Well Testing of Fracture Corridors in Naturally - fractured Reservoirs (NFR)

Geological folding and/or faulting may create fractured reservoirs containing a semi-parallel system of long, sparsely - spaced fracture corridors separated by exclusion zones. Presently, the best method for detecting and assessing fracture corridor networks requires drilling, logging, and coring from horizontal wells. However, there is no method to evaluate such reservoirs by pressure testing vertical wells. Vertical wells - completed either in highly-conductive corridors (fracture wells) or in the exclusion zone (matrix wells) would respond quite differently to well testing. Therefore, their pressure response patterns can be used to identify well\u27s placement in the corridor system and some other properties such as permeability of the exclusion zone, for example. (The actual permeability of the exclusion zone - due to diffuse fractures - is higher than the rock matrix permeability measured on the core samples.) The objective of this study is to apply the well flow testing analysis technique to estimate well’s location, permeability of the exclusion zone, distance from well to fracture corridor, corridor length, and conductivity. In this study, pattern recognition technique is used to analyze diagnostic plots of pressure drawdown generated by simulated flow tests with commercial software (CMG). A unique simulation model has been built by combining a local model of fracture well or matrix well with adjacent fracture corridor and a homogenized global model of the remaining corridor network. The global model generalizes the corridor network using single-porosity and radial permeability approach. The approach is verified as being sufficiently accurate. The results show that diagnostic plots of bottom hole pressure response to constant production rate for the matrix and fracture wells clearly indicate the well\u27s location as the plot patterns are quite different. Moreover, for matrix well (completed outside the fracture corridor) permeability of the exclusion zone and well-to-corridor distance can be determined from the initial radial flow regime after removing the wellbore storage effect by β-deconvolution. It is also shown that for fracture well (intercepting fracture corridor) diagnostic plot of the bilinear flow regime provides data for finding the fracture corridor conductivity and fracture corridor length. The corridor length, however, can be estimated with more precision from the pseudosteady-state flow regime plot representing reservoir boundary and reservoir shape factor effects. However, the approach is only practical for production rather than transient flow testing. This study also employs statistics - the cumulative logit models - to qualify accuracy of two techniques: finding permeability of the exclusion zone and distance from the well to the nearest corridor. The results show that the more distant the well from the corridor and the lower the exclusion zone permeability the more accurate permeability estimation becomes. Also, accuracy of the well-corridor distance estimation improves for longer corridors and lower permeable exclusion zones

Inferring Mobile Payment Passcodes Leveraging Wearable Devices

Mobile payment has drawn considerable attention due to its convenience of paying via personal mobile devices at anytime and anywhere, and passcodes (i.e., PINs) are the first choice of most consumers to authorize the payment. This work demonstrates a serious security breach and aims to raise the awareness of the public that the passcodes for authorizing transactions in mobile payments can be leaked by exploiting the embedded sensors in wearable devices (e.g., smartwatches). We present a passcode inference system, which examines to what extent the user's PIN during mobile payment could be revealed from a single wrist-worn wearable device under different input scenarios involving either two hands or a single hand. Extensive experiments with 15 volunteers demonstrate that an adversary is able to recover a user's PIN with high success rate within 5 tries under various input scenarios

WristSpy: Snooping Passcodes in Mobile Payment Using Wrist-worn Wearables

Mobile payment has drawn considerable attention due to its convenience of paying via personal mobile devices at anytime and anywhere, and passcodes (i.e., PINs or patterns) are the first choice of most consumers to authorize the payment. This paper demonstrates a serious security breach and aims to raise the awareness of the public that the passcodes for authorizing transactions in mobile payments can be leaked by exploiting the embedded sensors in wearable devices (e.g., smartwatches). We present a passcode inference system, WristSpy, which examines to what extent the user's PIN/pattern during the mobile payment could be revealed from a single wrist-worn wearable device under different passcode input scenarios involving either two hands or a single hand. In particular, WristSpy has the capability to accurately reconstruct fine-grained hand movement trajectories and infer PINs/patterns when mobile and wearable devices are on two hands through building a Euclidean distance-based model and developing a training-free parallel PIN/pattern inference algorithm. When both devices are on the same single hand, a highly challenging case, WristSpy extracts multi-dimensional features by capturing the dynamics of minute hand vibrations and performs machine-learning based classification to identify PIN entries. Extensive experiments with 15 volunteers and 1600 passcode inputs demonstrate that an adversary is able to recover a user's PIN/pattern with up to 92% success rate within 5 tries under various input scenarios

Effects of suppressor of cytokine signaling 3 (SOCS3) on the development of colon cancer via regulation of HIF-1α

Purpose: To investigate the influence of suppressor of cytokine signaling 3 (SOCS3) on rats with colon cancer (CC). Methods: Sprague-Dawley (SD) rats were randomly divided into CC group and control group. CC models were constructed. The expression of SOCS3 in CC tissues was determined by quantitative real time-polymerase chain reaction (qRT-PCR). Hematoxylin-eosin staining (H&E) was used to examine colon tissue morphology, while immunohistochemistry (IHC) staining assay was performed to determine the expression of SOCS3 protein in colon tissues. The content of HIF-1α, phosphorylated phosphatidylinositol 3-hydroxy kinase (p-PI3K), and phosphorylated protein kinase B (p-AKT) proteins was determined by Western blotting (WB). Results: Compared with that in the control group, the number of tumors in the CC group was significantly increased (p < 0.05). Protein and messenger ribonucleic acid (mRNA) expressions of SOCS3 were down-regulated in CC group (p < 0.05), while protein expressions of p-PI3K, p-AKT and HIF-1α were significantly elevated in CC group (p < 0.05). Conclusion: SOCS3 is poorly expressed in CC rats, and promotes the expression of HIF-1α by activating PI3K/AKT signaling pathway. The findings, thus, provide a probable strategy for management of colon cancer

Ecological Balance of Oral Microbiota is Required to Maintain Oral Mesenchymal Stem Cell Homeostasis

Oral microbiome is essential for maintenance of oral cavity health. Imbalanced oral microbiome causes periodontal and other diseases. It is unknown whether oral microbiome affect oral stem cells function. In this study, we used a common clinical anti-biotic treatment approach to alter oral microbiome ecology and examine whether oral mesenchymal stem cells (MSCs) are affected. We found that altered oral microbiome resulted gingival MSCs deficiency, leading to a delayed wound healing in male mice. Mechanistically, oral microbiome release LPS that stimulates the expression of microRNA-21 (miR-21) and then impair the normal function of gingival MSCs and wound healing process through miR-21/Sp1/TERT pathway. This is the first study indicate that interplay between oral microbiome and MSCs homeostasis in male mice

Effects of SOCS3 on the development of colon cancer via regulation of HIF-1α

Purpose: To investigate the influence of suppressor of cytokine signaling 3 (SOCS3) on rats with colon cancer (CC). Methods: Sprague-Dawley (SD) rats were randomly divided into CC group and control group, and then CC rat model was constructed. The expression of SOCS3 in CC tissues was determined by quantitative real time-polymerase chain reaction (qRT-PCR). Hematoxylin-eosin staining (H&E) was used to examine colon tissue morphology. Immunohistochemistry (IHC) staining assay was performed to determine the expression of SOCS3 protein in colon tissues. The contents of HIF-1α, phosphorylated phosphatidylinositol 3-hydroxy kinase (p-PI3K), and phosphorylated protein kinase B (p-AKT) proteins were determined by Western blotting (WB). Results: Compared with that in the control group, the number of tumors in CC group was significantly increased (p < 0.05). 2). On the other hand, protein and message ribonucleic acid (mRNA) expressions of SOCS3 were down-regulated in CC group (p < 0.05). 3), while protein expressions of p-PI3K, p-AKT and HIF-1α were raised in CC group (p < 0.05). Conclusion: SOCS3 is lowly expressed in CC rats, and promotes the expression of HIF-1α by activating PI3K/AKT signaling pathway. Thus, SOCS3 provides a therapeutic strategy for the management of colon cancer. Keywords: Colon cancer; Suppressor of cytokine signaling protein 3 (SOCS3); Hypoxia inducible factor-1

Multidimensional Resource Fragmentation-Aware Virtual Network Embedding in MEC Systems Interconnected by Metro Optical Networks

The increasing demand for diverse emerging applications has resulted in the interconnection of multi-access edge computing (MEC) systems via metro optical networks. To cater to these diverse applications, network slicing has become a popular tool for creating specialized virtual networks. However, resource fragmentation caused by uneven utilization of multidimensional resources can lead to reduced utilization of limited edge resources. To tackle this issue, this paper focuses on addressing the multidimensional resource fragmentation problem in virtual network embedding (VNE) in MEC systems with the aim of maximizing the profit of an infrastructure provider (InP). The VNE problem in MEC systems is transformed into a bilevel optimization problem, taking into account the interdependence between virtual node embedding (VNoE) and virtual link embedding (VLiE). To solve this problem, we propose a nested bilevel optimization approach named BiVNE. The VNoE is solved using the ant colony system (ACS) in the upper level, while the VLiE is solved using a combination of a shortest path algorithm and an exact-fit spectrum slot allocation method in the lower level. Evaluation results show that the BiVNE algorithm can effectively enhance the profit of the InP by increasing the acceptance ratio and avoiding resource fragmentation simultaneously