Optimization of Project Portfolio Selection Considering Interactions Among Multiple Projects

In conditions of capital constraints, a single-objective nonlinear 0-1 integer programming model is proposed based on grey theory. First, application of Grey Theory deals with uncertainty of attribute weights’ values given by experts and projects’ scores under different attributes. Second, we construct two multi-attribute utility objective functions by comparing situations of considering interactions and without interactions, and two new multi-project portfolio optimization models are established. Finally, a numerical example illustrates effectiveness and practicality of the proposed model

EFFECT OF DUAL-TRACK INTERACTIVE NURSING INTERVENTION MODEL ON ANXIETY AND DEPRESSION IN PATIENTS WITH CORONARY HEART DISEASE

Background: Elderly patients with coronary heart disease often suffer adverse psychological reactions, such as anxiety and depression. The dual-track interactive nursing model is a nursing intervention aimed to provide specific and community nursing. For patients with chronic diseases, this model can improve the patients’ self-management and rehabilitation. The effect of this model on the mental health of patients with chronic diseases has been unanimously recognized by researchers. In this study, a dual-track interactive nursing model intervention was conducted on the anxiety and depression in elderly patients with coronary heart disease to verify the psychological effect of the model. Subjects and methods: From June 2018 to June 2019, 136 elderly patients with coronary heart disease (mean age of 63.5±8.26 years) from three communities in Changsha, Hunan Province, China were selected as subjects. A total of 53 and 50 patients were identified in the intervention and the control groups, respectively. The control group underwent routine longitudinal referral, whereas the intervention group was subjected to a two-track interactive nursing model intervention. The Short Form-36 Health Survey (SF-36) and related questionnaires were used to monitor and compare the two groups before and after the intervention and employed for scoring and comparative analysis. Results: After the intervention, the mental health scores of the intervention group in total score, somatization, obsessive–compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, and paranoia are significantly lower than those of the control group (P<0.05). The intervention group has scored significantly higher in coping style but significantly lower in negative coping than the control group (P<0.05). Conclusions: The application of the dual-track interactive nursing model intervention in the management of patients with coronary heart disease can improve the self-management and the mental health of patients with coronary heart disease

An Exact Algorithm for the Shortest Path Problem With Position-Based Learning Effects

[EN] The shortest path problems (SPPs) with learning effects (SPLEs) have many potential and interesting applications. However, at the same time they are very complex and have not been studied much in the literature. In this paper, we show that learning effects make SPLEs completely different from SPPs. An adapted A* (AA*) is proposed for the SPLE problem under study. Though global optimality implies local optimality in SPPs, it is not the case for SPLEs. As all subpaths of potential shortest solution paths need to be stored during the search process, a search graph is adopted by AA* rather than a search tree used by A*. Admissibility of AA* is proven. Monotonicity and consistency of the heuristic functions of AA* are redefined and the corresponding properties are analyzed. Consistency/monotonicity relationships between the heuristic functions of AA* and those of A* are explored. Their impacts on efficiency of searching procedures are theoretically analyzed and experimentally evaluated.This work was supported in part by the National Natural Science Foundation of China under Grant 61572127 and Grant 61272377, and in part by the Specialized Research Fund for the Doctoral Program of Higher Education under Grant 20120092110027. The work of R. Ruiz was supported in part by the Spanish Ministry of Economy and Competitiveness under Project "RESULT-Realistic Extended Scheduling Using Light Techniques" under Grant DPI2012-36243-C02-01, and in part by the FEDER.Wang, Y.; Li, X.; Ruiz García, R. (2017). An Exact Algorithm for the Shortest Path Problem With Position-Based Learning Effects. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans. 47(11):3037-3049. https://doi.org/10.1109/TSMC.2016.2560418S30373049471

Evaluation of Travis Peak gas reservoirs, west margin of the East Texas Basin

Gas production from low-permeability (tight) gas sandstones is increasingly important in the USA as conventional gas reservoirs are being depleted, and its importance will increase worldwide in future decades. Travis Peak tight sandstones have produced gas since the 1940s. In this study, well log, 2D seismic, core, and production data were used to evaluate the geologic setting and reservoir characteristics of the Travis Peak formation. The primary objective was to assess the potential for basinward extension of Travis Peak gas production along the west margin of the East Texas Basin. Along the west margin of the East Texas Basin, southeast-trending Travis Peak sandstones belts were deposited by the Ancestral Red River fluvial-deltaic system. The sandstones are fine-grained, moderately well sorted, subangular to subrounded, quartz arenites and subarkoses; reservoir quality decreases with depth, primarily due to diagenetic quartz overgrowths. Evaluation of drilling mud densities suggests that strata deeper than 12,500 ft may be overpressured. Assessment of the geothermal gradient (1.6 °F/100 ft) indicates that overpressure may be relict, resulting from hydrocarbon generation by Smackover and Bossier formation potential source rocks. In the study area, Travis Peak cumulative gas production was 1.43 trillion cubic feet from January 1, 1961, through December 31, 2005. Mean daily gas production from 923 wells was 925,000 cubic ft/well/day, during the best year of production. The number of Travis Peak gas wells in “high-cost” (tight sandstone) fields increased from 18 in the decade 1966-75 to 333 in the decade 1996-2005, when high-cost fields accounted for 33.2% of the Travis Peak gas production. However, 2005 gas production from high cost fields accounted for 63.2% of the Travis Peak total production, indicating that production from high-cost gas wells has increased markedly. Along the west margin of the East Texas Basin, hydrocarbon occurs in structural, stratigraphic, and combination traps associated with salt deformation. Downdip extension of Travis Peak production will depend on the (1) burial history and diagenesis, (2) reservoir sedimentary facies, and (3) structural setting. Potential Travis Peak hydrocarbon plays include: updip pinch-outs of sandstones; sandstone pinch-outs at margins of salt-withdrawal basins; domal traps above salt structures; and deepwater sands

Critically Appraised Paper for “Cognitive stimulation of executive functions in mild cognitive impairment: Specific efficacy and impact in memory”

Executive functions play a pivotal role in an individual’s independence. However, little research has been conducted on the efficacy of specific cognitive training for individuals with deficits consistent with mild cognitive impairment (MCI). The researchers in this study aimed to use a cognitive stimulation program that taught specific strategies to enhance the participants’ attentional and executive functional tasks. The study, using a crossover design involving two groups, included 30 participants affected by the amnestic form of MCI, executive function deficits, or both. The 6-month training sessions addressed challenges through the use of individualized cognitive strategies and proposed activities to exercise specific cognitive functions, such as shifting between two or more tasks to target cognitive flexibility. The first 2 months of the program consisted of intensive treatment, with two individual sessions per week, starting with an in-depth discussion about the difficulties each participant was experiencing. A program was then planned and discussed with the participant and caregiver, after which cognitive strategies were created and implemented. The last 4 months of the program comprised one session per week involving cognitive strategies created by the therapists and tested by the participants and caregivers in daily life activities. During the training sessions, the caregivers were actively involved and played an important role by assisting the participants in implementing strategies in the home environment. The results showed an improvement in executive function in participants affected by MCI after they participated in the program. Moreover, the study also showed that cognitive performance can decline over time without stimulation and may only be partially recovered with the stimulation program. The data indicate that individuals affected by MCI may benefit from the cognitive stimulation program in the early stages, before a decline in cognition. Furthermore, once decline has begun, only partial recovery of the lost cognitive function may be restored through this program. This study generated several significant findings in that individuals affected by MCI can show improvement in executive function with specific cognitive stimulation. However, in recommending this cognitive stimulation program as an intervention in the field of occupational therapy, therapists should be cautious of the limitations and generalizability of this study as well as the labor-intensity demands of the intervention. Furthermore, the caregivers’ influence created a limitation on the clinical application of this study. The caregivers were very involved in this study; however, almost no information was given regarding their characteristics

An Iterated Greedy Heuristic for Mixed No-Wait Flowshop Problems

[EN] The mixed no-wait flowshop problem with both wait and no-wait constraints has many potential real-life applications. The problem can be regarded as a generalization of the traditional permutation flowshop and the no-wait flowshop. In this paper, we study, for the first time, this scheduling setting with makespan minimization. We first propose a mathematical model and then we design a speed-up makespan calculation procedure. By introducing a varying number of destructed jobs, a modified iterated greedy algorithm is proposed for the considered problem which consists of four components: 1) initialization solution construction; 2) destruction; 3) reconstruction; and 4) local search. To further improve the intensification and efficiency of the proposal, insertion is performed on some neighbor jobs of the best position in a sequence during the initialization, solution construction, and reconstruction phases. After calibrating parameters and components, the proposal is compared with five existing algorithms for similar problems on adapted Taillard benchmark instances. Experimental results show that the proposal always obtains the best performance among the compared methods.This work was supported in part by the National Natural Science Foundation of China under Grant 61572127 and 61272377, in part by the Key Research and Development Program in Jiangsu Province under Grant BE2015728, and in part by the Collaborative Innovation Center of Wireless Communications Technology. The work of R. Ruiz was supported in part by the Spanish Ministry of Economy and Competitiveness through the project "SCHEYARD-Optimization of Scheduling Problems in Container Yards" under Grant DPI2015-65895-R, and in part by the FEDER Funds.Wang, Y.; Li, X.; Ruiz García, R.; Sui, S. (2018). An Iterated Greedy Heuristic for Mixed No-Wait Flowshop Problems. IEEE Transactions on Cybernetics. 48(5):1553-1566. https://doi.org/10.1109/TCYB.2017.2707067S1553156648

Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis

Radiomics analysis has achieved great success in recent years. However, conventional Radiomics analysis suffers from insufficiently expressive hand-crafted features. Recently, emerging deep learning techniques, e.g., convolutional neural networks (CNNs), dominate recent research in Computer-Aided Diagnosis (CADx). Unfortunately, as black-box predictors, we argue that CNNs are "diagnosing" voxels (or pixels), rather than lesions; in other words, visual saliency from a trained CNN is not necessarily concentrated on the lesions. On the other hand, classification in clinical applications suffers from inherent ambiguities: radiologists may produce diverse diagnosis on challenging cases. To this end, we propose a controllable and explainable {\em Probabilistic Radiomics} framework, by combining the Radiomics analysis and probabilistic deep learning. In our framework, 3D CNN feature is extracted upon lesion region only, then encoded into lesion representation, by a controllable Non-local Shape Analysis Module (NSAM) based on self-attention. Inspired from variational auto-encoders (VAEs), an Ambiguity PriorNet is used to approximate the ambiguity distribution over human experts. The final diagnosis is obtained by combining the ambiguity prior sample and lesion representation, and the whole network named $DenseSharp^{+}$ is end-to-end trainable. We apply the proposed method on lung nodule diagnosis on LIDC-IDRI database to validate its effectiveness.Comment: MICCAI 2019 (early accept), with supplementary material