Miracle-dz/UniFAR-FTUs huggingface dataset:
Logistics decisions in descriptive freight transportation models: A review

The objective of this paper is to provide an inventory of approaches to descriptively (as opposed to normatively) model logistics decisions within the context of freight transport modelling. Rather than taking transport modelling frameworks as a starting point, as has been the case in the literature so far, we depart from a framework of logistics decisions. The framework is developed by combining elements of over a dozen existing frameworks from the supply chain management literature. Based on this comprehensive framework, we review freight modelling approaches from the literature. We find that freight modelling can be extended by taking into account previously uncovered areas of logistics decisions, such as those related to marketing or logistics systems forecasting and planning, as well as in areas that are well known from an optimization perspective but not from a descriptive perspective, such as routing and scheduling decisions. We conclude with a systematic listing of such areas, which can be used by researchers and transport modelling practitioners to develop further those transport models that take agent decision making as a starting point.
Simulation-based parameter identification of a reduced model using neural networks

Simulation models are used to study and design real systems in order to optimize their performance. However, the lack of complexity in models, as compared to systems, leads to differences between simulation and actual behavior. Identification of the effective system parameters in the simulation models would reduce the discrepancies between the model and the real system and results in better simulation of system behavior. In this paper, radial basis neural networks are proposed for the identification of the effective parameters of the machine tool feed drive system. Neural networks are first trained with an estimated set of model parameter values and corresponding step responses of the position control loop. After the training period, the response of the model with the identified parameters is compared to the system step position response at different axis positions for validation. An application of neural network to other trajectories is done on a ramp function. The obtained results reveal considerable potential of neural networks in identifying accurately the system parameters and in reducing the discrepancies between experimental test results and the model.
Baseline health, socioeconomic status, and 10-year mortality among older middle-aged Americans: findings from the Health and Retirement Study, 1992 2002.

OBJECTIVE This study analyzed whether socioeconomic status in older middle age continues to be associated with 10-year survival after data are controlled for baseline health status. METHODS We confirmed deaths through 2002 for 9,759 participants in the Health and Retirement Study, aged 51 to 61 in 1992. We used discrete time survival models to examine hazard ratios over 10 years of follow-up. We examined associations of demographic characteristics and socioeconomic status measures before and after adjustment by health status and behavioral risk factors. RESULT The 10-year mortality rate was 10.9%, ranging from 4.7% for respondents reporting excellent health to 35.8% for those reporting poor health at baseline. Lower levels of education, income, and wealth were strongly associated with higher mortality risk after we controlled for just demographic characteristics. After further adjustment for health status and behavioral risk factors, only household income remained significant. DISCUSSION Baseline health by age 50 is an important pathway in the association between midlife socioeconomic status and mortality risk to age 70. The continuing effect of low household income on mortality risk was concentrated among respondents reporting excellent to good health at baseline. Socioeconomic disparities in middle-age health continue to limit disability-free life expectancy at older ages.
B-STATIONARITY CONDITIONS FOR A CLASS OF OPTIMIZATION PROBLEMS GOVERNED BY VARIATIONAL INEQUALITIES OF THE 2 ND KIND

We investigate optimality conditions for optimization problems constrained by a class of variational inequalities of the second kind. Based on a nonsmooth primal-dual reformulation of the governing inequality, the differentiability of the solution map is studied. Directional differentiability is proved both for finite-dimensional and function space problems, under suitable assumptions on the active set. A characterization of B-stationary optimal solutions is obtained thereafter. Finally, based on the obtained first-order information, a trust-region algorithm is proposed for the solution of the optimization problems.
Investigating the long-term use of exergames in the home with elderly fallers

Rehabilitation has been shown to significantly reduce the risk of falling in older adults. However, low adherence to rehabilitation exercises in the home means that seniors often do not get the therapy that they require. We propose that the use of tailored exergames could encourage adherence to falls rehabilitation in the home, as exergames have proved successful in clinical settings. We describe the results from the first known study to investigate the long-term (12 weeks) use of exergames, designed in close collaboration with elderly users, for falls rehabilitation in the home. Our findings suggest that there is an untapped potential of exergames for home rehabilitation use, as our findings show that there was better adherence to exercise in participants who used the exergames, versus those who used standard care. Finally, we make recommendations for designers, on the design of exergames for the rehabilitation of seniors.
Self-assessment through serious game

The activity of the traditional learning is defined as an activity of transmission of information following a single direction from a teacher to a student. The student is thus as a passive recipient of information without reacting or participating in resolution of real problems. Given the evolution of learning methods, teachers now have the opportunity to introduce games with an educational purpose to facilitate learning. The Serious Games is a continuous evolution and accelerated. This type of learning is integrated in teaching and in several areas. It is used to combine both serious aspects such as teaching, learning and playfulness through these games. After the learning process, assessment is the most important step in determining the learning' and the level of validation of learning objectives through the use of different valuation technics. It is therefore interesting to involve learners in the assessment process. This paper presents a novel approach regarding self-assessment in serious game. We address the needs of serious games as well as a review of existing research work in this field. To enrich learning aspect of serious games, we propose the integration of self-assessment modules in serious games. This integration is reflected in the design of an ontology representing different concepts.
Optimization of interference coordination schemes in Device-to-Device(D2D) communication

Device-to-Device (D2D) communication is considered to be a promising resource reuse technology for local services, to meet the system demands of higher data rates and spectrum efficiency in future networks. In order to limit severe interference between cellular links and local D2D links, previous studies mainly focus on one or two functional blocks, such as power control and resource allocation, which seems inadequate for further exploiting D2D's potential. In this paper, several interference coordination schemes, including centralized power control, resource allocation and mode selection strategy and distributed self-optimization mechanism, are proposed. Based on the proposed optimization schemes, we provide the system performance of the D2D-enabled network and analyze the impact of local service ratio and user density. Numerical results show that D2D underlay communication can increase spectrum efficiency and provide more local service opportunities compared to pure cellular communication.
Modulation of the gut microbiota composition by rifaximin in non-constipated irritable bowel syndrome patients: a molecular approach

Rifaximin, with its low systemic absorption, may represent a treatment of choice for irritable bowel syndrome (IBS), mainly due to its ability to act on IBS pathogenesis, through the influence on gut microbiota. The aim of the present study was to assess, by biomolecular tools, the rifaximin active modulation exerted on gut microbiota of non-constipated IBS patients. Fifteen non-constipated IBS subjects were treated with 550 mg rifaximin three times a day for 14 days. Stool samples were collected before starting the treatment, at the end of it, and after a 6-week washout period. Real-time polymerase chain reaction, denaturing gradient gel electrophoresis, and next-generation sequencing were applied to all the samples to verify and quantify possible microbial fluctuations. Rifaximin treatment did not affect the overall composition of the microbiota of the treated subjects, inducing fluctuations in few bacterial groups, balanced by the replacement of homologs or complementary bacterial groups. Rifaximin appeared to influence mainly potentially detrimental bacteria, such as Clostridium, but increasing the presence of some species, such as Faecalibacterium prausnitzii. A decrease in the Firmicutes/Bacteroidetes ratio after 14 days of treatment and bacterial profiles with higher biodiversity were observed during the follow-up compared to baseline. Rifaximin treatment, although effective on IBS symptom relief and normalization of lactulose breath test, did not induce dramatic shifts in the microbiota composition of the subjects, stimulating microbial reorganization in some populations toward a more diverse composition. It was not possible to speculate on differences of fecal microbiota modification between responders vs nonresponders and to correlate the quali-/quantitative modification of upper gastrointestinal microbiota and clinical response.
A distributed constraint optimization approach for coordination under uncertainty

Distributed Constraint Optimization (DCOP) provides a rich framework for modeling multi-agent coordination problems. We present a mapping to DCOP for large-scale team coordination problems that were used in the DARPA Coordinators program. We develop a new DCOP algorithm that scales to this domain and show that our algorithm outperforms other DCOP algorithms for this domain. Our approach is competitive with other general approaches used in the DARPA Coordinators program.
Towards Intelligent Team Composition and Maneuvering in Real-Time Strategy Games

Players of real-time strategy (RTS) games are often annoyed by the inability of the game AI to select and move teams of units in a natural way. Units travel and battle separately, resulting in huge losses and the AI looking unintelligent, as can the choice of units sent to counteract the opponents. Players are affected as well as computer commanded factions because they cannot micromanage all team related issues. We suggest improving AI behavior by combining well-known computational intelligence techniques applied in an original way. Team composition for battling spatially distributed opponent groups is supported by a learning self-organizing map (SOM) that relies on an evolutionary algorithm (EA) to adapt it to the game. Different abilities of unit types are thus employed in a near-optimal way, reminiscent of human ad hoc decisions. Team movement is greatly enhanced by flocking and influence map-based path finding, leading to a more natural behavior by preserving individual motion types. The team decision to either attack or avoid a group of enemy units is easily parametrizable, incorporating team characteristics from fearful to daredevil. We demonstrate that these two approaches work well separately, but also that they go together naturally, thereby leading to an improved and flexible group behavior.
AB-FTL: An alternative block Flash Translation Layer using locality-aware technique

Since flash memory has useful characteristics, it has been used in a variety of areas recently. However, it has a critical weakness known as “erase-before-write”, which means that whenever receiving a write request to the preoccupied place from a file system, an erase operation must be preceded. If such a frequent request is generated in succession, this policy makes systems have experienced serious performance degradation. Many efforts have been actively made to solve this problem, and the activities are moved to utilize Flash Translation Layers (FTL). The software layer also manages garbage collection and wear leveling strategies to extend the life span and prevent malfunction. In this paper, we propose a novel flash memory management scheme named AB-FTL using an alternative block which plays a role to collect the data with the same LBN (Logical Block Number) and the new operation named split operation to decrease many erase operations created by a number of full merge operations. Moreover, alternative blocks depend on the characteristics of locality to manage update requests more efficiently. Our experimental results show that AB-FTL is an outstanding FTL algorithm of reducing the full merge cost generated by full merge operations over the implemented FTLs.
Modeling and Analysis of a Flywheel Energy Storage System with a Power Converter Interface

A shipboard power system is a stiff, isolated power system. Power is generated locally, and distributed over short distances making the system vulnerable to transients. Power quality problems such as voltage sags, which arise due to a fault or a pulsed load, can cause interruptions of critical loads. This can be of a serious concern for the survivability of a combat ship. A series voltage injection type flywheel energy storage system is used to mitigate voltage sags. The basic cir- cuit consists of an energy storage system, power electronic interface and a series connected transformer. In this case the energy storage system consists of a flywheel coupled to an induction machine. The power electronic interface consists of two voltage sourced converters (VSC) connected through a common DC link. The flywheel stores energy in the form of kinetic energy and the induction machine is used for energy conversion. Bi-directional power flow is maintained by regu- lating the DC bus voltage. Indirect field oriented control with space vector PWM is used to control the induction machine. Sinusoidal PWM is used for controlling the power system side VSC. This paper presents the modeling, simulation and analysis of a flywheel energy storage system and with a power converter interface using EMTDC.
Cognitive radio: Emerging trend of next generation communication system

The 4 G communication systems are expected to become intelligent enough for communication between different entities. The idea is to extend Shannon's idea of perfect communication system to artificial agent for wireless communication. The internetworking of 3G communication system, cognitive radio, and software defined radio are candidate of 4G communication system. The difference in performance of 4G communication system is achieved through incorporating intelligence in wireless communication device. The various streams are studied to have in-built intelligence in communication devices. In this paper we focused on cognitive radio which works on basic idea of effectively managing available spectrum for different wireless communication systems. Paper explains cognitive radio as 4G communication system candidate and discusses design challenges of cognitive radio.
On The Torsion Homology of Non-Arithmetic Hyperbolic Tetrahedral Groups

Numerical data concerning the growth of torsion in the first homology of non-arithmetic hyperbolic tetrahedral groups are collected. The data provide support the speculations of Bergeron and Venkatesh on the growth of torsion homology and the regulators for lattices in SL(2,C).
A New Definition and Look at DNA Motif

Genetics is the main source of life. The more insights added to the knowledge of genetics, the more accurate prediction and even diagnosis of diseases may become. In genetics, a sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance. Sequence motifs are short, recurring patterns in DNA that are presumed to have a biological function. Often they indicate sequence-specific binding sites for proteins such as nucleases and transcription factors (TF). Others are involved in important processes at the RNA level, including ribosome binding, mRNA processing (splicing, editing, polyadenylation) and transcription termination. In this study we first concentrate on promoter motifs; however the discussions can easily be extended to other type of sequences. Promoter is a fragment of DNA sequence that is responsible for the transcription from DNA to RNA. Through the study on promoter, it can be found out which DNA sequence will be transcribed into RNA, and even transcription of any DNA sequence which is intended to study into RNA. In bacteria, the target sequence for RNA polymerase attachment is called the promoter. However, in eukaryotes, the term ‘promoter’ is used to describe all the sequences that are important in initiation of transcription of a gene. Although no clear definition of motif exist (Pisanti et al., 2005), some define motifs based on statistical representations in the form of PSSM (Position Specific Scoring Matrix) (Gribskov et al., 1987; Hertz & Stormo, 1996; Lawrence & Reilly, 1990; Lawrence et al., 1993). Another school of thought defines a motif as a consensus (Brazma et al., 1998; Vanet et al., 1999). A motif is therefore a pattern that appears repeatedly in a sequence or set of sequences of interest. The sequences that make up the E-coli promoter were first identified by comparing the regions upstream of over 100 genes. It was assumed that promoter sequences would be very similar for all genes and so should be recognizable when the upstream regions are compared. These analyses showed that the E. coli promoter consists of two motifs described as -10 box TATA-box or 5’-TATAAT-3’and -35 box TTG-Box or 5’-TTGACA-3’ (Brown, 2002). Most of the patterns known to biologist are contingent. In other words, nucleotides that these motifs have are located in consecutive positions. These patterns give more insight to understanding of DNA. O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
Indexação automática de imagens na web: tendências e desafios no contexto Deep Learning

O objetivo deste estudo é investigar em que medida as pesquisas na Ciência da Informação (CI) tem aproximado às das técnicas de Deep Learning, sendo relacionadas à representação, descrição e recuperação de imagens na Web, e assim, aferir da mais valia destas pesquisas quando aplicadas aos métodos da área da CI. A partir de uma revisão integrativa de literatura nacional e internacional de modo contextualizado na CI, os documentos recuperados foram analisados conforme os critérios da revisão integrativa, identificando um conjunto de operações que poderiam ser integrados nas metodologias de representação e descrição de imagens desenvolvidas e consolidadas no campo da CI. Conclui-se que ainda há uma lacuna nas pesquisas em CI tanto no âmbito nacional como internacional sobre Deep Learning e que recursos desta nova estrutura de programação podem ser aproximados aos métodos já validados pela área.
The common language of speech perception and action: a neurocognitive perspective

Quels sont les processus mis en œuvre pour extraire les informations du signal de parole ? Plus de 50 ans apres l’apparition de la theorie motrice de la perception de la parole, de recentes decouvertes neurophysiologiques contestent l’idee que la perception de la parole repose sur des mecanismes purement auditifs et suggerent que le systeme moteur jouerait egalement un role fondamental dans la comprehension de la parole. L’objectif du present chapitre est d’examiner ces resultats dans une tentative de definir ce que pourrait etre le « langage commun de la perception et de l’action ».
Utilising genetically informed research designs to better understand family processes and child development: implications for adoption and foster care focused interventions

Understanding the interplay between genetic factors and family environmental processes (e.g. interparental relationship quality, positive vs negative parenting practices) and children’s mental health (e.g. anxiety, depression, conduct problems, ADHD) in the contexts of adoption and foster care research and practice is critical for effective prevention and intervention programme development. While evidence highlights the importance of family relationship processes (e.g. interparental relationship quality, parent‒child relationship quality) for the mental health and well-being of children in adoption and foster care, there is relatively limited evidence of effective interventions specifically for these families. Additionally, family-based interventions not specific to the context of adoption and foster care typically show small to medium effects, and even where interventions are efficacious, not all children benefit. One explanation for why interventions may not work well for some is that responses to an intervention may be influenced by an individual’s genetic make-up. Alternatively, the targets of family relationship level interventions (e.g. parenting processes) may not always affect the specific environment ‘trigger’ deemed salient to specific child/adolescent outcomes. This article summarises how genetically informed research designs can help disentangle genetic from environmental processes underlying psychopathology outcomes for children, and how this evidence can provide improved insights into the development of more effective preventive intervention targets for adoptive and foster families. We discuss current difficulties in translating behavioural genetics research to prevention science and provide recommendations to bridge the gap between behavioural genetics research and prevention science, with lessons for adoption and foster care research and practice.