Demand forecasting: a case study in the food industry

The use of forecasting methods is nowadays regarded as a business ally since it supports both the operational and the strategic decision-making processes. This paper is based on a research project aiming the development of demand forecasting models for a company (designated here by PR) that operates in the food business, more specifically in the delicatessen segment. In particular, we focused on demand forecasting models that can serve as a tool to support production planning and inventory management at the company. The analysis of the company’s operations led to the development of a new demand forecasting tool based on a combination of forecasts, which is now being used and tested by the company.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/201

A multi-dimensional investigation of self-regulated learning in a blended classroom context : a case study on eLDa MOOC

Online systems such as massive open online courses (MOOCs) are new innovative learning technology in education. With the proliferation of MOOC systems, little has been mentioned about blended MOOC system and how it enhances students’ performance. Blended classroom is a form of learning taking place between two different activities of which one is online and the other is traditional teaching method using bricks and mortal classroom settings. This study reveals the effectiveness of blended classroom teaching for an undergraduate course. The module was embedded in an eLDa MOOC platform, which is a platform for delivery computing concepts, and Python programme course. This research aims to investigate students’ perceptions of self-regulated learning (SRL) habits. A multi-dimensional survey was designed to evaluate each aspect of SRL skills, motivation and attaining better grades within the course. This research analysis explores (a) cognitive process of students improving their self-regulated learning skills (b) potential of students’ preparedness and motivation to engage with the course content in a blended context (c) potential difference in addressing the relation among the methods of engagement and achievement in their weekly assessment results. The research applied an online self-regulated learning questionnaire (OSLQ) as the instrument for measuring the self-regulated learning skills of the students in the learning platform environment. In relation to developing a revised OSLQ to address the use of the instrument to measure self-regulated learning in an online blended classroom context. Data collection process was conducted on a sample of first year undergraduate students who took a seminar module via a blended course format. The results indicate the level of self-regulated learning explored from the measure of the self-regulation in the blended learning environment in this study

Global and decomposition evolutionary support vector machine approaches for time series forecasting

Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN.The authors wish to thank Ramon Sagarna for introducing the subject of EDA. The work of P. Cortez was supported by FEDER (program COMPETE and FCT) under project FCOMP-01-0124-FEDER-022674

K70Q Adds High-Level Tenofovir Resistance to “Q151M Complex” HIV Reverse Transcriptase through the Enhanced Discrimination Mechanism

HIV-1 carrying the “Q151M complex” reverse transcriptase (RT) mutations (A62V/V75I/F77L/F116Y/Q151M, or Q151Mc) is resistant to many FDA-approved nucleoside RT inhibitors (NRTIs), but has been considered susceptible to tenofovir disoproxil fumarate (TFV-DF or TDF). We have isolated from a TFV-DF-treated HIV patient a Q151Mc-containing clinical isolate with high phenotypic resistance to TFV-DF. Analysis of the genotypic and phenotypic testing over the course of this patient's therapy lead us to hypothesize that TFV-DF resistance emerged upon appearance of the previously unreported K70Q mutation in the Q151Mc background. Virological analysis showed that HIV with only K70Q was not significantly resistant to TFV-DF. However, addition of K70Q to the Q151Mc background significantly enhanced resistance to several approved NRTIs, and also resulted in high-level (10-fold) resistance to TFV-DF. Biochemical experiments established that the increased resistance to tenofovir is not the result of enhanced excision, as K70Q/Q151Mc RT exhibited diminished, rather than enhanced ATP-based primer unblocking activity. Pre-steady state kinetic analysis of the recombinant enzymes demonstrated that addition of the K70Q mutation selectively decreases the binding of tenofovir-diphosphate (TFV-DP), resulting in reduced incorporation of TFV into the nascent DNA chain. Molecular dynamics simulations suggest that changes in the hydrogen bonding pattern in the polymerase active site of K70Q/Q151Mc RT may contribute to the observed changes in binding and incorporation of TFV-DP. The novel pattern of TFV-resistance may help adjust therapeutic strategies for NRTI-experienced patients with multi-drug resistant (MDR) mutations

Theory of disk accretion onto supermassive black holes

Accretion onto supermassive black holes produces both the dramatic phenomena associated with active galactic nuclei and the underwhelming displays seen in the Galactic Center and most other nearby galaxies. I review selected aspects of the current theoretical understanding of black hole accretion, emphasizing the role of magnetohydrodynamic turbulence and gravitational instabilities in driving the actual accretion and the importance of the efficacy of cooling in determining the structure and observational appearance of the accretion flow. Ongoing investigations into the dynamics of the plunging region, the origin of variability in the accretion process, and the evolution of warped, twisted, or eccentric disks are summarized.Comment: Mostly introductory review, to appear in "Supermassive black holes in the distant Universe", ed. A.J. Barger, Kluwer Academic Publishers, in pres

Global heat balance and heat uptake in potential temperature coordinates

The representation of ocean heat uptake in Simple Climate Models used for policy advice on climate change mitigation strategies is often based on variants of the one-dimensional Vertical Advection/Diffusion equation (VAD) for some averaged form of potential temperature. In such models, the effective advection and turbulent diffusion are usually tuned to emulate the behaviour of a given target climate model. However, because the statistical nature of such a ``behavioural" calibration usually obscures the exact dependence of the effective diffusion and advection on the actual physical processes responsible for ocean heat uptake, it is difficult to understand its limitations and how to go about improving VADs. This paper proposes a physical calibration of the VAD that aims to provide explicit traceability of effective diffusion and advection to the processes responsible for ocean heat uptake. This construction relies on the coarse-graining of the full three-dimensional advection diffusion for potential temperature using potential temperature coordinates. The main advantage of this formulation is that the temporal evolution of the reference temperature profile is entirely due to the competition between effective diffusivity that is always positive definite, and the water mass transformation taking place at the surface, as in classical water mass analyses literature. These quantities are evaluated in numerical simulations of present day climate and global warming experiments. In this framework, the heat uptake in the global warming experiment is attributed to the increase of surface heat flux at low latitudes, its decrease at high latitudes and to the redistribution of heat toward cold temperatures made by diffusive flux

State–Space Forecasting of Schistosoma haematobium Time-Series in Niono, Mali

Adequate forecasting and early warning systems are based upon observations of human behavior, population, disease time-series, climate, environment, and/or a combination thereof, whichever option best compromises among realism, feasibility, robustness, and parsimony. Fully automatic and user-friendly state–space forecasting frameworks, incorporating myriad options (e.g., expert opinion, univariate, multivariate, and spatial-temporal), could considerably enhance disease control and hazard mitigation efforts in regions where vulnerability to neglected tropical diseases is pervasive and statistical expertise is scarce. The operational simplicity, generality, and flexibility of state–space frameworks, encapsulating multiple methods, could conveniently allow for 1) unsupervised model selection without disease-specific methodological tailoring, 2) on-line adaptation to disease time-series fluctuations, and 3) automatic switches between distinct forecasting methods as new time-series perturbations dictate. In this investigation, a univariate state–space framework with the aforementioned properties was successfully applied to the Schistosoma haematobium time-series for the district of Niono, Mali, to automatically generate contemporaneous on-line forecasts and hence, providing a basis for local re-organization and strengthening public health programs in this and potentially other Sahelian districts

Susceptibility of the human retrovirus XMRV to antiretroviral inhibitors

<p>Abstract</p> <p>Background</p> <p>XMRV (xenotropic murine leukemia virus-related virus) is the first known example of an exogenous gammaretrovirus that can infect humans. A limited number of reports suggest that XMRV is intrinsically resistant to many of the antiretroviral drugs used to treat HIV-1 infection, but is sensitive to a small subset of these inhibitors. In the present study, we used a novel marker transfer assay to directly compare the antiviral drug sensitivities of XMRV and HIV-1 under identical conditions in the same host cell type.</p> <p>Results</p> <p>We extend the findings of previous studies by showing that, in addition to AZT and tenofovir, XMRV and HIV-1 are equally sensitive to AZddA (3'-azido-2',3'-dideoxyadenosine), AZddG (3'-azido-2',3'-dideoxyguanosine) and adefovir. These results indicate that specific 3'-azido or acyclic nucleoside analog inhibitors of HIV-1 reverse transcriptase (RT) also block XMRV infection with comparable efficacy <it>in vitro</it>. Our data confirm that XMRV is highly resistant to the non-nucleoside RT inhibitors nevirapine and efavirenz and to inhibitors of HIV-1 protease. In addition, we show that the integrase inhibitors raltegravir and elvitegravir are active against XMRV, with EC₅₀values in the nanomolar range.</p> <p>Conclusions</p> <p>Our analysis demonstrates that XMRV exhibits a distinct pattern of nucleoside analog susceptibility that correlates with the structure of the pseudosugar moiety and that XMRV is sensitive to a broader range of antiretroviral drugs than has previously been reported. We suggest that the divergent drug sensitivity profiles of XMRV and HIV-1 are partially explained by specific amino acid differences in their respective protease, RT and integrase sequences. Our data provide a basis for choosing specific antiretroviral drugs for clinical studies in XMRV-infected patients.</p