The social profitability of rural roads in a small open economy: Do urban agglomeration economies matter?

The effects of a rural roads programme depend on labour mobility, how the programme is financed, and agglomeration economies. If financed by a rural poll tax and cross-price effects and agglomeration economies are sufficiently small, the wage will rise, with some return migration. Taxes on trade act as countervailing distortions, yielding urban households some relief. Rural-urban commuting promotes the exploitation of agglomeration economies; taxes on international trade are then inferior to a poll tax. The change in the value, at producer prices, of the rural sector's net supply vector can be a poor measure of the programme's social profitability.     

Labeling and Characterization of Phenol-Containing Glycopeptides Using Chemoselective Probes with Isotope Tags

Secondary metabolites are structurally diverse natural products (NPs) and have been widely used for medical applications. Developing new tools to enrich NPs can be a promising solution to isolate novel NPs from the native and complex samples. Here, we developed native and deuterated chemoselective labeling probes to target phenol-containing glycopeptides by the ene-type labeling used in proteomic research. The clickable azido-linker was included for further biotin functionalization to facilitate the enrichment of labeled substrates. Afterward, our chemoselective method, in conjunction with LC-MS and MSn analysis, was demonstrated in bacterial cultures. A vancomycin-related phenol-containing glycopeptide was labeled and characterized by our labeling strategy, showing its potential in glycopeptide discovery in complex environments.     

基于LBSN动态异构网络的时间感知兴趣点推荐

随着基于位置社交网络(Location-Based Social Network,LBSN)的快速发展,兴趣点(Point-Of-Interest,POI)推荐可以帮助人们发现有趣的并吸引人的位置。针对签到数据的稀疏性和用户兴趣的动态性等挑战性问题,提出了基于LBSN动态异构网络的时间感知兴趣点推荐算法。在LBSN异构网络模式中增加会话节点类型。通过动态元路径,在用户和兴趣点语义关系之间有效地融入时间信息、位置信息和社交信息等。设置了用户-兴趣点之间的动态元路径集,并提出了动态路径实例的偏好度计算方法。采用矩阵分解模型对不同动态偏好矩阵进行矩阵分解。根据不同动态元路径的用户特征矩阵和兴趣点特征矩阵,获取用户在目标时间访问兴趣点的推荐列表。实验结果表明,与其他兴趣点推荐方法相比,所提方法在兴趣点推荐精确度上取得了较好的推荐结果,具有良好的应用前景。     

Sustainable supply chain management in Indian organisations: an empirical investigation

The present work is an attempt to investigate the adoption of sustainable supply chain management (SSCM) practices amongst manufacturing and process based organisations in India and its impact on organisational performance encompassing all three dimensions of sustainability. SSCM practices conceived in the present study include environmental management practices (EMP), socially inclusive practices for employees (SPE), socially inclusive practices for community (SPC), operations practices (OP) and supply chain integration (SCI) which were treated as exogenous variables. Organisational performance considered in this study includes five dimensions, namely environmental performance (EPR), employee-centred social performance (ESP), community-centred social performance (CSP), operations performance (OPR) and competitiveness, which were regarded as endogenous variables. The analysis was carried out with the help of structural equation modelling considering natural logarithm of manpower as a control variable. Few major findings are mentioned. EMP does not have any significant association with OPR, nor does it result in competitiveness. However, when jointly mediated through both EPR and OPR, EMP leads to competitiveness. SPC has significant negative association with competitiveness, when only direct relationship is considered. However, indirect relationship between SPC and competitiveness shows significant positive association when mediated through CSP. The resultant total effect between SPC and competitiveness turns out to be insignificant. Further, OPR fully mediates the relationship between OP and competitiveness. Managerial implications of the findings are discussed.     

Developing English domestic occupancy profiles

ABSTRACT

Occupancy patterns are necessary to estimate energy demand and evaluate thermal comfort in households. Because of this, many European countries are developing representative domestic schedules to replace outdated criteria. This paper evaluates the state of knowledge of UK domestic occupancy patterns and develops new domestic occupancy profiles for England. The presented research (1) characterizes methods for collecting occupancy data and inferring patterns; (2) identifies and assesses the quality of categories of occupancy patterns used in building simulation; and (3) develops updated occupancy profiles. A systematic scoping review identified social and monitoring surveys as the most deployed data-collection methods. A systematic literature review also established that the occupancy categories most frequently used in UK building simulation are (a) a family with dependent children where the parents work full time; and (b) a retired elderly couple who spend most of their time indoors. The interview sample from the English Housing Survey 2014–15 was used to map household typologies. Results show that categories (a) and (b) combined amount to only 19% of England’s households, which suggest models are over-reliant on these groups. Considering this result, the paper develops occupancy patterns for England derived from 2015 UK Time Use Survey diaries for each household typology previously identified.     

Exploring the Impact of Social Networking on Communication in Organizations

ABSTRACT

Social networking technology has the potential to transform how organizations communicate, cooperate, and connect with key stakeholders. Our research explores how social networking technologies are deployed within organizations and how the use of these technologies is related to effectiveness in organizational communication and promotion. We also identify the facilitating factors and constraints around the use of social networking tools for communication. To examine these questions, we conducted interviews with 131 senior level executives across a broad range of organizations and employed both quantitative and qualitative methods of analysis. The executives were asked to rate numerically and then discuss in narrative form a series of questions about IT strategy and issues affecting social networking in their organization. We find important differences both in the types of tools used as well as how they are used and discuss the implications of our findings for companies seeking to more effectively harness social networking technologies.     

社交网络中基于网络结构支撑模型的谣言传播研究

结合结构支撑理论，探究节点网络结构支持力的一些性质，提出了社交网络结构中的全网支持力和被支持力的总量一致性，并进一步提出计算节点支持力的方法。谣言作为特殊信息，在支持力不同节点之间的传播特性有所不同，借鉴随机游走模型中的PageRank计算方法，对不同节点支持力的谣言传播以及传播后的辟谣状况进行了仿真模拟，结果表明支持力不同的节点对于谣言传播和辟谣影响明显。     

TSL:predicting popularity of Facebook content based on tie strength

The rapid development of online social networks leads to an explosion of information,however,there are great differences in the popularity of different messages,and accurate prediction is always a great difficulty is the current study.Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status.Existing models for popularity prediction were mostly based on discovering network features or fitting the equation into a varying time function that the accuracy of current popularity prediction model was not high enough.Therefore,with the help of the weak ties theory in sociology,the concept of tie strength was introduced and a multilinear regression equation was constructed combined with the early popularity.A TSL model to predict the popularity of Facebook’s well-known pages was proposed.The main contribution of this article was to solve the problem and few or no work based on sociology.A high linear correlation between the proportion of faithful fans was existed in Facebook homepage with frequent shares in the early and the future popularity.Compared with other baseline models,an experimental study of Facebook (including 1.54 million shares) illustrates the effectiveness of the proposed TSL model,and the performance is better than the existing similar methods.     

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids, carbohydrates, and lipids, as well as protein synthesis from the consumed food, the liver has many diverse responsibilities and functions that are to be performed. Liver disease may impact the hormonal and nutritional balance in the human body. The earlier diagnosis of such critical conditions may help to treat the patient effectively. A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver. The proposed approach can recognize the abnormalities with better accuracy without training, unlike in supervisory procedures requiring considerable computational efforts for training. In the earlier stages, the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation. Then, the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted–-Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information, which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts. It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%. The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.     

Analyzing Dynamic Change in Social Network Based on Distribution-Free Multivariate Process Control Method

Social organizations can be represented by social network because it can mathematically quantify and represent complex interrelated organizational behavior. Exploring the change in dynamic social network is essential for the situation awareness of the corresponding social organization. Social network usually evolves gradually and slightly, which is hard to be noticed. The statistical process control techniques in industry field have been used to distinguish the statistically significant change of social network. But the original method is narrowed due to some limitation on measures. This paper presents a generic framework to address the change detection problem in dynamic social network and introduces a distribution-free multivariate control charts to supervise the changing of social network. Three groups of network parameters are integrated together in order to achieve a comprehensive view of the dynamic tendency. The proposed approaches handle the non-Gaussian data based on categorizing and ranking. Experiments indicate that nonparametric multivariate procedure is promising to be applied to social network analysis.