Search

Nowadays, heat, ventilation and air conditioning system are an essential part in a building. In order to achieve energy saving, the heating, ventilation, and air conditioning (HVAC) system have to enhance the designs of their various types of integrated electrical and mechanical components so that to control and operate plant optimally. This paper presented the development of smart sensor controller for heat, ventilation and air conditioning system by using Arduino. Smart sensor controller can be regarded a device that can control the speed of the motor based on the number of person detected by the infrared sensor. The motor used in this project will represent the fan motor of the normal air conditioner. The objective of the smart sensor controller is to prove the energy saving concept and to reduce the electrical consumption for the HVAC system. The experiment conducted show that the implementation of the smart sensor controller provides an average energy saving efficiency of 45.13 % compare to HVAC system without smart sensor controller.

The reduction of operation and maintenance costs as well as the improvement of reliability of wind energy conversion systems are of top priorities in the renewable energy industry as the demand for wind energy continuously grow tremendously. With that, the condition monitoring system (CMS) plays a crucial role in maximizing the potential of wind energy in generating electricity. Therefore, this review paper vividly captures the fact that the recent advancements in embedded control in CMS in wind energy conversion systems are able deliver tangible benefits to the renewable energy technology (RET) industry as a whole. It is proven that CMS based maintenance is deemed to be more suitable in multiple aspects with fewer drawbacks, as compared to scheduled and corrective maintenance. In this review paper, an attempt to evaluate the viability of CMS is being made. The main purpose is to shed some light on the significant contributions provided by CMS in shortening the downtime and increasing the production rate of the wind energy conversion system. Forthcoming promising applications with good potential to surpass the recent dilemmas were also explored and analyzed at the end of this paper.

Millimeter Wave (mm-wave) technology is a prerequisite to ensure ubiquitous wireless communication, given the rapid growth of the Internet of Things (IoT) infrastructure that integrates emerging technologies such as virtual reality (VR), artificial intelligence (AI), etc. However, to ensure the future growth and acceptance of this technology, a highly efficient mm-wave compatible transceiver hardware is essential to be developed. A low noise amplifier (LNA) is one of the modules that directly influences the performance of an IoT transceiver. Numerous approaches have thus far been deployed in LNA design, such as differential cascode topology, active inductor, embedded input balun, transformer-based feedback, current reuse, stacked structure, and body biasing, to standardize various parameters e.g. die area, gain, noise figure, linearity, and power efficiency. Although complementary metal–oxide–semiconductor (CMOS) technology-based current LNA architectures in the mm-wave range suffer from substrate losses and device parasitic, it is regarded as a competitive solution for THz communication due to its inherent benefits of low-cost integrity, which promotes CMOS LNA design as an emerging research topic. This review presents several CMOS LNA architectures and perceives the adjustments of circuit topologies to ratify LNA structures in mm-wave applications. Furthermore, various state-of-the-art LNA design features are compared to envision CMOS LNA design directions and identify apposite circuit techniques suitable for the imminent 6G communication protocol. Therefore, this review will serve as a comparative study and reference for the future LNA design for the mm-wave sensor transceiver applications.

In this study a coupled-eulerian–lagrangian (CEL) approach has been applied to assess the internal blast loading conditions, for the tunnel built in three layers of sandstone rock. The three weathered stages of sandstone have been considered in this study i.e., slightly, medium and also highly weathered sandstone in three different layers. The sandstone rock weathering increases as we move towards the ground surface from deep subsurface. The elastoplastic finite element model with varied overburden depth with dimensions of 60 m (L × B × H) each to incorporate different parametric cases. An explosive is assumed at the center of the tunnel, with the capacity of hundred kg of trinitrotoluene (TNT), the explosive is assumed to be hanging in the air inside the tunnel opening with equal distance from all sides. The TNT sphere and air that is inside the rock tunnel has been modelled through CEL technique to simulate actual in-situ condition. Through Mohr-Coulomb, Concrete Damage Plasticity, and Johnson-Cook constructive material model the elastoplastic behaviour of different materials like rock, steel bars and concrete has been simulated respectively. The cage of steel bars has been embedded through interaction constraint in concrete liner to produce reinforced concrete liner. In the initial stages of simulation with 5 m of overburden depth the tunnel has been placed in the upper layer of sandstone. For further analysis, the position of the tunnel has been changed for overburden depth of fifteen, twenty-five and thirty-five meter. In accordance with the result of the simulation, for rock in terms of acceleration, velocity, and dis-placement, the depth of the overburden and the displacement of the crown are inversely related. No damage in terms of compression is seen in this simulation, but in all instances, a small damage owing to tensile failure has been noted.

In this study, a time-variant baseline restorer (TV-BLR) circuit was designed and implemented to address the poor frequency selectivity issue in the shaping units of most state-of-the-art readout electronics for CdZnTe/CdTe detectors used in biomedical imaging applications. The proposed circuit improves image quality by canceling the artifacts that result from poor temporal and energy resolution in PET imaging. The proposed circuit consists of a Charge Sensitive Preamplifier (CSP) followed by a classical pole-zero compensation circuit. Two stages of integrators are added and a frequency rectifier module named the TV-BLR circuit has been built. The open-loop amplifier for the CSP is a single-ended input stage amplifier, designed for low-power applications with a maximum power consumption of 43 µW from a 1.2 V supply voltage, verified through post-layout Monte Carlo simulations. The TV-BLR increases the selectivity of the shaping filter, lowers the equivalent noise charge (ENC), and restores the baseline of the circuit to only 143 µV dc-offset. It also extends the counting rate behavior of the system by handling the time-over-threshold (ToT), which depends on the tail current (Itail) of the comparator stage. The circuit was designed, simulated, and validated for an input dynamic of 2–12.5fC, providing an energy range of 55.1–354.3 keV. The design has a charge-to-voltage conversion factor of 56.7 mV/fC with a 4% non-linearity error for an input detector capacitance of 200 fF, while achieving an optimal ENC of 57.4 e − RMS ± 0.1 e−/fC with 13.27 ns peaking time. Process Voltage Temperature (PVT) analysis was performed to validate the simulation results and performance metrics of the design. The proposed design improves energy resolution and avoids energy losses due to the readout system.

The current numerical study aims to investigate the effects of various rotating speeds of rotating cylinders on mixed convection and entropy generation in a lid-driven trapezoidal enclosure for fixed magnetic field inclination angle. Several water-based hybrid nanofluids are used as governing fluids. In this work, the impacts of SWCNT-water, Cu-water, and Al2O3-water nanofluids individually, as well as the effects of three different types of SWCNT-Cu-Al2O3-water hybrid nanofluids are examined. The average Nusselt number, average Sherwood number, average temperature, and average entropy generation because of heat transfer, diffusion, fluid friction, and the applied magnetic field as well as total entropy generation and Bejan number are evaluated as output parameters for different values of governing parameters. The Galerkin weighted residual finite element method is used to numerically solve the governing Navier-Stokes, thermal energy, and mass conservation equations. The optimal values of each governing parameter are established in order to produce the best results for the output parameters. To inspect the thermal and flow field within the trapezoidal enclosure as well as the variations in mass concentrations, isotherm contours, streamlines and isoconcentration contours are studied. Better performance is found for higher rotating speed regardless of other parameters.

Injection-locked frequency divider (ILFD) is an essential component of a phase-locked loop (PLL) used in a communication transceiver. Due to the rapid growth of virtual reality and artificial intelligence technologies, high-speed communication has become a crucial factor. As a result, highly efficient ILFDs must be engineered to ensure accurate high-speed communication. An optimized ILFD is anticipated to have a large locking range, a low power consumption, a low phase noise, and a low injection power for better functioning of a high speed PLL. However, there are inevitable trade-offs of frequency, phase noise, division ratio, and power consumption, making it more challenging to design an ILFD with a high division ratio at higher frequencies. Choosing an appropriate topology for different operational frequencies is also a challenging task for RFIC designers. This study exemplified different design architectures available for CMOS ILFDs in different super high frequency (SHF) and extremely high frequency (EHF) frequency ranges. The performance parameters of these architectures are analyzed, and a detailed discussion on the device’s performance is presented. This review will serve as a comparative study and reference for the RFIC designer’s future ILFD designs.

Since Covid-19 outbreak, billions of single used face masks (SUFM) are being used which pose a great concern in terms of environmental pollution – SUFM do not disintegrate easily. Reuse of used masks in concrete could be a pollution mitigating option. In this study, a unique series of testing program, incorporating pieced SUFM and powdered ladle furnace slag (LFS) in concrete, was considered. To prepare concretes, SUFM fibers were added as a volumetric replacement and LFS powder was added as supplementary cementitious material (SCM). Two different percentages (0.1% and 0.2%) and sizes (small: 5 × 20 mm and large: 5 × 40 mm) of SUFM fibers were used, and two different percentages (5% and 15%) of LFS were incorporated (along with SUFM) in concrete. Subsequently, control concretes, SUFM blended concretes, and SUFM-LFS blended concretes were prepared to carry out compressive strength tests, flexural strength tests, and sorptivity (i.e., capillary water absorption) tests. For SUFM blended concretes, the compressive strength and flexural strength results are found to be decreasing: 0.1% larger sized SUFM shows less decrease in strength (15.2% for compressive and 2.1% for flexure) when compared with control concretes. In the case of SUFM-LFS blended concretes, compressive strength is in decreasing trend whereas flexural strength is found to be increased with a peak increment of 8.3% compared to control concrete. In the case of sorptivity, higher amount of SUFM inclusion shows increased water absorption by concrete while larger amount of LFS inclusion produces concretes having less affinity to water. In general, larger sized SUFM blended concretes provide better concrete if compared with other blended samples.

The goal of the current numerical study is to determine how different magnetic field inclination angles along with Reynolds numbers affect mixed convective heat and mass transfer as well as entropy generation in a lid-driven trapezoidal enclosure with two rotating cylinders inside. As governing fluids, several water-based nanofluids and hybrid nanofluids with fixed solid volume fractions (5%) are employed. The impacts of three different types of SWCNT-Cu-Al2O3-water hybrid nanofluids, each made up of different ratios of SWCNT, Cu, and Al2O3 nanoparticles in water, are seen in this work, along with the effects of SWCNT-water, Cu-water, and Al2O3-water nanofluids separately. To obtain the results in the form of average Nusselt number, average Sherwood number, average temperature, and Bejan number as output parameters inside the enclosure for different magnetic field inclination angles (0° ≤ λ ≤ 90°) and other governing parameter values, the governing Navier-Stokes, thermal energy, and mass conservation equations are solved using the Galerkin weighted residual finite element method through numerical simulation. Then the simulation data is used to develop a novel artificial neural network model for efficient prediction. To achieve the best outcomes for the output parameters, the optimal values of each of these input parameters are determined by both FEM and ANN and a comparative study between these two is conducted. Cu-Al2O3-water hybrid nanofluid is used to test the performance of the developed ANN model for new cases. For each type of fluid in the present framework, maximum heat and mass transfer often take place when the magnetic field is applied at an inclined angle with respect to the horizontal axis. A satisfactory accuracy is obtained for the developed novel ANN model while predicting respective results. For training and validation data, it predicts convective heat and mass transfer with 96.81% accuracy and average dimensionless temperature and Bejan number with 98.74% accuracy. For test data, it predicts convective heat and mass transfer with 97.03% accuracy and average dimensionless temperature and Bejan number with 99.17% accuracy.

The past decade has witnessed rapid research and developments in wind energy conversion systems and related enabling technologies. The incorporation of wind turbines in the integral design of buildings has become a promising approach to promote on-site renewable energy conversion in urban areas. However, information pertaining the efficiency of the wind turbines, wind speeds and the integration of generated wind power to the grid in urban environments is scarce. This review paper aims to capture the fact that recent advancements in wind energy systems are able to deliver tangible benefits to the renewable energy technology (RET) industry as a whole. A comprehensive review has been carried out on the applied techniques of radial wind turbine (RWTs), contra-rotating wind turbines (CRWTs), hybrid Savonius–Darrieus rotor, piezoelectric generators, flag-type triboelectric nanogenerator and stretching-enhanced triboelectric nanogenerator. This paper provides a knowledge platform for readers to explore possible methods in exploiting the advantages of urban wind profiles with minimal vibration, noise and installation space. Unique approaches pertaining the developments of wind energy system in urban environments are reviewed and reported in this paper. Several research gaps are also identified to guide future study in urban wind energy conversion systems.

Monitoring of heavy metal concentrations in soil and their accumulation in vegetables grown in the newly shifted tannery area of Savar, Bangladesh, is crucial for human health. Heavy metals (i.e., Cr, Pb, Cu, Zn, Ni, and Cd) concentrations in soil and vegetable samples were determined by atomic absorption spectrophotometer (AAS). In soil, 3220 mg/kg Cr was observed, which was 32-fold greater than the WHO/FAO recommended limit. Ecological risk indices such as the contamination factor, enrichment factor, pollution load index, and geoaccumulation index showed metal levels as moderately to very highly contaminated. The non-carcinogenic risk (NCR) was found to be higher, and the carcinogenic risk (CR) exceeded the acceptable value 1 × 10−6 and posed greater risks to children than adults, especially for Cr in soil. The main exposure pathway for soil metals was 97.8–99.9% due to oral ingestion. The concentration of heavy metals especially Cr, Pb, Zn, and Cd, in vegetables was alarming as they crossed the safety limit. The calculated mean hazard index (8.71) for vegetable samples showed elevated levels of potential NCR, while CR for Cr and Cd, exceeded the acceptable limit of 1 × 10−6, indicating the probability of cancer risk to humans through the consumption of vegetables. This study revealed a to-and-fro analysis of the present scenario of the tannery area, giving importance to human health and the environment.

In the era of smart Internet-of-Things, convolutional neural network (CNN) models with low computational overhead are crucial for low-latency applications in resource-constrained embedded devices. The performance and efficiency of multiplication operations play a vital role in accelerating and optimizing CNN computation. In this article, we propose the MA4C technique, which reduces CNN computation overhead by converting a pretrained CNN’s parameters into approximated minimum signed digit (MSD) representations. MSD representation contains fewer non-zero digits on average compared to the binary representation of a number. The proposed scheme approximates the MSD representations by only considering a specified number of most significant digits. The MA4C technique reduces the computational complexity of multipliers by reducing the number of partial sums. The proposed MSD approximation was applied on various DNN models, and their performance was analyzed for different datasets, varying CNN depth, and network configuration. Implementation of our proposed method on FPGA reduced the logic circuits and multiplier latency by up to 4.2× and 1.2× respectively compared to an 8-bit Booth multiplier for most CNN models.

The pathological consequences leading to primary storage, autophagy impairment, impaired mitochondrial dynamics, and endoplasmic reticulum (ER) stress on neural cell dysfunction and apoptosis in metachromatic leukodystrophy (MLD) have been poorly elucidated. In the present study, we generated 2 cell lines of patient-specific-induced pluripotent stem cells (iPSCs) and modeled the progression of pathological events during the differentiation of iPSCs to motor neuron progenitors (MNPs) and mature motor neurons (MNs). The iPS cells were generated from two late-infantile MLD patient-derived skin fibroblasts using electroporation or the Sendai virus. Olig2+ MNPs were generated from both iPSC lines using a combination of small molecules in a chemically defined neural medium. Furthermore, the MNPs could be differentiated into mature MNs, which was confirmed by RT–PCR and MN markers, including SMI32 and ChAT. The population of MNs was approximately 50% under the culture conditions. Pathological observation of MLD patient-derived iPSCs revealed lysosomal accumulation and impaired autophagy. In addition, both MNPs and MNs derived from MLD-iPSCs showed increased lysosomal accumulation, dysfunctional autophagy, impaired mitophagy, endoplasmic reticulum (ER) stress or unfolded protein response (UPR) activation, and premature cellular death.

Building occupants' awareness is very essential to promote energy efficiency in the green building concept. However, research related to awareness of the campus building occupants has not been widely explored, especially in Indonesia. This research investigates the criteria of the occupant's awareness regarding energy efficiency awareness as well as their performance in Institut Teknologi Sepuluh Nopember (ITS) Campus. A questionnaire survey was conducted across three-campus building occupants, namely lecturer, staff and students. 181 data were acquired and analyzed the variables' performance. It was found 15 that awareness variables where their performance were categorised as ‘good’ form the overall occupants. Nevertheless, the students' awareness still can be categorised as ‘moderate’ category and needs be improved to achieve energy efficiency. To be focussed, the improvement should be conducted to three critical variables, namely Recognize the issue of electricity resource depletion, Resource sharing to reduce the use of electrical energy consumption, and Understand to make efforts and prepare for electricity resource depletion. This research shed the light to manage occupants' awareness of energy efficiency in the campus building context.

A feeding trial was conducted to evaluate the effects of Bacillus-based probiotics on growth performance, intestinal histo-morphology, gut microbial population and immune response in broilers. A total of 2000 Hubbard Classic day-old chicks were randomly enrolled in four experimental groups and 4 replicates of 500 birds in each group, and reared for 35 days under a low- level of biosecurity measures. The trial groups were assigned treatment-1 (T1): basal diet(control), treatment-2 (T2): basal diet plus Bacillus licheniformis (DSM17236), treatment-3 (T3): basal diet plus Bacillus subtilis (PB6), and treatment-4 (T4) basal diet plus 4% Flavomycin. All four groups were fed with maize-soybean based prepared feeds (starter, grower and finisher). Dietary inclusion of B. licheniformis significantly improved body weight gain and lessened FCR in T2 compared to other groups (p

Niemann−Pick disease type C (NPC) is a rare neurodegenerative disorder caused by a recessive mutation in the NPC1 or NPC2 gene, in which patients exhibit lysosomal accumulation of unesterified cholesterol and glycolipids. Most of the research on NPC has been done in patient-derived skin fibroblasts or mouse models. Therefore, we developed NPC patient neurons derived from induced pluripotent stem cells (iPSCs) to investigate the neuropathological cause of the disease. Although an accumulation of cholesterol and glycolipids, which is characteristic of NPC, was observed in both undifferentiated iPSCs and derived neural stem cells (NSCs), we could not observed the abnormalities in differentiation potential and autophagic activity in such immature cells. However, definite neuropathological features were detected in mature neuronal cells generated from NPC patient-derived iPSCs. Abnormal accumulation of cholesterol and other lipids identified by lipid droplets and number of enlarged lysosomes was more prominent in mature neuronal cells rather than in iPSCs and/or NSCs. Thin-sectioning electron microscopic analysis also demonstrated numerous typical membranous cytoplasmic bodies in mature neuronal cells. Furthermore, TUJ1-positive neurite density was significantly reduced in NPC patient-derived neuronal cells. In addition, disruption of the p62/SQSTM1−KEAP1−NRF2 axis occurred in neurons differentiated from NPC patient-derived iPSCs. These data indicate the impairment of neuronal network formation associated with neurodegeneration in mature neuronal cells derived from patients with NPC.

The COVID-19 pandemic is the defining health crisis of the world in 2020 and the world economy is affected as well. Bangladesh is also one of the impacted countries, which needs to conduct sufficient tests to identify patients and accordingly adopt measures to limit the massive outbreak of this viral infection. But due to economic drawbacks and also unavailability of testing equipment, Bangladesh is lagging critically behind in test numbers. This study shows a pool testing method named Conditional Cluster Sampling (CCS) that utilizes soft computing and data analysis techniques to reduce the expense of total testing equipment. The proposed method also demonstrates its effectiveness compared to the traditional individual testing method. Firstly, according to patients’ symptoms and severity of their conditions, they are classified into four classes- Minor, Moderate, Major, Critical. After that Random Forest Classifier (RFC) is used to predict the class. Then random sampling is done from each class according to CCS. Finally, using Monte Carlo Simulation (MCS) for 100 cycles, the effectiveness of CCS is demonstrated for different probability levels of infection. It is shown that the CCS method can save up to 22% of the test kits that can save a huge amount of money as well as testing time.

Arsenic contamination is a major environmental issue, as it may lead to serious health hazard. The reduced trivalent form of inorganic arsenic, arsenite, is in general more toxic to plants compared with the fully oxidized pentavalent arsenate. The uptake of arsenite in plants has been shown to be mediated through a large subfamily of plant aquaglyceroporins, nodulin 26-like intrinsic proteins (NIPs). However, the efflux mechanisms, as well as the mechanism of arsenite-induced root growth inhibition, remain poorly understood. Using molecular physiology, synchrotron imaging, and root transport assay approaches, we show that the cellular transport of trivalent arsenicals in Arabidopsis thaliana is strongly modulated by PIN FORMED 2 (PIN2) auxin efflux transporter. Root transport assay using radioactive arsenite, X-ray fluorescence imaging (XFI) coupled with X-ray absorption spectroscopy (XAS), and inductively coupled plasma mass spectrometry analysis revealed that pin2 plants accumulate higher concentrations of arsenite in roots compared with the wild-type. At the cellular level, arsenite specifically targets intracellular sorting of PIN2 and thereby alters the cellular auxin homeostasis. Consistently, loss of PIN2 function results in arsenite hypersensitivity in roots. XFI coupled with XAS further revealed that loss of PIN2 function results in specific accumulation of arsenical species, but not the other metals such as iron, zinc, or calcium in the root tip. Collectively, these results suggest that PIN2 likely functions as an arsenite efflux transporter for the distribution of arsenical species in planta.

Fabry disease is an X-linked lysosomal storage disorder caused by a deficiency of α-galactosidase A (α-gal A), leading to the progressive accumulation of glycosphingolipids. Classical hemizygous males usually present symptoms, including pain and paresthesia in the extremities, angiokeratoma, hypo- or anhidrosis, abdominal pain, cornea verticillata, early stroke, tinnitus, and/or hearing loss, during early childhood or adolescence. Moreover, proteinuria, renal impairment, and cardiac hypertrophy can appear with age. Enzyme replacement is the most common therapy for Fabry disease at present which has been approved in Japan since 2004. We report a case involving a 27-year-old male with extreme terminal pain, anhidrosis, abdominal pain, tinnitus, hearing impairment, cornea verticillata, and recurrent huge ulcers in the lower extremities. At the age of 16 years, he was diagnosed with Fabry disease with a positive family history and very low α-gal A activity. He then received enzyme replacement therapy (ERT) with recombinant human agalsidase beta at 1 mg/kg every 2 weeks for 10 years. Throughout the course of ERT, his leg ulcers recurred, and massive excretion of urinary globotriaosylceramide and plasma globotriaosylsphingosine was observed. Electron microscopy of the venous tissue in the regions of the ulcer showed massive typical zebra bodies in the vascular wall smooth muscle cells.

X-linked adrenoleukodystrophy (X-ALD) is a rare inherited metabolic disease that results in the accumulation of very long chain fatty acids (VLCFA) in plasma and all tissues. Recent studies regarding cerebral X-ALD (CALD) treatment emphasize the importance of its early diagnosis. 26:0 lysophosphatidylcholine (LysoPC) is a sensitive biomarker for newborn screening of X-ALD, while its application for Japanese DBS is unclear. Therefore, we evaluated the feasibility of 20:0 LysoPC and 24:0 LysoPC along with 26:0 LysoPC for diagnosing X-ALD in a cohort of newborns (n = 604), healthy adults (n = 50) and patients (n = 4). Results indicated that 26:0 LysoPC had strong significance for discrimination of patients by the amounts of 2.0 to 4.0 and 0.1 to 1.9 pmol/punch for patients and newborns/healthy adults, respectively. Based on these values, we recommend that further diagnostic confirmation is essential if the amount of 26:0 LysoPC in DBS is above 1.7 pmol/punch.

Fabry disease is an X-linked lysosomal storage disorder caused by a deficiency of α-galactosidase A (α-gal A). The clinical variability of the phenotypes of Fabry disease in females is still poorly understood. The degree of aberrant methylation of non-mutated alleles is thought to have significant effects on X-chromosome inactivation (XCI). We previously reported that one heterozygous Fabry female showing classical phenotypes had complete methylation of the non-mutated allele of the GLA gene. In this report, we summarized 36 heterozygous females with a clinical severity score based on the FAbry STabilization indEX (FASTEX). We measured their α-gal A activity and plasma/ serum globotriaosylsphingosine (lyso-Gb3) accumulation and performed electron microscopy of skin biopsies. We analyzed the methylation-sensitive restriction enzyme sites throughout the GLA gene, including the 5’UTR, and found a single SacII site and multiple HhaI and HpaII sites aggregated in exon 1 and the 5’UTR. One HpaII sequence in exon 7 was also detected as a methylation-sensitive site. With methylation-sensitive restriction enzymes, methylated and non-methylated alleles could be separated, and the ratio of the methylation was quantified. We found a clear correlation between the severity of the phenotype and lyso-Gb3 accumulation for heterozygous Fabry disease in females. Methylation of the non-mutated allele was also proportionately correlated to the clinical severity score measured by FASTEX. Keywords: Heterozygous Fabry females, Fabry stabilization indEX, Methylation, X-chromosome inactivation

Human Pose Estimation (HPE) is a crucial step towards understanding people in images and videos. HPE provides geometric and motion information of the human body, which has been applied to a wide range of applications (e.g., human-computer interaction, motion analysis, augmented reality, virtual reality, healthcare, etc.). An extremely useful task of this kind is the 2D pose estimation of bedridden patients from infrared (IR) images. Here, the IR imaging modality is preferred due to privacy concerns and the need for monitoring both uncovered and covered patients at different levels of illumination. The major drawback of this research problem is the unavailability of covered examples, which are very costly to collect and time-consuming to label. In this work, a deep learning-based framework was developed for human sleeping pose estimation on covered images using only the uncovered training images. In the training scheme, two different image augmentation techniques, a statistical approach as well as a GAN-based approach, were explored for domain adaptation, where the statistical approach performed better. The accuracy of the model trained on the statistically augmented dataset was improved by 124 % as compared with the model trained on non-augmented images. To handle the scarcity of training infrared images, a transfer learning strategy was used by pre-training the model on an RGB pose estimation dataset, resulting in a further increment in accuracy of 4 %. Semi-supervised learning techniques, with a novel pose discriminator model in the loop, were adopted to utilize the unannotated training data, resulting in a further 3 % increase in accuracy. Thus, significant improvement has been shown in the case of 2D pose estimation from infrared images, with a comparatively small amount of annotated data and a large amount of unannotated data by using the proposed training pipeline powered by heavy augmentation.

Foreign Direct Investment’s (FDI) contribution to the agricultural share of GDP is a questionable topic in Bangladesh’s current economy. Therefore, this study aims to inspect the effect of FDI inflow in agriculture on the agriculture sector’s contribution to Bangladesh’s economic development. The study used advanced econometric tools to the time series data obtained from the Bangladesh Bank and the Bangladesh Economic Review from 1996 to 2021. For the empirical analysis, the authors employ the Autoregressive Distributed Lag (ARDL) co-integration approach to measure short-run dynamics and long-run relationship between FDI inflow in agriculture (AFDI) and agricultural share to GDP (AGDP) in Bangladesh. The findings from the estimation confirm that AFDI has a statistically significant effect on AGDP in the short run; in the long run, it is insignificant. Bangladesh will have to improve its policy for creating the environment to attract FDI in the agricultural sector to draw more promising investments to boost agricultural productivity. In this regard, the country can reform its taxation and agricultural investment policies to create an ‘investment-friendly climate’ for attracting long-term foreign capital in agriculture.

Sentiment analysis (SA) is a subset of natural language processing (NLP) research. In the case of categorical weighted based dictionary with rule-based sentiment score generation, no work in SA has been done yet in Bangla language using deep learning (DL) approaches. This paper proposes DL models for SA on Bangla text using an extended lexicon data dictionary (LDD). We implement the rule-based method Bangla text sentiment score (BTSC) algorithm for extracting polarity from large texts. These polarities are then fed into the neural network along with the preprocessed text as training samples. The preprocessed texts are formatted as a vectorization of words of unique numbers of pre-trained word embedding models. Word2Vec matrix with top highest probability word is applied on embedding layer as a weighted matrix to fit the DL models. This paper also presents a remarkably detailed analysis of selective DL models with some fine tuning. The fine-tuning includes the use of drop out, optimizer regularization, learning rate, multiple layers, filters, attention mechanism, capsule layers, transformer with progressive training along with validation and testing accuracy, precision, recall and F1-score. Experimental results indicate that the proposed new long short-term memory (LSTM) models are highly accurate in performing SA tasks. For our proposed hierarchical attention based LSTM (HAN-LSTM), Dynamic routing based capsule neural network with Bi-LSTM (D-CAPSNET-Bi-LSTM) and bidirectional encoder representations from Transformers (BERT) with LSTM (BERT-LSTM) model we achieved accuracy values of 78.52%, 80.82% and 84.18% respectively.

Soil organic carbon (SOC), greenhouse gas (GHG) emissions and water footprint (WF) are the key indicators of environmental sustainability in agricultural systems. Increasing SOC while reducing GHG emissions and WF are effective measures to achieve high crop productivity with minimum environmental impact (i.e. a multi-pronged approach of sustainable intensification (SI) and climate-smart agriculture (CSA) to achieve food security). In conventional agricultural systems, intensive soil tillage and removal of crop residues can lead to increase negative environmental impact due to reduce SOC, GHG emission and high water consumption. Conservation agriculture (CA) based conservation tillage systems (CTS) with crop residue retention is often suggested as a resource conserving alternative to increase crop productivity without compromising soil health and environmental sustainability of cereal cropping systems. The environmental impact of CTS in terms of SOC, WF and GHG emissions nonetheless remains understudied in Bangladesh. A two-year field experiment was carried out to evaluate the impacts of CTS with retention of crop residue on SOC accumulation, GHG emission and WF in wheat cultivation of Bangladesh. In the experiment, CTS such as zero tillage (ZT) and minimum tillage (MT) were compared with the conventional tillage (CT) practice. Result observed that the SOC accumulation in the soil was 0.11 t ha−1, 0.97 t ha−1, and 1.3 t ha−1 for CT, MT and ZT practices, respectively. A life cycle GHG emission estimation by farm efficiency analysis tool (FEAT) calculated 1987, 1992 and 2028 kg CO2eq ha−1 for ZT, MT and CT practices, respectively. Among the studied tillage options, lowest WF was achieved by MT (570.05 m3 t−1) followed by ZT (578.56 m3 t−1) and CT (608.85 m3 t−1). Since the results are in favor of CTS, this study recommends MT and ZT practice to reduce negative environmental externalities in wheat cultivation in Bangladesh. In comparison between the methods, the MT, which retains crop residue (20 cm), and involves principles of CA, is suitable for both CSA and SI of wheat cultivation in Bangladesh due to its ability to increase SOC accumulation, prevent both water loss, and GHG emission without compromising yield.

The preparation of the nanocomposites zinc oxide/platinum (ZnO/Pt) has attracted much attention with regard to improving the photocatalytic efficiency of ZnO, but most studies have focused on the use of ZnO/Pt in conventional powdered spherical nanocrystals only. In this experiment, bayberry-like Pt nanoparticles (NPs) were successfully synthesized and deposited on the surfaces of ZnO nanorods (NRs) that were hydrothermally grown on glass substrates. The bayberry-like Pt NPs, which had a diameter range of 40–70 nm and consisted of many nanodots with a diameter

Aims: We aimed to compare the GRACE and TIMI risk scores in patients with non- ST elevation acute coronary syndrome for their accuracy in predicting the angiographic severity of coronary artery disease. Method: The cross-sectional study done in the Department of Cardiology, National Institute of Cardiovascular Diseases, Dhaka, Bangladesh from April, 2015–April, 2016. The patients admitted with non-ST elevation acute coronary syndrome were evaluated to calculate the GRACE and TIMI risk score. Coronary angiogram was done during index hospitalization and the severity of coronary artery disease was assessed by vessel score and Gensini score. Results: Of 205 patients, a positive correlation of the vessel score and Gensini score was observed with both the GRACE and TIMI risk scores (p =

Background: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system., Method: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features., Results: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively., Conclusions: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Systemic lupus erythematosus (SLE) is an inflammatory, autoimmune disorder of unknown etiology. The inflammatory stress in SLE patients may modify macromolecules and produce structural/functional abnormalities. The present study is aimed at examining the consequences of stresses on the structure of albumin in SLE patients. Albumin was isolated from the sera of SLE/healthy subjects. Multiple physicochemical techniques were used to elucidate, structure of albumin. Advanced glycation end products in SLE patients' albumin were identified by the AGE specific fluorescence. Quenching of tryptophan, tyrosine fluorescence and surface protein hydrophobicity was observed in SLE patients' albumin. Protein-bound carbonyls were elevated while free thiol, lysine, arginine, and alpha helicity was found to be decreased in SLE albumin. Furthermore, changes in the secondary structure of SLE albumin were observed as shift in the position of amide I/II bands. Functionality of SLE albumin was also compromised as its cobalt-binding ability was substantially declined. Adduction of moieties was detected by dynamic light scattering (DLS) and confirmed by matrix assisted laser desorption/ionization. DLS, thioflavin T and transmission electron microscopy results confirmed aggregates in SLE patients' albumin. This study may be helpful in understanding the role of modified albumin in the cofounding pathologies associated with SLE., Competing Interests: Declaration of competing interest Authors have no conflict of interest to declare., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Systemic lupus erythematosus (SLE) is an autoimmune disorder where the role of inflammatory processes in the etiopathogenesis is well documented. Despite extensive research, the trigger for initiation of the disease has not been identified. Peroxynitrite, a strong nitrating/oxidizing agent has been reported in SLE and other autoimmune diseases. In this study, human serum albumin (HSA) was exposed to peroxynitrite for 30min at 37°C. The structure of HSA was grossly perturbed when examined by various physico-chemical techniques. Peroxynitrite mediated nitration of HSA was confirmed by LCMS/MS. Furthermore, increase in hydrodynamic radius of peroxynitrite-modified-HSA suggests the attachment of nitro group(s). Aggregation in peroxynitrite-modified-HSA was evident in a TEM scan. Nitration, oxidation, cross linking, aggregation etc conferred immunogenicity on peroxynitrite-modified-HSA. High titre antibodies were elicited in rabbits immunized with peroxynitrite-modified-HSA. Induced antibodies were highly specific for peroxynitrite-modified-HSA but showed considerable binding with other nitrated molecules. Direct binding/inhibition ELISA carried out with autoantibodies in SLE sera showed preferential binding with peroxynitrite-modified-HSA. Anti-nDNA positive IgG from SLE sera showed preference for peroxynitrite-modified-HSA when subjected to immunoassay (direct binding and inhibition) and mobility shift assay. Our results reinforce the role of augmented inflammation in SLE progression., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Introduction: Galactosialidosis is a rare lysosomal storage disease caused by a combined deficiency of GM1 β-galactosidase (β-gal) and neuraminidase secondary to a defect of a lysosomal enzyme protective protein/cathepsin A (PPCA) and mutation in CTSA gene. Three subtypes are recognized: early infantile, late infantile, and juvenile/adult. There is no specific therapy for patients with galactosialidosis at this time., Objectives: The aim of this study was to determine the chaperone effect of N-octyl-4-epi-β-valienamine (NOEV) on β-gal proteins in skin fibroblasts of PPCA-deficit patients., Methods: β-Gal and neuraminidase activities were measured for the diagnosis of the patients with galactosialidosis. Western blotting for PPCA protein and direct sequencing for CTSA gene were performed. Cultured skin fibroblast were treated with NOEV., Results: We report four novel patients with galactosialidosis: one had the early infantile form and the other three had the juvenile/adult form. We found that NOEV stabilized β-gal activity in lysate from cultured skin fibroblasts from these patients. Treatment with NOEV significantly enhanced β-gal activity in cultured skin fibroblasts in the absence of PPCA., Conclusions: Our results indicate the possibility that NOEV chaperone therapy might have a beneficial effect, at least in part, for patients with galactosialidosis., (Copyright © 2015 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.)

Interplay between drug-resistance mutations in CTL epitopes and HIV-1-specific CTLs may influence the control of HIV-1 viremia. However, the effect of integrase inhibitor (INI)-resistance mutations on the CTL recognition has not been reported. We here investigated the effect of a raltegravir and elvitegravir-resistance mutation (E92Q) on HLA-B*40:02-restricted Int92-102 (EL11: ETGQETAYFLL)-specific CTLs. EL11-specific CTLs recognized E92Q peptide-pulsed and E92Q mutant virus-infected cells less effectively than EL11 peptide-pulsed and wild-type virus-infected cells, respectively. Ex vivo ELISpot analysis showed no induction of E92Q-specific T cells in chronically HIV-1-infected individuals. Thus, we demonstrated that EL11-specific CTL recognition was affected by the INI-resistance mutation., (Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.)

This report describes a 60-year-old female patient with Krabbe disease who presented with slowly progressive gait disturbance due to mild spastic paraplegia. Brain magnetic resonance imaging showed high-intensity lesions along the upper parts of the bilateral pyramidal tracts in fluid-attenuated inversion recovery images. Central motor conduction time was prolonged both in the upper and the lower extremities, while central sensory conduction time was normal. The reduced lymphocyte galactocerebrosidase (GALC) activity and two novel mutations in the GALC gene, p.G496S and p.G569S, proved the diagnosis of Krabbe disease. Our findings show that adult-onset Krabbe disease is characterized by isolated pyramidal tract impairment in the central nervous system, both neurophysiologically and radiologically., (Copyright © 2012 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.)

Ghrelin is a growth hormone (GH) secretagogue secreted mainly from the stomach that functions in controlling muscle volume and energy homeostasis. We here studied the effects of ghrelin on unloading-induced muscle atrophy using a mouse model of hindlimb suspension (HS). Ghrelin administration during 2-week HS alleviated reductions of muscle mass in the fast-twitch fiber-rich plantaris muscle and the slow-twitch fiber-rich soleus muscle of the hindlimb. Ghrelin administration during a 5-day recovery period following 2-week HS enhanced food intake and facilitated recovery from atrophy in both muscles. Ghrelin administration normalized hypercorticosteronemia in these studies. Ghrelin's anti-muscle atrophy effect was found even under pair-feeding condition, but not in mice given des-acyl ghrelin. Insulin-like growth factor (IGF)-1 mRNA expression was significantly reduced in the atrophied plantaris muscle compared with control muscles. A single ghrelin administration to HS mice acutely increased plasma GH and also amplified phosphorylation of signal transducer and activator of transcription (STAT) 5 and increased IGF-1 mRNA expression in the plantaris muscle, but not in the soleus muscle. This study demonstrated that ghrelin stimulated the GH-STAT5-IGF-1 axis in the locally atrophied plantaris muscle, and its administration alleviated muscle atrophy and facilitated recovery from muscle atrophy. Ghrelin's effects represent a novel therapeutic paradigm for the treatment of unloading-induced muscle atrophy induced by factors such as bed rest, injury, and joint immobilization., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The interactions and complexation process of the structurally related amphiphilic phenothiazines promazine and triflupromazine hydrochlorides with horse myoglobin in aqueous buffered solutions of pH 2.5, 5.5 and 9.0 have been examined by zeta-potential, isothermal titration calorimetry (ITC), UV-vis spectroscopy and dynamic light-scattering techniques with the aim of analyzing the effect of hydrophobic and electrostatic forces, the alteration of protein conformation and the effect of substituents in the drug molecular structure on the binding mechanism and structure of the resulting complexes. The energetics and stoichiometry of the binding process was derived from ITC. The enthalpies of binding obtained are small and exothermic, and the Gibbs energies of binding are dominated by large increases in entropy consistent with hydrophobic interactions. Binding isotherms were obtained from microcalorimetric data by using a theoretical model based on the Langmuir isotherm. zeta-Potential data showed a reversal in the sign of the protein charge at pH 9.0 as a consequence of drug binding. Gibbs energies of drug binding per mole of drug were also derived from zeta-potential data. On the other hand, binding of the phenothiazines causes a conformational transition on protein structure which was followed as a function of drug concentration by using UV-vis spectroscopy. These data were analyzed to obtain the Gibbs energy of the transition in water (DeltaG(w)(degrees)) and in a hydrophobic environment (DeltaG(hc)(degrees)). Finally, the population distribution of the different species in solution and their size was analyzed through dynamic light scattering. The existence of an aggregation process of drug/protein complexes, mainly at pH 2.5, was observed. We think this is a consequence of the already expanded structure of the protein at this pH and the subsequent binding of drug molecules to the protein.