Impact of Integrase Sequences From HIV-1 Subtypes A6/A1 on the In Vitro Potency of Cabotegravir or Rilpivirine

The FLAIR study demonstrated noninferiority of monthly long-acting cabotegravir + rilpivirine vs daily oral dolutegravir/abacavir/lamivudine for maintaining virologic suppression. Three participants who received long-acting therapy had confirmed virologic failure (CVF) at Week 48, and all had HIV-1 that was originally classified as subtype A1 and contained the baseline integrase polymorphism L74I; updated classification algorithms reclassified all 3 as HIV-1 subtype A6. Retrospectively, the impact of L74I on in vitro sensitivity and durability of response to cabotegravir in HIV-1 subtype B and A6 backgrounds was studied. Site-directed L74I and mutations observed in participants with CVF were generated in HIV-1 subtype B and a consensus integrase derived from 3 subtype A6 CVF baseline sequences. Rilpivirine susceptibility was assessed in HIV-1 subtype B and A1 containing reverse transcriptase mutations observed in participants with CVF. HIV-1 subtype B L74I and L74I/G140R mutants and HIV-1 subtype A6 I74L and I74/G140R mutants remained susceptible to cabotegravir; L74I/Q148R double mutants exhibited reduced susceptibility in HIV-1 subtypes B and A6 (half maximal effective capacity fold change, 4.4 and 4.1, respectively). Reduced rilpivirine susceptibility was observed across HIV-1 subtypes B and A1 with resistance-associated mutations K101E or E138K (half maximal effective capacity fold change, 2.21 to 3.09). In cabotegravir breakthrough experiments, time to breakthrough was similar between L74 and I74 viruses across HIV-1 subtypes B and A6; Q148R was selected at low cabotegravir concentrations. Therefore, the L74I integrase polymorphism did not differentially impact in vitro sensitivity to cabotegravir across HIV-1 subtype B and A6 integrase genes (ClinicalTrials.gov identifier: NCT02938520).

Pengembangan Penataan Perparkiran Universitas Hasanuddin Di Fakultas Teknik, Fakultas MIPA Dan Fakultas Farmasi

Meningkatnya pemilikan kendaraan bermotor civitas akademika Universitas Hasanuddin mengakibatkan peningkatan permintaan fasilitas parkir mengingat fasilitas parkir merupakan bagian yang tak terpisahkan dari sistem transportasi sehingga menimbulkan kesemrawutan perparkiran seperti yang dilihat pada area perparkiran Fakultas Teknik, Fakultas MIPA dan Fakultas Farmasi. Tujuan penelitian ini, yaitu menyusun konsep penataan ruang parkir yang dapat menjelaskan kapasitas ruang parkir efektif ditinjau berdasarkan tata layout bangunan dan kebutuhan parkir Fakultas Teknik, Fakultas MIPA, dan Fakultas Farmasi di Universitas Hasanuddin Tamalanrea, Makassar menggunakan metode penelitian deskriptif kuantitatif dalam menganalisis karakteristik parkir untuk mengetahui kapasitas parkir, volume parkir, akumulasi parkir, tingkat penggunaan parkir, dan kebutuhan parkir kendaraan roda dua dan roda empat yang keluar-masuk area parkir selama lima hari kerja mulai pukul 06.30 sampai dengan pukul 17.30 dengan hasil penelitian menunjukkan bahwa penyusunan sebuah konsep penataan ruang parkir efektif di lingkungan tiga fakultas di Universitas Hasanuddin (Teknik, MIPA, dan Farmasi) berhasil disusun dengan merekomendasikan penggabungan beberapa lahan parkir menjadi satu area parkir kendaraan roda empat dan sentralisasi parkiran kendaraan beroda dua. The increasing number of vehicles ownership among the Hasanuddin University academic community resulted in increased demand for parking facilities; considering it is an integral part of the transportation system, the steep demands causing parking disorganize as seen in the parking facilities of the Faculty of Engineering, Faculty of Science and Faculty of Pharmacy. This study attempts to propose a parking spaces rearrangement that could describe the effective capacity of parking area from the standpoint of the building layout planning and the parking spaces needs of the Faculty of Engineering, Faculty of Science and Faculty of Pharmacy at the University of Hasanuddin Tamalanrea Makassar. Using descriptive quantitative research method in analyzing the characteristics of parking to determine the capacity of parking, parking volume, accumulated parking, parking usage levels, and the need for parking of the two-wheeled and four-wheeled vehicles entered and exited the parking area for five working days; starting at 06:30 AM until 17.30 PM, resulting a concept of an effective parking spaces rearrangement that encompassing the three faculty of Hasanuddin University (faculty of Engineering, Sciences, and Pharmacy) by recommending the incorporation of several of the parking lot into a four-wheeled vehicle parking areas and centralized parking facilities for two-wheeled vehicles.

Enhancing Gas Injection Compressors Performance by Lateral Thinking Resulting in 0.62 Million Barrels Oil Per Year Additional Production Capacity at Zero Cost

The Fourth Industrial Revolution (4.0) in Oil & Gas Industry creates a dynamic landscape where Operational Excellence (OE) strives for stability, quality, and efficiency while continuing to serve an increasingly demanding customer. Operational excellence is a journey, not a sole destination. Abu Dhabi National Oil Company (ADNOC) Onshore, one of the South East Fields, oil production capacity was constrained due to the limitation of associated gas handling capacity of the compressors. Gas flow towards the compressor was not steady due to natural flowing wells non-steady behavior and this disturbance cannot be removed from the system. The situation was quite complicated. In order to produce oil, associated gas must be handled to avoid flaring. It was more than a challenge to increase the compressors effective capacity without any hardware modification. Since flaring is not permitted in ADNOC and running of huge capacity standby compressor was not economically viable, therefore, Field Operations by lateral thinking transformed this challenging situation into an opportunity and enhanced compressor effective capacity by expanding its operating envelope to handle additional gas. One innovative solution proposed by Field Operations was to expand the pressure-operating envelope of the machine to withstand high pressures without tripping. The idea was to increase the machine throughput by elevating the machine high-pressure trip set point along with Pressure Safety Valve (PSV) set point elevation. This submission shares success story of an oil field Operations in house efforts to enhance the gas injection compressor effective capacity by 600 MSCFD which subsequently increased the oil production capacity by 1700 bopd or 0.62 million barrels oil per year by Operational Excellence. Operational Excellence played its role with a value improvement objective. Rather than replacing successful practices and programs, Operational Excellence knitted them into a larger, fully integrated tapestry woven to increase value produced within the overall business strategy which is very evident in this scenario. This case study is blend of Operations Excellence and innovation representing Management support to employee to solve complex problems. Such support is always beneficial for the company and employee. Management of change process for followed to study, analyze and implement the idea.

Organisational agility, environmental knowledge and green product success

Purpose The purpose of this study is to analyse the effect of organisational agility on environmental knowledge as an instrument for the successful development of eco-innovation in products. Design/methodology/approach This study used a cross-sectional design to collect data on the study variables from a sample of 184 Spanish manufacturing organisations. Structural equations with partial least squares were used to test the hypotheses. Findings Organisational agility is significantly linked to internal and external environmental knowledge. The results of this study highlight the effect of external knowledge on the success of eco-innovation. Internal environmental knowledge positively moderates the effect of external knowledge on the success of green products. Research limitations/implications Based on the dynamic capabilities approach, a theoretical model has been proposed in which organisational agility is configured as an effective capacity for the development of environmental knowledge. The results confirm this relationship and indicate that, although internal environmental knowledge is not decisive in developing new green products, it does enhance the effect of external knowledge on the success of eco-innovation. Practical implications Innovative companies must implement organisational agility practices that promote environmental knowledge for the success of new green products. They should also promote both external and internal knowledge. Originality/value This study addresses the little explored area of the relationship between organisational agility and the successful development of new green products. The inherent particularities of eco-innovation prompt the need for further studies on the creation of specific knowledge for its promotion. This study concludes that adopting agile practices enables key environmental knowledge for this type of innovation to be created. Additionally, it explores the tensions arising from the dichotomy between internal and external knowledge, with scarce resources allocated to the most effective source. Although both types of knowledge seem to be equally relevant, external knowledge plays a more significant role in the case of eco-innovation. A final contribution of this study is the finding that internal knowledge can further enhance the effect of external knowledge on the development of successful green products.

Effective Capacity Analysis of NOMA Networks with Short Packets

Low latency and a massive connection have become the requirements of energy internet wireless communication. Effective capacity analysis of non-orthogonal multiple access (NOMA) networks with short packets is of vital importance in energy internet communication planning and design. Low-latency communications are one of the main application scenarios in next-generation wireless networks. This paper focuses on the effective capacity of NOMA networks, where the finite blocklength, delay exponent, and transmission error probability are taken into account. New exact and asymptotic expressions of effective capacities are derived for arbitrarily ordered users with a finite blocklength. Based on the analytical results, the high Signal-to-Noise Ratio slopes of effective capacity in NOMA networks are carefully attained. The numerical results validate that (a) non-orthogonal users are capable of obtaining a larger effective capacity when the blocklength decreases, and that (b), as the value of the error probability and delay exponent increases, the effective capacity of non-orthogonal users worsens.

Effective capacity analysis of reconfigurable intelligent surfaces aided NOMA network

The future sixth generation (6G) is going to face the significant challenges of massive connections and green communication. Recently, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) have been proposed as two key technologies to solve the above problems. Motivated by this fact, we consider a downlink RIS-aided NOMA system, where the source aims to communicate with the two NOMA users via RIS. Considering future network supporting real-time service, we investigate the system performance with the view of effective capacity (EC), which is an important evaluation metric of delay sensitive systems. Specifically, we derive the analytical expressions of the EC of the near and far users. To obtain more useful insights, we deduce the analytical approximation expressions of the EC in the low signal-to-noise-ratio approximation by utilizing Taylor expansion. Moreover, we provide the results of orthogonal multiple access (OMA) for the purpose of comparison. It is found that (1) The number of RIS components and the transmission power of the source have important effects on the performance of the considered system; (2) Compared with OMA, NOMA system has higher EC due to the short transmission time.

Course Scheduling Under Sudden Scarcity: Applications to Pandemic Planning

Problem definition: Physical distancing requirements during the COVID-19 pandemic have dramatically reduced the effective capacity of university campuses. Under these conditions, we examine how to make the most of newly scarce resources in the related problems of curriculum planning and course timetabling. Academic/practical relevance: We propose a unified model for university course scheduling problems under a two-stage framework and draw parallels between component problems while showing how to accommodate individual specifics. During the pandemic, our models were critical to measuring the impact of several innovative proposals, including expanding the academic calendar, teaching across multiple rooms, and rotating student attendance through the week and school year. Methodology: We use integer optimization combined with enrollment data from thousands of past students. Our models scale to thousands of individual students enrolled in hundreds of courses. Results: We projected that if Massachusetts Institute of Technology moved from its usual two-semester calendar to a three-semester calendar, with each student attending two semesters in person, more than 90% of student course demand could be satisfied on campus without increasing faculty workloads. For the Sloan School of Management, we produced a new schedule that was implemented in fall 2020. The schedule allowed half of Sloan courses to include an in-person component while adhering to safety guidelines. Despite a fourfold reduction in classroom capacity, it afforded two thirds of Sloan students the opportunity for in-person learning in at least half their courses. Managerial implications: Integer optimization can enable decision making at a large scale in a domain that is usually managed manually by university administrators. Our models, although inspired by the pandemic, are generic and could apply to any scheduling problem under severe capacity constraints.

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

The Internet of Things (IoT) facilitates physical things to detect, interact, and execute activities on-demand, enabling a variety of applications such as smart homes and smart cities. However, it also creates many potential risks related to data security and privacy vulnerabilities on the physical layer of cloud-based Internet of Things (IoT) networks. These can include different types of physical attacks such as interference, eavesdropping, and jamming. As a result, quality-of-service (QoS) provisioning gets difficult for cloud-based IoT. This paper investigates the statistical QoS provisioning of a four-node cloud-based IoT network under security, reliability, and latency constraints by relying on the effective capacity model to offer enhanced QoS for IoT networks. Alice and Bob are legitimate nodes trying to communicate with secrecy in the considered scenario, while an eavesdropper Eve overhears their communication. Meanwhile, a friendly jammer, which emits artificial noise, is used to degrade the wiretap channel. By taking advantage of their multiple antennas, Alice implements transmit antenna selection, while Bob and Eve perform maximum-ratio combining. We further assume that Bob decodes the artificial noise perfectly and thus removes its contribution by implementing perfect successive interference cancellation. A closed-form expression for an alternative formulation of the outage probability, conditioned upon the successful transmission of a message, is obtained by considering adaptive rate allocation in an ON-OFF transmission. The data arriving at Alice’s buffer are modeled by considering four different Markov sources to describe different IoT traffic patterns. Then, the problem of secure throughput maximization is addressed through particle swarm optimization by considering the security, latency, and reliability constraints. Our results evidence the considerable improvements on the delay violation probability by increasing the number of antennas at Bob under strict buffer constraints.

Addressing IT Capacity Management Concerns Using Machine Learning Techniques

The digitization of various industries is emerging from and being supported by the Information Technology (IT) industry. However, bringing about the practical implementation of the fourth industrial revolution will require different fields of IT to undergo their own transformations. One of the research fields that draws a lot of attention nowadays is machine learning and its application in different areas. Therefore, in this paper, we present an analysis on the applicability of various machine learning techniques to address different problems in the field of capacity management for Commercial-off-the-shelf enterprise applications. Our investigation of the selected machine learning techniques is based on real monitoring data from over 18,000 SAP applications and database instances that are hosted on more than 16,000 different physical servers. These data are used to train various performance models, such as support vector machines with different kernels, random forests, and AdaBoost, for standard business functions. Boosted trees achieve sufficient accuracy to predict mean response times for ten frequently used transactions. To evaluate the suggested models, we applied them successfully to address different concerns in the context of capacity management. The evaluation includes multiple scenarios in the fields of server sizing, load testing, and server consolidation, with the objective to identify cost-effective designs. Based on the same monitoring data, we also present an anomaly detection scenario. In this scenario, we aim to demonstrate the use of machine learning techniques on historical data to detect possible performance anomalies for a suggested design or even predict possible anomalies in future scenarios. Results strongly emphasize the need to integrate monitoring data from standardized business applications to allow for novel and cost-effective capacity management service offerings.