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The need to integrate Early Warning System (EWS) with Disaster Risk Reduction (DRR) has long been recognized in several global forums. In the year 2006, the United Nations International Strategy for Disaster Reduction (UNISDR) proposed an Integrated Risk-based EWS (IR-EWS) by integrating four elements: (1) Monitoring and warning service; (2) Risk knowledge; (3) Dissemination and communication; and (4) Response capability. Nearly after two decades of the UNISDR proposal, our study finds that there are still gaps in making IR-EWS operational. Our study also finds that works on conceptualizing integration of resilience against disaster with EWS as part of DRR (in line with SDG-13) has not yet been started. Against this backdrop, in this study we developed an IR-EWS for flood termed as Dynamic Flood Risk Model (DFRM) which contains: (1) simple risk-based warning numbers which are easily understandable and communicable to the community, with risk considered as a proxy for resilience; and (2) capital-based action plans in relation to community capital to reduce disaster risk and increase community resilience against disaster. The DFRM is applied in two flood-prone districts in Bangladesh and found to be acceptable to the community with reasonable accuracy. The model is the customized version of flood for generic IR-EWS. This study can be considered as the first attempt of the next generation IR-EWS where risk is represented by simple warning numbers and where EWS (as part of DRR) can be applied to increase the resilience.

The bifacial photovoltaics (PV) technology promises several advantages over monofacials, including improved energy yield, lower operating temperature, and easier integration with agrophotovoltaics. There have been various experimental or computational studies comparing bifacials to monofacials; however, a theory-experiment combined analysis for accurate worldwide extrapolation is missing. Literature review reveals that many reported experiments study standalone systems that overrepresent the yield performance obtainable in farms. Moreover, most reported experimental studies are for configurations that are not necessarily designed close to the optimum. In this work, we experimentally study and analyze the fixed-tilted bifacial farm configiurations, namely south-facing monofacial, south-facing tilted bifacial (TBF), and ground-sculpted vertical bifacial (VBF) arrays, at Dhaka, Bangladesh (23.7 °N, 90.4 °E). The optimal TBF configuration, for 0.5 albedo, yields 21.3% and 73.3% more than the optimal monofacial and the optimal VBF configurations, respectively. Through a combination of experimental and numerical analysis, we compare the in-array performance of the configurations under different albedo conditions to analyze the physics and consolidate the predictions. There is a growing interest in PV array configurations beyond the conventionally ground-mounted south-facing TBF, such as agrophotovoltaics, floating-PV, industry-roof PV array, etc. This necessitates a critical analysis of various array configurations for broader PV expansion.

Bangladesh's vulnerability to storm surge and success in reducing their impacts on the coastal communities are well-known. However, global warming is expected to increase both the frequency and the intensity of tropical cyclones. Also, the country still lacks in good quality data and information that can offer enhanced services to effectively design coastal defense systems and adapt to climate changes. This study developed a storm surge inundation model and database using the available tropical cyclones' database and simulated inundation for the past 31 cyclones in the Bay of Bengal, near the coastal regions of Bangladesh. The model uses a suite of Delft3D hydrodynamic and Delft Dashboard cyclone models. The model was calibrated and validated for two major cyclones, namely Sidr and Aila, using the available data for different bed roughness, track sources, and wind drag coefficient conditions. The results suggested that spatially varying bed roughness and wind varying drag conditions provide a more reliable prediction of inundation over the coast. The results also show that historical track data from Indian Meteorological Department optimize the model performances. The inundation database indicates that depending on the intensity and location, tropical cyclones can cause the maximum inundation of 1–5 m in the coastal lands of Bangladesh. More than 70% of the storms lead to the maximum inundation of more than 2 m, and about 25 and 7% of the storms can cause the maximum inundation of more than 3 and 4 m, respectively. The study also discusses the potential applications and shares insights on the implications of the inundation database that can offer improved information for enhanced climate services in Bangladesh. The database can be advanced with information about sectoral loss and damage as well as citizen science that will not only provide necessary information to design coastal protection structures and emergency measurements but also contribute to build long-term climate adaptation plans in the data-scarce region.

For the policy makers, risk-based planning to minimize future climatic risk needs decision on investment priority. This is particularly important where there are resource constraints, and in cases where the decisions depend on socio-political reality of the region. For the policy makers, it is also extremely important to know how a system will behave if investment is made on any specific adaptation in any specific location to minimize climatic risk in the region. To answer these questions, an Adaptation Model is developed in this study to compute adaptation deficiency for a location that will minimize climatic risk in that location. In this methodology, a system approach is followed by applying non-linear programming. The non-linear programming system is formulated by defining future climatic risk as the objective function where the risk is a non-linear function of hazard, exposure, vulnerability, where vulnerability is a linear combination of sensitivity and adaptive capacity. The system is restricted by seven constraints composed of different combinations of hazard, exposure, sensitivity and adaptive capacity. The model can be applied in any part of the world, for any climatic hazard, and for any time domain. In this study, the model is applied in Bangladesh coastal zone to compute adaptation deficiency required to be filled to minimize mid-century storm surge risk in the identified hotspots. The results show that out of 20 identified storm surge risk hotspots in Bangladesh coastal zone, cyclone shelter has the maximum adaptation deficiency in 10 hotspots followed by plantation in 8 hotspots. The output from the model can be used by the policy makers to decide on the most appropriate investment options for risk-based planning that will minimize future risks in the identified hotspots. The model shows the risk limit below which risk cannot be reduced. Any investment attempt on adaptation to reduce the risk beyond this limit will disrupt the system equilibrium and will make this investment a surplus.

A community level field survey is conducted in the coastal zone of Bangladesh to assess the effectiveness of five selected planned adaptations against storm surge in micro scale which are already proved effective in macro scale. The five selected planned adaptations are: cyclone shelter, plantation, paka & semi-paka house, loan, and communication infrastructure. The selected study area is well-known for storm surge hazard. The study site and sample size are selected by using Probability Proportional to Size (PPS) and cluster sampling methods. Semi-structured household questionnaire, Focus Group Discussion (FGD), and Key Informative Interviews (KII) were conducted for understanding community perceptions on adaptations. Effectiveness of planned adaptations are assessed by applying an Index developed by using five-point Likert scale. Barriers against the adaptations are assessed by probabilistic analysis and represented by Venn diagram. Interrelationships among the adaptations are assessed through causal relation network. The study results show a mismatch of effectiveness of planned adaptations between the macro scale and micro scale. It is found that cyclone shelter, paka & semi-paka house, loan, and communication infrastructure do not exhibit a similar level of effectiveness in micro scale as these are expected to be effective in macro scale. Among the five selected planned adaptations, plantation is the only adaption which is found to be effective in both micro scale and macro scale because of its high economic return for the community. The reasons for the mismatch of this effectiveness between macro scale and micro scale are – barriers and causal relation for these adaptations in micro scale are not considered in macro scale. A comprehensive analysis is recommended to ensure a similar level of effectiveness of an adaptation both in macro scale and in micro scale.

We propose a physics-based analytical model for gate capacitance-voltage characteristics of ultra-thin-body III - V-on-insulator (XOI) MIS structure. The accuracy of the analytical model is verified by comparing with TCAD results. The model is general and is applicable to different III-V channel materials.

The five senses of sight, sound, smell, touch, and taste define the world for us. Sensing technologies augment these primary sensing capabilities: Mechanical sensors broaden our perception of the world by being sensitive to objects that we cannot ‘sense’ and then translate it in a format so that we can. A false color-map of galaxies produced by a radio-telescope, the trajectories in a bubble-chamber of a subatomic particle, the sound of a carbon monoxide alarm, or an MRI image of the brain are all translations of information adapted specifically for us. It is hardly surprising, therefore, that the history of sensors parallels the development of science and technology.

The influences of the intermediate band (IB) filling, the absorption coefficient constants, and the IB position on the efficiency of a quantum dot intermediate band solar cell (QD-IBSC) are investigated considering the spatial variation of subbandgap generation rates. A new definition of optimal intermediate band filling is proposed. A mathematical model is developed to optimize the intermediate band solar cell (IBSC) structure under idealized conditions, which calculates the optimal ratio of the subbandgap absorption coefficient constants and the optimal position of IB.

Impact of storm surge largely varies depending on the tidal phase during the landfall of a tropical cyclone. This study investigates comparative variance in inundation condition and thrust force for an identical cyclone during low tide and high tide by applying a numerical model (Delft3D) and a semi-analytical model (DFM). A moderate strength cyclone, Mora, which made landfall on Bangladesh coast in May 2017 is selected to study its impact on land during low tide and high tide. Actual landfall time of Mora was during low tide. To study the impact of storm surge during high tide, a synthetic cyclone is created which has similar strength and track to that of Mora but makes landfall during high tide. The results show that inundation depth, inundation extent, and thrust force increase when a cyclone makes landfall during high tide compared to the condition when the cyclone makes landfall during low tide. But the relation between storm surge impact and tidal phase is not linear. It depends on the land topography of the location, direction of cyclone movement, direction and magnitude of water velocity and wind velocity, gradients of water surface and wind velocity, and proximity and position of the location with respect to cyclone track.

Anemia is a critical medical condition in public health concern in tropical and subtropical areas, and understanding its hematological changes is crucial for improving diagnosis, treatment, and prognosis.It manifests through symptoms like weakness, fatigue, pale skin, and shortness of breath due to insufficient hemoglobin or red blood cells to carry adequate oxygen, with severe cases leading to complications such as chest pain. Common causes include blood loss, chronic diseases, and iron and vitamin deficiencies. This dataset captures various hematological parameters of patients suffering from anemia, including sex, age, Hemoglobin level (Hb), oxygen transportation (RBC), packed cell volume (PCV), mean corpuscular volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean corpuscular hemoglobin concentration (MCHC). The data is systematically collected from patients admitted to Aalok Healthcare Ltd., situated in Dhaka, Bangladesh., offering an opportunity to analyze hematological variations in patients with anemia. By providing a worldwide viewpoint for comparing hematological responses, this dataset aids in the development of prediction models for the severity of anemia and patient outcomes, improving clinical decision-making. The study examines how various treatment plans can affect blood characteristics, potentially leading to improved treatment strategies. For statistical analysis, the data is cleaning the noise (null and duplicate values), normalized, and encoded. The Chi-square test results indicate a p-value of 4.1929×10−29, showing no significant association between gender and diagnostic outcomes. However, the Z-test and T-test results reveal a notable gender difference in hemoglobin levels, with p-values of 3.4789×10−33 and 4.1586×10−24, respectively, underscoring the relevance of gender in analyzing hemoglobin variations. These findings emphasize how gender influences hematological responses against Anemia. The dataset will greatly advance research on anemia, improve these critical medical terms in public health strategies, and enhance patient diagnosis and treatment methods, offering a distinct advantage.

We investigate the effect of varying the top barrier thickness on the gate C–V characteristics of InGaAs and InSb MOS-HEMT devices. The gate capacitance of these devices exhibits a sharp increase at certain gate voltages under both accumulation and inversion bias. The gate voltages at which some of these sharp changes occur depend on the thickness of the top barrier layer. The sharp rise in gate capacitance appears as a peak in the derivative of the capacitance with respect to the gate voltage. The positions of certain peaks of the derivative as a function of the gate voltage give information on the thickness of the top barrier layer. By exploiting this trend it is possible to extract the barrier thickness from the gate C–V characteristics. Keywords: III-V semiconductor, Gate capacitance, MOS-HEMT, Barrier thickness, Characterization

Abstract This research investigates the Circle of Willis, a critical vascular structure vital for cerebral blood supply. A modified novel dual‐pathway multi‐scale hierarchical upsampling network (HUNet) is presented, tailored explicitly for accurate segmentation of Circle of Willis anatomical components from medical imaging data. Evaluating both the multi‐label magnetic resonance angiography region of interest and the multi‐label magnetic resonance angiography whole brain‐case datasets, HUNet consistently outperforms the convolutional U‐net model, demonstrating superior capabilities and achieving higher accuracy across various classes. Additionally, the HUNet model achieves an exceptional dice similarity coefficient of 98.61 and 97.95, along with intersection over union scores of 73.32 and 85.76 in both the multi‐label magnetic resonance angiography region of interest and the multi‐label magnetic resonance angiography whole brain‐case datasets, respectively. These metrics highlight HUNet's exceptional performance in achieving precise and accurate segmentation of anatomical structures within the Circle of Willis, underscoring its robustness in medical image segmentation tasks. Visual representations substantiate HUNet's efficacy in delineating Circle of Willis structures, offering comprehensive insights into its superior performance.

Prostate cancer is a prevalent and life-threatening disease characterized by abnormal cell growth within the prostate gland. Early and accurate diagnosis of prostate cancer is crucial for effective treatment planning. Magnetic Resonance Imaging (MRI) is valuable for diagnosing and assessing prostate cancer. Medical professionals use MRI to create segmentation for detecting prostate cancer. However, existing segmentation methods are limited in accurately delineating anatomical structures and tumor regions within the prostate. This research proposes an innovative methodology for advancing MRI-based prostate segmentation. The objective is to encompass anatomical and tumor zones within the prostate, facilitating precise diagnosis and treatment planning. The proposed dual-pathway multi-scale hierarchical upsampling network introduces significant modifications compared to the traditional UNet-based architecture. It outperforms previous studies, demonstrating superior performance in anatomical segmentation on both the ProstateX and Prostate158 datasets. It achieves an intersection over union of 0.8449 and a dice similarity coefficient of 0.9872 on ProstateX, as well as an intersection over union of 0.8065 and a dice similarity coefficient of 0.9831 on Prostate158, suppressing previous research by a significant margin. These results highlight the potential of this approach to advance the utility of MRI in diagnosing and planning the treatment of prostate-related pathologies, benefiting both patients and healthcare practitioners.

Matrix–matrix multiplication is of singular importance in linear algebra operations with a multitude of applications in scientific and engineering computing. Data structures for storing matrix elements are designed to minimize overhead information as well as to optimize the operation count. In this study, we utilize the notion of the compact diagonal storage method (CDM), which builds upon the previously developed diagonal storage—an orientation-independent uniform scheme to store the nonzero elements of a range of matrices. This study exploits both these storage schemes and presents efficient GPU-accelerated parallel implementations of matrix multiplication when the input matrices are banded and/or structured sparse. We exploit the data layouts in the diagonal storage schemes to expose a substantial amount of fine-grained parallelism and effectively utilize the GPU shared memory to improve the locality of data access for numerical calculations. Results from an extensive set of numerical experiments with the aforementioned types of matrices demonstrate orders-of-magnitude speedups compared with the sequential performance.

Although ABO incompatible kidney transplantations are increasingly being practised worldwide, in Bangladesh it was never attempted. Here we report the first ever ABO incompatible kidney transplantation case performed in Bangladesh. The patient was a 23-year-old male with end-stage kidney disease secondary to chronic glomerulonephritis on haemodialysis. The only kidney donor available was his mother who had a different blood-group (patient O positive; mother A positive). His baseline anti-A IgG titre was 1:128. We used a modified desensitization protocol with low-dose Rituximab, triple immunosuppression (Tacrolimus, Mycophenolate Sodium and Prednisolone) and 3 sessions of plasmapheresis followed by IVIG. His Anti-A IgG titre was brought down to 1: 8 before transplantation. He also received basiliximab as induction therapy. He successfully underwent renal transplantation across the ABO barrier. After transplantation his IgG titre was monitored which was remained 1:4. At 1, 3 and 6 months of post transplant, serum creatinine level was 207 µmol/L, 182 µmol/L and 183 µmol/L, respectively. This was the first case of ABO-incompatible kidney transplantation in Bangladesh. This case gives us the confidence that more ABO-incompatible kidney transplantations can be performed in a resource limited setting and high infection risk countries like ours following a more cautious approach. This will substantially increase the living kidney donor pool; hence reduce the economic and health impact of continuing long term dialysis therapy in Bangladesh. Keywords: ABO incompatible kidney transplantation, Anti-A IgG titre, Desensitization, Plasmapheresis, End Stage Kidney Disease