SHIP Deficiency Research Articles

Intelligent ship inspection analytics: Ship deficiency data mining for port state control

To provide safe, secure, and environment-friendly maritime transport, it is an essential point to define and take appropriate countermeasures against the substandard ships in maritime transport. Port State Control (PSC) is one of the critical inspection regimes recognized worldwide to define substandard ships. However, one of the biggest challenge faced in ship inspection is the necessity of checking many items through limited time and qualified human resources. Therefore, in this study, it is aimed to develop a decision support system to increase the effectiveness of ship inspections. In accordance with this, we proposed an intelligent ship inspection analytics (I-SIA) model based on the Knowledge Discovery in Database (KDD) process by utilizing fuzzy c-means clustering and apriori algorithms. The I-SIA model provides the determination of ship deficiency patterns based on specific ship attributes, and subsequently predicts main/sub inspection items to be focused on through former inspection records of the ship to be inspected. In the case study performed for a selected ship, I-SIA predicts critical 5 main and 23 sub-inspection items that need to be checked with high priority, among 17 main inspection items and out of more than 500 sub-inspection items. Herewith, I-SIA provides a ship-specific and dynamic ship inspection based on deficiencies recorded in previous inspections and detected during inspection. Thus, it becomes possible to enhance the effectiveness of the inspection via defined deficiency patterns.

Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation

<abstract><p>Maritime transportation plays a significant role in international trade and global supply chains. Ship navigation safety is the foundation of operating maritime business smoothly. Recently, more and more attention has been paid to marine environmental protection. To enhance maritime safety and reduce pollution in the marine environment, various regulations and conventions are proposed by international organizations and local governments. One of the most efficient ways of ensuring that the related requirements are complied with by ships is ship inspection by port state control (PSC). In the procedure of ship inspection, a critical issue for the port state is how to select ships of higher risk for inspection and how to optimally allocate the limited inspection resources to these ships. In this study, we adopt prediction and optimization approaches to address the above issues. We first predict the number of ship deficiencies based on a k nearest neighbor (kNN) model. Then, we propose three optimization models which aim for a trade-off between the reward for detected deficiencies and the human resource cost of ship inspection. Specifically, we first follow the predict-then-optimize framework and develop a deterministic optimization model. We also establish two stochastic optimization models where the distribution of ship deficiency number is estimated by the predictive prescription method and the global prescriptive analysis method, respectively. Furthermore, we conduct a case study using inspection data at the Hong Kong port to compare the performances of the three optimization models, from which we conclude that the predictive prescription model is more efficient and effective for this problem.</p></abstract>

Pairwise-Comparison Based Semi-SPO Method for Ship Inspection Planning in Maritime Transportation

Port state control (PSC) plays an important role in enhancing maritime safety and protecting the marine environment. Since the inspection resources are limited and the inspection process is costly and time-consuming, a critical issue for port states to guarantee inspection efficiency is to accurately select ships with a high risk for inspection. To address this issue, this study proposes three prediction models to predict the ship deficiency number and a ship selection optimization model based on the prediction results to target the riskiest ships for inspection. In addition to a linear regression model for ship deficiency number prediction solved by the least squares method, we establish two prediction models with the pairwise-comparison target based semi-“smart predict then optimize” (semi-SPO) method. Specifically, a linear programming model and a support vector machine (SVM) model are built and both have a loss function to minimize the sum of predicted ranking errors of each pair of ships regarding their deficiency numbers. We use the Hong Kong port as a case study, which shows that the SVM model based on the semi-SPO approach performs best among the three models with the least computation time and best ship selection decisions.

Ship Deficiency Data of Port State Control to Identify Hidden Risk of Target Ship

In the new inspection regime (NIR) of port state control (PSC), the criteria for being judged as a standard risk ship (SRS) is too broad. Some ships are classified as SRS even though they have a large number of ship deficiencies. This paper develops a selection system to identify the hidden risk of target ships in the SRS category using PSC inspection records. This system allows the target ship to be used to help reduce cases of flags being greylisted or blacklisted, which can cause huge shipping losses. This study analyzes ship deficiency data in the Tokyo memorandum of understanding (Tokyo MoU) database. It adopts the multiple criteria decision making (MCDM) model as a data processing technique to build a risk assessment scale. It uses fuzzy importance performance analysis (F-IPA) and technology for order preference by similarity to the ideal solution (TOPSIS) for its analysis. Subsequently, the weights of F-IPA and TOPSIS are adopted into the MCDM model. This article also consulted the Tokyo MoU database. It has been verified that the next time PSC inspection, the system hits 83.3% of the hidden risk ships in the SRS category. Thus, this system will help inspectors be more insightful for target ships.

Shipping Domain Knowledge Informed Prediction and Optimization in Port State Control

Maritime transportation is the backbone of global supply chain. To improve maritime safety, protect the marine environment, and set out seafarers’ rights, port state control (PSC) empowers ports to inspect foreign visiting ships to verify them comply with various international conventions. One critical issue faced by the port states is how to optimally allocate the limited inspection resources for inspecting the visiting ships. To address this issue, this study first develops a state-of-the-art XGBoost model to accurately predict ship deficiency number considering ship generic factors, dynamic factors, and inspection historical factors. Particularly, the XGBoost model takes shipping domain knowledge regarding ship flag, recognized organization, and company performance into account to improve model performance and prediction fairness (e.g., for two ships that are different only in their flag performances, the one with a better flag performance should be predicted to have a better condition than the other). Based on the predictions, a PSC officer (PSCO) scheduling model is proposed to help the maritime authorities optimally allocate inspection resources. Considering that a PSCO can inspect at most four ships in a day, we further propose and incorporate the concepts of inspection template and un-dominated inspection template in the optimization models to reduce problem size as well as improve computation efficiency and model flexibility. Numerical experiments show that the proposed PSCO scheduling model with the predictions of XGBoost as the input is more than 20% better than the current inspection scheme at ports regarding the number of deficiencies detected. In addition, the gap between the proposed model and the model under perfect-forecast policy is only about 8% regarding the number of deficiencies detected. Extensive sensitivity experiments show that the proposed PSCO scheduling model has stable performance and is always better than the current model adopted at ports.

A188 TARGETING RIPK2 TO TREAT INTESTINAL INFLAMMATION CAUSED BY SHIP DEFICIENCY

Abstract Background Crohn’s disease (CD) is a form of inflammatory bowel disease characterized by chronic inflammation along the gastrointestinal tract. We have described the SHIP-/- mouse model of CD-like intestinal inflammation. SHIP-/- mice develop spontaneous ileal inflammation that is characterized by villus hyperplasia and disorganization, edema, immune cell infiltration, ulceration, loss of goblet cells, and muscle wall thickening. SHIP deficiency in people with CD has been associated with a more severe and treatment-refractory disease. Interestingly, NOD2 gene variants, which are the most profound genetic associations for CD, are also associated with a more severe CD phenotype. Muramyl dipeptide (MDP) is a molecular associated microbial pattern, which activates the NOD2 signalling pathway. Recently, SHIP has been reported to play a role in the NOD2 pathway by disrupting the downstream interaction between RIPK2 and XIAP required for NOD2-mediated NFκB activation and pro-inflammatory cytokine production. Aims Based on this, we hypothesized that SHIP deficiency contributes to inflammation in CD by increasing NOD2-mediated pro-inflammatory cytokine production. Moreover, RIPK2 inhibitors will block intestinal inflammation caused by SHIP deficiency by blocking RIPK2-XIAP interactions required for NOD2 signalling and resultant pro-inflammatory cytokine production. To test this hypothesis, my aim was to determine the effect of RIPK2 inhibitors on the development of spontaneous intestinal inflammation in SHIP-/- mice. Methods 6 week-old SHIP-/- mice (and SHIP+/+ mice controls) were treated with RIPK2 inhibitors, FCG806791773 or Z1210264067, by intra-pertioneal injections every other day for 2 weeks and compared to SHIP-/- mice treated with 2% DMSO in PBS, as a vehicle control. On Day 14, distal ilea were harvested and gross pathology was assessed. Cross-sections of the ilea were H&E stained to evaluate histological damage based on villi architecture, edema, immune cell infiltration, ulceration, goblet cell loss, and muscle wall thickening. Results As expected, SHIP+/+ mice did not have gut pathology and their healthy gut phenotype was not affected by RIPK2 inhibitors. SHIP-/- mice had ileal inflammation that was evident in gross pathology and in H&E-stained tissue sections. Importantly, SHIP-/- mice treated with RIPK2 inhibitors, FCG806791773 or Z1210264067, had reduced gross pathology compared to vehicle control-treated mice. Z1210264067 treated SHIP-/- mice also had significantly lower histological damage compared to vehicle control-treated SHIP-/- mice. Conclusions RIPK2 inhibitors reduced gross and histopathology in SHIP-/- mice suggesting that RIPK2 inhibitors may be an effective treatment for people with CD, and may be particularly effective in people with CD, who harbor NOD2 risk variants and/or have low SHIP activity. Funding Agencies CCC, CIHR

Incorporation of deficiency data into the analysis of the dependency and interdependency among the risk factors influencing port state control inspection

Port State Control (PSC) inspection aids to control substandard ships and ensure safety at sea. Current risk-based PSC research and practice fail to incorporate ship deficiency records into detention probability analysis, because of the difficulty introduced by the involved big deficiency data. In this paper, a new Bayesian Network (BN) based PSC risk probabilistic model is developed to analyze the dependency and interdependency among the risk factors influencing PSC inspections based on big data derived from the inspection database of Tokyo MoU for the period between 2014 and 2017. The results reveal that ship's safety condition related deficiencies as well as technical features of the inspected vessel itself are among the most influential factors concerning PSC inspections and ship detention. New Bayesian learning methods are used to improve the model efficiency in ship detention prediction. As a result, the newly developed model has shown a reliable performance on dynamic prediction and cause-effect diagnosis of ship detention probabilities by pioneering the incorporation of ship deficiency records in the analysis. The findings provide important insights on how to facilitate risk-based PSC inspections for both ship owners and port states. They provide support for port state authorities to implement rational inspection policies.

Ship Detention Situation Prediction via Optimized Analytic Hierarchy Process and Naïve Bayes Model

Ship detention serves as an obligatory but efficient manner in port state control (PSC) inspection, and accurate ship detention prediction provides early warning information for maritime traffic participants. Previous studies mainly focused on exploiting the relationship between ship factors (i.e., ship age and ship type) and PSC inspection reports. Less attention was paid to identify and predict the correlation between ship fatal deficiency and ship detention event. To address the issue, we propose a novel framework to identify crucial ship deficiency types with an optimized analytic hierarchy process (AHP) model. Then, the Naïve Bayes model is introduced to predict the ship detention probability considering weights of the identified crucial ship deficiency types. Finally, we evaluate our proposed model performance on the empirical PSC inspection dataset. The research findings can help PSC officials easily determine main ship deficiencies, and thus, less time cost is required for implementing the PSC inspection procedure. In that manner, the PSC officials can quickly make ship detention decision and thus enhance maritime traffic safety.

Mining ship deficiency correlations from historical port state control (PSC) inspection data.

Early warning on the ship deficiency is crucial for enhancing maritime safety, improving maritime traffic efficiency, reducing ship fuel consumption, etc. Previous studies focused on the ship deficiency exploration by mining the relationships between the ship physical deficiencies and the port state control (PSC) inspection results with statistical models. Less attention was paid to discovering the correlation rules among various parent ship deficiencies and subcategories. To address the issue, we proposed an improved Apriori model to explore the intrinsic mutual correlations among the ship deficiencies from the PSC inspection dataset. Four typical ship property indicators (i.e., ship type, age, deadweight and gross tonnage) were introduced to analyze the correlations for the ship parent deficiency categories and subcategories. The findings of our research can provide basic guidelines for PSC inspections to improve the ship inspection efficiency and maritime safety.

The Effectiveness of New Inspection Regime on Port State Control Inspection

Port state control (PSC) inspection is an important measure to improve ship safety and reduce ship accident rate. To improve the effectiveness of PSC inspections, some MoUs have begun to implement new inspection regime (NIR). However, the effectiveness of NIR remains to be studied. Then this study aims to verify the effectiveness of NIR and improve shipping safety. In this study, Bayesian Network model is used to establish the relationship between NIR, ship deficiencies, detention and ship accident to explore the impact of NIR on maritime safety. The data in this study are from PSC inspection data in the Tokyo Memorandum of Understanding (MoU) and accident data in the International Maritime Organization (IMO). By analyzing the changes of the number of ship deficiency, detention rate and accident rate before and after NIR implementation, the effectiveness of NIR can be verified. The results show that the implementation of NIR does not effectively reduce the number of substandard ships, but the number of ships with serious deficiencies is significantly reduced. However, ship accident rate has not declined. Therefore, it is believed that Tokyo MoU needs to further improve the effectiveness of NIR and strengthen supervision of defective ships.

SHIP1 regulates MSC numbers and their osteolineage commitment by limiting induction of the PI3K/Akt/β-catenin/Id2 axis.

Here, we show that Src homology 2-domain-containing inositol 5'-phosphatase 1 (SHIP1) is required for the efficient development of osteoblasts from mesenchymal stem cells (MSCs) such that bone growth and density are reduced in mice that lack SHIP1 expression in MSCs. We find that SHIP1 promotes the osteogenic output of MSCs by limiting activation of the PI3K/Akt/β-catenin pathway required for induction of the MSC stemness factor Id2. In parallel, we demonstrate that mice with myeloid-restricted ablation of SHIP1, including osteoclasts (OCs), show no reduction in bone mass or density. Hence, diminished bone mass and density in the SHIP1-deficient mice results from SHIP deficiency in MSC and osteolineage progenitors. Intriguingly, mice with a SHIP-deficient MSC compartment also exhibit decreased OC numbers. In agreement with our genetic findings we also show that treatment of mice with an SHIP1 inhibitor (SHIPi) significantly reduces bone mass. These findings demonstrate a novel role for SHIP1 in MSC fate determination and bone growth. Further, SHIPi may represent a novel therapeutic approach to limit bone development in osteopetrotic and sclerotic bone diseases.

Deficiency Analysis of Different Ship Types Based on Taiwan PSC Data

The work Port State Control (PSC) lets ships more and more comply with the relevant international conventions by checking and mandatory correction or detention. In this paper, based on the PSC data of Taiwan ports in the past nine years, mathematical statistics method is put forward to analysis the association between ship type and deficiency, which could provide PSC officers with constructive recommendations.

Aberrant antibody affinity selection in SHIP‐deficient B cells

The strength of the Ag receptor signal influences development and negative selection of B cells, and it might also affect B-cell survival and selection in the GC. Here, we have used mice with B-cell-specific deletion of the 5'-inositol phosphatase SHIP as a model to study affinity selection in cells that are hyperresponsive to Ag and cytokine receptor stimulation. In the absence of SHIP, B cells have lower thresholds for Ag- and interferon (IFN)-induced activation, resulting in augmented negative selection in the BM and enhanced B-cell maturation in the periphery. Despite a tendency to spontaneously downregulate surface IgM expression, SHIP deficiency does not alter anergy induction in response to soluble hen-egg lysozyme Ag in the MDA4 transgenic model. SHIP-deficient B cells spontaneously produce isotype-switched antibodies; however, they are poor responders in immunization and infection models. While SHIP-deficient B cells form GCs and undergo mutation, they are not properly selected for high-affinity antibodies. These results illustrate the importance of negative regulation of B-cell responses, as lower thresholds for B-cell activation promote survival of low affinity and deleterious receptors to the detriment of optimal Ab affinity maturation.

Lineage extrinsic and intrinsic control of immunoregulatory cell numbers by SHIP

We previously showed that germline or induced SHIP deficiency expands immuno-regulatory cell numbers in T lymphoid and myeloid lineages. We postulated these increases could be interrelated. Here, we show that myeloid-specific ablation of SHIP leads to the expansion of both myeloid-derived suppressor cell (MDSC) and regulatory T (Treg) cell numbers, indicating SHIP-dependent control of Treg-cell numbers by a myeloid cell type. Conversely, T-lineage specific ablation of SHIP leads to expansion of Treg-cell numbers, but not expansion of the MDSC compartment, indicating SHIP also has a lineage intrinsic role in limiting Treg-cell numbers. However, the SHIP-deficient myeloid cell that promotes MDSC and Treg-cell expansion is not an MDSC as they lack SHIP protein expression. Thus, regulation of MDSC numbers in vivo must be controlled in a cell-extrinsic fashion by another myeloid cell type. We had previously shown that G-CSF levels are profoundly increased in SHIP(-/-) mice, suggesting this myelopoietic growth factor could promote MDSC expansion in a cell-extrinsic fashion. Consistent with this hypothesis, we find that G-CSF is required for expansion of the MDSC splenic compartment in mice rendered SHIP-deficient as adults. Thus, SHIP controls MDSC numbers, in part, by limiting production of the myelopoietic growth factor G-CSF.

SHIP deficiency causes Crohn's disease-like ileitis

BackgroundInflammatory bowel disease (IBD) can arise from genetic mutations that compromise intestinal epithelial cell integrity or immune regulation. SHIP has previously been shown to play a pivotal role in limiting...

SHIP is required for a functional hematopoietic stem cell niche

AbstractSH2-domain-containing inositol 5′-phosphatase-1 (SHIP) deficiency significantly increases the number of hematopoietic stem cells (HSCs) present in the bone marrow (BM). However, the reconstitution capacity of these HSCs is severely impaired, suggesting that SHIP expression might be an intrinsic requirement for HSC function. To further examine this question, we developed a model in which SHIP expression is ablated in HSCs while they are resident in a SHIP-competent milieu. In this setting, we find that long-term repopulation by SHIP-deficient HSCs is not compromised. Moreover, SHIP-deficient HSCs from this model repopulate at levels comparable with wild-type HSCs upon serial transfer. However, when HSCs from mice with systemic ablation of SHIP are transplanted, they are functionally compromised for repopulation. These findings demonstrate that SHIP is not an intrinsic requirement for HSC function, but rather that SHIP is required for the BM milieu to support functionally competent HSCs. Consistent with these findings, cells that comprise the BM niche express SHIP and SHIP deficiency profoundly alters their function.

Managing the Operational Constraints in Ship Machinery Design and Installation: Synthesis of Design‐Based Failures for Improving the Structural Quality of Shipboard Systems

AbstractAlthough the relevant standards, technical innovations, international rules, and safety‐related regulations enforce the shipbuilding industry to improve the design and structural quality of the merchant ships, there are still many design‐based failures that are being encountered by operators during the service period. Design‐based failures that have an influence on the technical performance and operational efficiency cause minor or catastrophic consequences, increase human errors, and impair safety on board ships. This paper mainly focuses on examining the potential causes and effects of design‐based deficiencies in ship machinery space on board merchant ships by referring to the outcomes of experimental surveys, ship deficiency reports, and marine accident statistics. In addition, a shipyard‐centered information network on monitoring design‐based failures is proposed for managing the gaps between designers, operators, and equipment manufacturers. It encourages the shipyard organizations to enhance the design and structural quality of the shipboard systems.

Inappropriate Recruitment and Activity by the Src Homology Region 2 Domain-Containing Phosphatase 1 (SHP1) Is Responsible for Receptor Dominance in the SHIP-Deficient NK Cell

We have previously demonstrated that the NKR repertoire is profoundly disrupted by SHIP deficiency. This repertoire disruption is characterized by receptor dominance where inhibitory signals from 2B4 repress killing of complex targets expressing MHC class I and activating ligands. In this study, we examine the molecular basis of receptor dominance in SHIP-/- NK cells. In this study, we show that in SHIP-/- NK cells there is a pronounced bias toward the 2B4 long isoform. We have also characterized signaling molecules recruited to 2B4 in SHIP-/- NK cells. Interestingly, we find that approximately 10- to 16-fold more Src homology region 2 domain-containing phosphatase 1 (SHP1) is recruited to 2B4 in SHIP-/- NK cells when compared with wild type. Consistent with SHP1 overrecruitment, treatment with sodium orthovanadate or a novel inhibitor with micromolar activity against SHP1 restores the ability of SHIP-/- NK cells to kill Rae1+ RMA and M157+ targets. These findings define the molecular basis for hyporesponsiveness by SHIP-deficient NK cells.

Induced SHIP Deficiency Expands Myeloid Regulatory Cells and Abrogates Graft-versus-Host Disease

Graft-vs-host disease (GVHD) is the leading cause of treatment-related death in allogeneic bone marrow (BM) transplantation. Immunosuppressive strategies to control GVHD are only partially effective and often lead to life-threatening infections. We previously showed that engraftment of MHC-mismatched BM is enhanced and GVHD abrogated in recipients homozygous for a germline SHIP mutation. In this study, we report the development of a genetic model in which SHIP deficiency can be induced in adult mice. Using this model, we show that the induction of SHIP deficiency in adult mice leads to a rapid and significant expansion of myeloid suppressor cells in peripheral lymphoid tissues. Consistent with expansion of myeloid suppressor cells, splenocytes and lymph node cells from adult mice with induced SHIP deficiency are significantly compromised in their ability to prime allogeneic T cell responses. These results demonstrate that SHIP regulates homeostatic signals for these immunoregulatory cells in adult physiology. Consistent with these findings, induction of SHIP deficiency before receiving a T cell-replete BM graft abrogates acute GVHD. These findings indicate strategies that target SHIP could increase the efficacy and utility of allogeneic BM transplantation, and thereby provide a curative therapy for a wide spectrum of human diseases.

SHIP deficiency enhances HSC proliferation and survival but compromises homing and repopulation

AbstractThe SH2 domain–containing inositol 5′-phosphatase-1 (SHIP) has the potential to modulate multiple signaling pathways downstream of receptors that impact hematopoietic stem cell (HSC) biology. Therefore, we postulated that SHIP might play an important role in HSC homeostasis and function. Consistent with this hypothesis, HSC proliferation and numbers are increased in SHIP–/– mice. Despite expansion of the compartment, SHIP–/– HSCs exhibit reduced capacity for long-term repopulation. Interestingly, we observe that SHIP–/– stem/progenitor cells home inefficiently to bone marrow (BM), and consistent with this finding, have reduced surface levels of both CXCR4 and vascular cell adhesion marker-1 (VCAM-1). These studies demonstrate that SHIP is critical for normal HSC function, homeostasis, and homing.