Multi–stage process for chemotherapy scheduling and effective capacity determination

A novel solution approach is developed for the scheduling of chemotherapy sessions at cancer treatment centers. The problem is divided into two subproblems determining the day (interday scheduling) and the time slots (intraday scheduling), respectively. The interday subproblem is solved by a model that allows for effective treatment center capacity choices while the intraday subproblem is addressed using two optimization models. New patient arrivals and treatment protocols specifying the latest starting date and session spacing are sources of uncertainty. Unlike other existing approaches, the proposed method incorporates the concept of effective treatment capacity which facilitates the interaction between the interday and intraday subproblems allowing them to be solved sequentially and iteratively to thus achieve much more resource-efficient solutions. A case study using real data from a Chilean cancer center to conduct comparative simulations of its manual scheduling methods and the proposed methodology found that the latter almost always performed better, often significantly so, on makespan, resource utilization, overtime, and patient diversion metrics.     

Biocathodic nitrous oxide removal in bioelectrochemical systems

Anthropogenic nitrous oxide (N(2)O) emissions represent up to 40% of the global N(2)O emission and are constantly increasing. Mitigation of these emissions is warranted since N(2)O is a strong greenhouse gas and important ozone-depleting compound. Until now, only physicochemical technologies have been applied to mitigate point sources of N(2)O, and no biological treatment technology has been developed so far. In this study, a bioelectrochemical system (BES) with an autotrophic denitrifying biocathode was considered for the removal of N(2)O. The high N(2)O removal rates obtained ranged between 0.76 and 1.83 kg N m(-3) net cathodic compartment (NCC) d(-1) and were proportional to the current production, resulting in cathodic coulombic efficiencies near 100%. Furthermore, our experiments suggested the active involvement of microorganisms as the catalyst for the reduction of N(2)O to N(2), and the optimal cathode potential ranged from -200 to 0 mV vs standard hydrogen electrode (SHE) in order to obtain high conversion rates. Successful operation of the system for more than 115 days with N(2)O as the sole cathodic electron acceptor strongly indicated that N(2)O respiration yielded enough energy to maintain the biological process. To our knowledge, this study provides for the first time proof of concept of biocathodic N(2)O removal at long-term without the need for high temperatures and expensive catalysts.     

Gravel deposits survey in south central Brazil

This paper deals with the influence of discontinuous particle-size distribution on the basic properties of asphaltic concrete. New particle-size curves were obtained by removing the fine, medium and coarse material connected with one or two successive sieves. Consequently the following characteristics have been examined: stability, deformation and voids of compacted asphaltic concrete according to the Greek specifications. The results showed that a high degree of flexibility capable of removing part of the aggregate exists. In that case the values of tests present positive or negative results which are also influenced by the existing proportion of bitumen. Thus a revision of specifications concerned with particle-size distribution might be possible.     

Enhancing the performance of TCP over Wi-Fi power saving mechanisms

The Wi-Fi technology is quickly being adopted by new types of devices that pose stringent requirements in terms of energy efficiency. In order to address these requirements the IEEE 802.11 group developed in the recent years several power saving protocols, that are today widely used among devices like smartphones. In this paper we study, by means of analysis and simulation, the effect that these power saving protocols have on the performance/energy trade-off experienced by long lived TCP traffic. Our study unveils that the efficiency of Wi-Fi power saving protocols critically depends on the bottleneck bandwidth experienced by a TCP connection. Based on the obtained insights, we design and evaluate a novel algorithm, BA-TA, which runs in a Wi-Fi station, does not require any modification to existing 802.11 standards, and using only information available at layer two, improves the performance/energy trade off of long lived TCP connections, whilst also exhibiting a notable performance with Web traffic and TCP Streaming.     

Characteristics and sensory assessment of extra virgin olive oils produced in two different zones of Brazil

The Brazilian olive oil production has been growing in recent decades and largest plantations are on two different zones, from Serra da Mantiqueira (states of Minas Gerais and São Paulo) and Campanha Gaúcha (state of Rio Grande do Sul). The total planted area, in 2022, reached approximately 6500 hectares. The aim of the present study was to characterize the sensory and analytical parameters of extra virgin olive oils (EVOO) from Southwestern (Serra da Mantiqueira) and Southern (Campanha Gaúcha) Brazil regions. Twenty-two EVOO samples were obtained from different cultivars of unlike regions. Quality parameters, oxidative stability, phenolic compounds ortho-diphenols and fatty acids were analyzed and relationships with olive variety or region. From the chemical perspective, the EVOO exhibited all parameters within the necessary to be qualified as extra virgin, according to international standard definitions. All samples showed a good quality of sensory perceptions and a high level of polyphenols, which are varied among samples but was more intense in Campanha Gaúcha olive oils.     

On evaluating stream learning algorithms

Most streaming decision models evolve continuously over time, run in resource-aware environments, and detect and react to changes in the environment generating data. One important issue, not yet convincingly addressed, is the design of experimental work to evaluate and compare decision models that evolve over time. This paper proposes a general framework for assessing predictive stream learning algorithms. We defend the use of prequential error with forgetting mechanisms to provide reliable error estimators. We prove that, in stationary data and for consistent learning algorithms, the holdout estimator, the prequential error and the prequential error estimated over a sliding window or using fading factors, all converge to the Bayes error. The use of prequential error with forgetting mechanisms reveals to be advantageous in assessing performance and in comparing stream learning algorithms. It is also worthwhile to use the proposed methods for hypothesis testing and for change detection. In a set of experiments in drift scenarios, we evaluate the ability of a standard change detection algorithm to detect change using three prequential error estimators. These experiments point out that the use of forgetting mechanisms (sliding windows or fading factors) are required for fast and efficient change detection. In comparison to sliding windows, fading factors are faster and memoryless, both important requirements for streaming applications. Overall, this paper is a contribution to a discussion on best practice for performance assessment when learning is a continuous process, and the decision models are dynamic and evolve over time.     

Scalable Unified Transform Architecture for Advanced Video Coding Embedded Systems

A novel high throughput and scalable unified architecture for the computation of the transform operations in video codecs for advanced standards is presented in this paper. This structure can be used as a hardware accelerator in modern embedded systems to efficiently compute all the two-dimensional 4 × 4 and 2 × 2 transforms of the H.264/AVC standard. Moreover, its highly flexible design and hardware efficiency allows it to be easily scaled in terms of performance and hardware cost to meet the specific requirements of any given video coding application. Experimental results obtained using a Xilinx Virtex-5 FPGA demonstrated the superior performance and hardware efficiency levels provided by the proposed structure, which presents a throughput per unit of area relatively higher than other similar recently published designs targeting the H.264/AVC standard. Such results also showed that, when integrated in a multi-core embedded system, this architecture provides speedup factors of about 120× concerning pure software implementations of the transform algorithms, therefore allowing the computation, in real-time, of all the above mentioned transforms for Ultra High Definition Video (UHDV) sequences (4,320 × 7,680 @ 30 fps).     

Median Filtering: A New Insight

Median filtering (MF) is a canonical image processing operation truly useful in many practical applications. The MF most appealing feature is its resistance to noise and errors in data, but because the method requires window values to be sorted it is computationally expensive. In this work, a new insight into MF capabilities based on the optimal breakdown value (BV) of the median is offered, and it is also shown that the BV-based versions of two of the most popular MF algorithms outperform their corresponding standard versions. A general framework for both the theoretical analysis and comparison of MF algorithms is presented in the process, which will hopefully contribute to a better understanding of the MF many subtle features. The introduced ideas are experimentally tested by using real and synthetic images.