DESIGN, ENGINEERING, AND ASSESSMENT OF MOBILE MINEFIELDS

Naval mine warfare typically supports a sea denial strategy through the denial and/or delay of the enemy’s use of the water space or by controlling sea traffic in a designated area. Sea mines have been effective for decades. However, with technological progress, mine countermeasure (MCM) efforts have reduced the risks of a minefield by detecting and/or neutralizing mines to establish and maintain a Q-route for safe passage. The concept of a mobile minefield is proposed to increase the difficulty of the enemy’s MCM and improve the survivability of the minefield by adding mobility. This research explores both the physical design concepts and the operational effectiveness of mobile mines based on simulations and models. The simulation results show that, compared to static mines, mobile mines improved the number of enemy ships destroyed by at least 200% and increased the time it took the enemy to transition through the minefield by 50%. The results suggest that the mobile minefield would be operationally useful for the Department of the Navy and this technology is worth pursing and exploring.Distribution Statement A. Approved for public release: Distribution is unlimited.Captain, Singapore ArmyCaptain, Singapore ArmyMajor, Singapore ArmyLieutenant, Taiwan NavyMajor, United States ArmyCivilian, Department of the NavyLieutenant, United States NavyCivilian, Singapore Technologies Engineering, SingaporeMajor, Singapore ArmyMajor, Singapore ArmyMajor, Singapore ArmyCommander, United States NavyCivilian, Defense Science and Technology Agency (DSTA), SingaporeMajor, Singapore ArmyMajor, Republic of Singapore Air ForceTenente-Coronel, Brazilian Air ForceLieutenant, United States NavyCivilian, Department of the ArmyMajor, Singapore ArmyMajor, Israel Defense ForcesCivilian, Defense Science Organisation, SingaporeCaptain, Singapore Arm

Avicin D: A Protein Reactive Plant Isoprenoid Dephosphorylates Stat 3 by Regulating Both Kinase and Phosphatase Activities

Avicins, a class of electrophilic triterpenoids with pro-apoptotic, anti-inflammatory and antioxidant properties, have been shown to induce redox-dependant post-translational modification of cysteine residues to regulate protein function. Based on (a) the cross-talk that occurs between redox and phosphorylation processes, and (b) the role of Stat3 in the process of apoptosis and carcinogenesis, we chose to study the effects of avicins on the processes of phosphorylation/dephosphorylation in Stat3. Avicins dephosphorylate Stat3 in a variety of human tumor cell lines, leading to a decrease in the transcriptional activity of Stat3. The expression of Stat3-regulated proteins such as c-myc, cyclin D1, Bcl2, survivin and VEGF were reduced in response to avicin treatment. Underlying avicin-induced dephosphorylation of Stat3 was dephosphorylation of JAKs, as well as activation of protein phosphatase-1. Downregulation of both Stat3 activity and expression of Stat 3-controlled pro-survival proteins, contributes to the induction of apoptosis in avicin treated tumor cells. Based on the role of Stat3 in inflammation and wounding, and the in vivo inhibition of VEGF by avicins in a mouse skin carcinogenesis model, it is likely that avicin-induced inhibition of Stat3 activity results in the suppression of the pro-inflammatory and pro-oxidant stromal environment of tumors. Activation of PP-1, which also acts as a cellular economizer, combined with the redox regulation by avicins, can aid in redirecting metabolism from growth promoting anabolic to energy sparing pathways

Graphene-Based Nanocomposites for Energy Storage

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene-based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene-based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H2) storage and high-performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)-ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)-ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage-related applications are discussed

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Development and validation of a multidimensional short version Zarit Burden Interview (ZBI-9) for caregivers of persons with cognitive impairment

Background: There is a lack of appreciation of the full dimensionality of the original 22-item Zarit Burden Interview (ZBI) in the development of short versions. Existing short versions are premised upon a 1-factor or 2-factor structure or statistical techniques for item selection. Thus, there is a need for ZBI short versions that considers the multidimensional constructs of role strain, personal strain, and worry about performance (WaP) during item selection to provide a more holistic and comprehensive evaluation. Purpose: To develop and validate a short version of ZBI through a combined quantitative and qualitative approach that incorporates the validated 4-factor structure of role strain demands; role strain-control; personal strain, and WaP. Patients: We studied 202 caregivers of patients with dementia (84.2%) or mild cognitive impairment (15.8%) attending a memory clinic in Singapore. Methods: Confirmatory factor analysis and qualitative considerations from expert consensus were used for item selection. Confirmatory factor analysis fit statistics support the 4-factor structure. The 9-item ZBI-9 showed good internal consistency (Cronbach’s α=0.87) and convergent validity with anxiety and depression (Pearson correlation: Hospital Anxiety and Depression sub-scales, r≥0.56, P<0.001; ZBI- 22, r=0.95, P<0.001). Using a cut-off score of ≥13, ZBI-9 displayed good discriminatory ability for depressive symptoms (area under curve=0.79, P<0.001; sensitivity=70%, specificity=75%). The ZBI-9 also displayed comparable performance to the 22-item full version and three 12-item short versions. Conclusion: The ZBI-9 is a multidimensional short-version assessment tool for caregivers of persons with dementia and mild cognitive impairment that is reliable, valid, and discriminates depressive symptoms.Published versionThe research was funded by the Ng Teng Fong Healthcare Innovative Program, Singapore (NTF_JUN2018_I_C1_C_02)

The adoption of deep learning interpretability techniques on diabetic retinopathy analysis:a review

Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence of diabetes. There are challenges such as the dearth of ophthalmologists, healthcare resources, and facilities that are unable to provide patients with appropriate eye screening services. As a result, deep learning (DL) has the potential to play a critical role as a powerful automated diagnostic tool in the field of ophthalmology, particularly in the early detection of DR when compared to traditional detection techniques. The DL models are known as black boxes, despite the fact that they are widely adopted. They make no attempt to explain how the model learns representations or why it makes a particular prediction. Due to the black box design architecture, DL methods make it difficult for intended end-users like ophthalmologists to grasp how the models function, preventing model acceptance for clinical usage. Recently, several studies on the interpretability of DL methods used in DR-related tasks such as DR classification and segmentation have been published. The goal of this paper is to provide a detailed overview of interpretability strategies used in DR-related tasks. This paper also includes the authors’ insights and future directions in the field of DR to help the research community overcome research problems. GRAPHICAL ABSTRACT: [Image: see text

Nanomedicine-mediated therapies to target breast cancer stem cells

Accumulating evidences have suggested the existence of breast cancer stem cells (BCSCs), which possess the potential of both self-renewal and differentiation. The origin of BCSCs might have relationship to the development of normal mammary stem cells. BCSCs are believed to play a key role in the initiation, recurrence and chemo- and/or radiotherapy resistances of breast cancer. Therefore, elimination of BCSCs is crucial for breast cancer therapy. However, conventional chemo and radiation therapies cannot eradicate BCSCs effectively. Fortunately, nanotechnology holds great potential for specific and efficient anti-BCSCs treatment. Smart nanocarriers can distinguish BCSCs from the other breast cancer cells and selectively deliver therapeutic agents to the BCSCs. Emerging findings suggest that BCSCs in breast cancer could be successfully inhibited and even eradicated by functionalized nanomedicines. In this review, we focus on origin of BCSCs, strategies used to target BCSCs, and summarize the nanotechnology-based delivery systems that have been applied for eliminating BCSCs in breast cancer