2/2019. The weighted moving average is one of the technical analysis tools, and this technical and mathematical tool has been used to build a portfolio consists of (24 companies). The first ten companies that have the highest weighted moving average have been selected and the research period is divided into the period before the global pandemic which started from 25/2/2019 to 24/2/2020 and the concurrent period of the global pandemic from 25/2/2020 to 2/24/2021 and the researcher used the statistical program [Microsoft Excel 10]. It has been concluded from the research that the Sharpe ratio for the technical portfolio for the concurrent period of the global pandemic was higher than the Sharpe ratio for the previous technical portfolio before the global pandemic, although the Sharpe ratio for both portfolios is negative, meaning that the returns of the portfolio are less than the risk-free return, but the Sharpe ratio for the technical portfolio for the concurrent period is better than the technical portfolio for the previous period, which confirms that the decrease in the number of trading sessions and the volume of trading have affected the performance of the investment portfolio, the smaller the number of trading volume, the better the performance of the portfolio. The researcher recommends with using other technical and mathematical tools to build an efficient investment portfolio in the light of the global pandemic.

A57 An evolutionary framework to guide the hunt for human dsDNA viruses

It is becoming increasingly obvious that we only know a fraction of the human virome. The development of next-generation sequencing (NGS) technologies has dramatically increased our ability to hunt viruses. Yet, the small genomes and low copy numbers characteristic of most viruses make undirected (shotgun) hunts a relatively inefficient strategy. Here, we propose to speed-up the rate of double-stranded DNA (dsDNA) virus discovery by combining NGS with evolutionary thinking. dsDNA viruses are thought to have co-diverged with their hosts. As this applies to the hominine lineages (gorillas, humans, chimpanzees, and bonobos), it is theoretically possible to estimate the phylogenetic position of cryptic human viruses by identifying co-divergent viral lineages infecting non-human hominines. Where these lineages do not comprise a human-infecting counterpart, a yet-unknown human virus may be hiding. The first phase of this project will consist in the high-throughput characterization of dsDNA viruses (herpesviruses, papillomaviruses, and polyomaviruses) infecting wild gorillas, chimpanzees, and bonobos. For this, we will use an exhaustive collection of fecal samples (in terms of hominine species/sub-species diversity) and apply a discovery strategy combining in-solution capture and NGS. This strategy has been developed in the ancient DNA field but has a very broad applicability; it will constitute a nice addendum to the institute technical portfolio. Thanks to the massive amount of information collected, we will be able to reconstruct the evolutionary history of many dsDNA virus lineages and to identify those where a human virus would be expected but is still unknown. This will pave the way to the second phase of the project which will consist in a pre-oriented dsDNA human virus hunt based on the use of specific PCR systems implemented in multiplex. We expect that this project will generate an unprecedented amount of data on the processes at play along dsDNA virus evolution (co-divergence versus cross-species transmission), help determine the directionality, frequency, and timing of cross-species transmission events between hominines and unveil the existence of yet-to-be-discovered human viruses.

Extent of Resection in Newly Diagnosed Glioblastoma: Impact of a Specialized Neuro-Oncology Care Center

Treatment of glioblastoma (GBM) consists of microsurgical resection followed by concomitant radiochemotherapy and adjuvant chemotherapy. The best outcome regarding progression free (PFS) and overall survival (OS) is achieved by maximal resection. The foundation of a specialized neuro-oncology care center (NOC) has enabled the implementation of a large technical portfolio including functional imaging, awake craniotomy, PET scanning, fluorescence-guided resection, and integrated postsurgical therapy. This study analyzed whether the technically improved neurosurgical treatment structure yields a higher rate of complete resection, thus ultimately improving patient outcome. Patients and methods: The study included 149 patients treated surgically for newly diagnosed GBM. The neurological performance score (NPS) and the Karnofsky performance score (KPS) were measured before and after resection. The extent of resection (EOR) was volumetrically quantified. Patients were stratified into two subcohorts: treated before (A) and after (B) the foundation of the Regensburg NOC. The EOR and the PFS and OS were evaluated. Results: Prognostic factors for PFS and OS were age, preoperative KPS, O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, isocitrate dehydrogenase 1 (IDH1) mutation status and EOR. Patients with volumetrically defined complete resection had significantly better PFS (9.4 vs. 7.8 months; p = 0.042) and OS (18.4 vs. 14.5 months; p = 0.005) than patients with incomplete resection. The frequency of transient or permanent postoperative neurological deficits was not higher after complete resection in both subcohorts. The frequency of complete resection was significantly higher in subcohort B than in subcohort A (68.2% vs. 34.8%; p = 0.007). Accordingly, subcohort B showed significantly longer PFS (8.6 vs. 7.5 months; p = 0.010) and OS (18.7 vs. 12.4 months; p = 0.001). Multivariate Cox regression analysis showed complete resection, age, preoperative KPS, and MGMT promoter status as independent prognostic factors for PFS and OS. Our data show a higher frequency of complete resection in patients with GBM after the establishment of a series of technical developments that resulted in significantly better PFS and OS without increasing surgery-related morbidity.

Dynamic portfolio management under competing representations

PurposeTo solve the multi‐period portfolio management problem under transactions costs.Design/methodology/approachWe apply a recently designed super genetic hybrid algorithm (SuperGHA) – an integrated optimisation system for simultaneous parametric search and non‐linear optimisation – to a recursive portfolio management decision support system (SHAREX). The parametric search machine is implemented as a genetic superstructure, producing tentative parameter vectors that control the ultimate optimisation process.FindingsSHAREX seems to outperform the buy and hold‐strategy on the Finnish stock market. The potential of a technical portfolio system is best exploitable under favorable market conditions.Originality/valueA number of robust engines for matrix algebra, mathematical programming and numerical calculus have been integrated with SuperGHA. The engines expand its scope as a general‐purpose algorithm for mathematical programming.