Miracle-dz/UniFAR-FTUs huggingface dataset:
Agriculture 4.0 in Bangladesh: Issues and Challenges

Agriculture 4.0 is emerging as the next big trend, with a focus on smart and precision agriculture to maximise benefits in the context of growing populations and climate change. Agriculture 4.0 supports the adoption of intelligent systems in all spheres of farming, harvesting, irrigation, and so on. Though there is enough inclusion of Artificial Intelligence and Internet of Things (IoT) based systems in developed countries, agriculture sector of Bangladesh did not receive that much attention. To mitigate this gap, a Big Data and IoT based architecture for crop, fisheries, and livestock has been proposed in this paper based on the existing research advancements around the world where different nodes and actuators will be implemented in field level to read environmental stimuli and forward to cloud server for processing. A thorough review work was performed on agriculture 4.0, and these framework were analysed from the perspective of Bangladesh. This paper will fulfil the requirement of a connection between the existing state of the art researches and its suitability in terms of a developing country like Bangladesh.
High-accuracy effective density measurements of sodium methanesulfonate and aminium chloride nanoparticles using a particulate calibration standard

Abstract Methanesulfonate and aminium salts are commonly found in ambient nanoparticles and are often used as calibration standards. However, the effective densities of the particles generated from these standards are required if they are to be used to calibrate aerosol mass spectrometers or to estimate hygroscopic growth factors from electrodynamic balance experiments. A centrifugal particle mass analyzer and scanning mobility particle sizer were used in tandem (CPMA-SMPS) to measure the effective density of five salts. The effective densities were determined to be: sodium methanesulfonate, 1474 ± 13 kg m−3; methylammonium chloride, 1236 ± 29 kg m−3, monoethanolamine hydrochloride, 1136 ± 26 kg m−3; 1,4-diaminobutane dihydrochloride, 1135 ± 33 kg m−3; and NaCl was found to have a size-dependent effective density due to its non-spherical shape. It is also shown how Santovac® vacuum pump oil can be used to accurately calibrate the CPMA-SMPS system for particles less than 100 nm in diameter, which is a size range that has been problematic for calibration techniques relying on polystyrene latex spheres. Copyright © 2023 American Association for Aerosol Research
Ambiental Factors in Parkinson’s Disease Progression: A Systematic Review

Background and Objectives: So far, there is little evidence of the ambient effect on motor and non-motor symptoms of Parkinson’s Disease (PD). This systematic review aimed to determine the association between ambiental factors and the progression of PD. Materials and Methods: A systematic literature search of PubMed, Cochrane, Embase, and Web of Science was conducted up to 21 December 2021 according the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Eight articles were used in the analyses. Long-term exposure to fine particles (particulate matter ≤ 2.5 μm; PM2.5) was positively associated with disease aggravation in two studies. Short-term PM2.5 exposure was positively associated with disease aggravation in three studies. Significant associations were found between PD aggravation and NO2, SO2, CO, nitrate and organic matter (OM) concentrations in two studies. Associations were more pronounced, without reaching statistical significance however, in women, patients over 65 years old and cold temperatures. A 1% increase in temperature was associated with a significant 0.18% increase in Levodopa Equivalent Dose (LED). Ultraviolet light and humidity were not significantly associated with an increase in LED. There was no difference in hallucination severity with changing seasons. There was no evidence for seasonal fluctuation in Unified Parkinson’s Disease Rating Scale (UPDRS) scores. Conclusions: There is a link between air pollutants and temperature for PD progression, but this has yet to be proven. More longitudinal studies are warranted to confirm these findings.
No Evidence of Morning or Large-Scale Drizzle on Titan

Widespread methane precipitation on Titan has been predicted by several authors since methane saturation in the upper troposphere was measured by the Huygens probe over its landing site. Recently, observational evidence of widespread morning drizzle has been suggested based on detection of a dark morning site in surface-subtracted 2 μm spectroimages obtained from ground-based observations. We have obtained similar new spectroimages of Titan observed at Gemini-North Observatory at several rotational phase angles and have analyzed them using the same image processing technique. By comparing images at different phases, we show that the presumed dark drizzling regions in the surface-subtracted images are mainly negative renditions of bright surface regions. No evidence of spectroscopically verifiable drizzling is apparent in our cloudless Titan images. At present, constraining models of Titan’s hydrological cycle to produce a diurnal response would be premature.
PINER: Prior-informed Implicit Neural Representation Learning for Test-time Adaptation in Sparse-view CT Reconstruction

Recently, deep learning has been introduced to solve important medical image reconstruction problems such as sparse-view CT reconstruction. However, the developed deep reconstruction models are generally limited in generalization when applied to out-of-distribution samples in unseen domains. Furthermore, privacy concerns may impede the availability of source-domain training data to retrain or adapt the model to the target-domain testing data, which are quite common in real-world medical applications. To address these issues, we introduce a source-free black-box test-time adaptation method for sparse-view CT reconstruction with unknown noise levels based on prior-informed implicit neural representation learning (PINER). By leveraging implicit neural representation learning to generate the image representations at various noise levels, the proposed method is able to construct the adapted input representations at test time based on the inference of black-box model and output analysis. We performed experiments of source-free test-time adaptation for sparse-view CT reconstruction with unknown noise levels on multiple anatomical sites with different black-box deep reconstruction models, where our method outperforms the state-of-the-art algorithms. Code: https://github.com/efzero/PINER
On the difference between empirical mode decomposition and wavelet decomposition in the nonlinear time series

The method of empirical mode decomposition （EMD） based Hilbert transformation is that separate the nonlinear time series into intrinsic mode functions （IMFs ） with different time scale by using EMD, then apply the Hilbert transformation to every IMF to get the Hilbert spectrum.By systematically comparing the advan tages and disadvantages between EMD and wavelet decomposition （WD）, between Hi lbert transformation and wavelet transformation in transacting nonlinear time s eries using ideal time series and 18 O time series of Guliya i ce co re on the Tibetan Plateau, we present some improving measures to reduce the di sadvantages. The result of investigation show that the combination of EMD-based and WD-based methods may be more effectively in recognizing the main informatio n of the time series.
ON SOME DIFFERENTIAL-OPERATOR EQUATIONS OF ARBITRARY ORDER

On the half-line we investigate the following equation in a Banach space: (1)where are closed operators which commute with . We consider the following classes of equations: parabolic, inverse parabolic, hyperbolic, quasi-elliptic, and quasi-hyperbolic. We present boundary value problems for these classes and prove that they are well-posed. The proofs are based on a solvability theorem for the operator equation , where is a closed operator.Bibliography: 20 items.
Human Factor Engineering Research for Rehabilitation Robots: A Systematic Review

The application of human factors engineering for rehabilitation robots is based on a “human-centered” design philosophy that strives to provide safe and efficient human-robot interaction training for patients rather than depending on rehabilitation therapists. Human factors engineering for rehabilitation robots is undergoing preliminary investigation. However, the depth and breadth of current research do not provide a complete human factor engineering solution for developing rehabilitation robots. This study aims to provide a systematic review of research at the intersection of rehabilitation robotics and ergonomics to understand the progress and state-of-the-art research on critical human factors, issues, and corresponding solutions for rehabilitation robots. A total of 496 relevant studies were obtained from six scientific database searches, reference searches, and citation-tracking strategies. After applying the selection criteria and reading the full text of each study, 21 studies were selected for review and classified into four categories based on their human factor objectives: implementation of high safety, implementation of lightweight and high comfort, implementation of high human-robot interaction, and performance evaluation index and system studies. Based on the results of the studies, recommendations for future research are presented and discussed.
Comparison of numerical methods for light propagating in fibers with high steps of refractive index

Fast development of complex structures like microstructural fibers, photonic nanowires or slot waveguides requires numerical tools to predict a light propagation. There are many works concerning weakly guided case, but the microstructural fibers need algorithm for a high step of the refractive index. In this paper, three approximate methods are compared. The comparison concerns a structure consisting of circular cores surrounded by cladding for different values of the refractive index steps. Application of these methods in chromatic dispersion case is also presented. It is shown that certain conditions prefer two dimensional scalar algorithms (based on approximated methods) than three dimensional ones. This allows us to implement more efficient and less complicated methods.
ISO far infrared observations of the high latitude cloud L 1642 I. The density and temperature structure

We have performed a large-scale mapping of the high-latitude, moderate extinction dark cloud L 1642 with ISO (Infrared Space Observatory) at 200 μ m to study the properties of dust, the virial equilibrium condition of the cloud, and their relation to star formation. The cloud consists of three denser regions which are connected by diffuse material. Only one of the regions, the one most massive and with the greatest optical depth, is related to a temperature mimimum. The pre-main sequence binary stars IRAS 04325-1419 and IRAS 04327-1419, probably born within the cloud, are located close to this temperature mimimum coinciding with the column density maximum. The minimum dust temperature is ~13.8 K. The ratio $2E_{{\rm kin}}$/$|E_{{\rm pot}}|$ for the star-forming region is about 1.2, and thus it is close to being gravitationally bound. However, the other regions are not gravitationally bound. On a 1´-10´ spatial scale the radial density distributions, derived from far-infared optical depth maps, are similar between the star-forming and non star-forming regions. The differences that distinguish the star-forming core appear to be its higher density and lower dust temperature.
Nutritional Strategies in the Rehabilitation of Musculoskeletal Injuries in Athletes: A Systematic Integrative Review

It is estimated that three to five million sports injuries occur worldwide each year. The highest incidence is reported during competition periods with mainly affectation of the musculoskeletal tissue. For appropriate nutritional management and correct use of nutritional supplements, it is important to individualize based on clinical effects and know the adaptive response during the rehabilitation phase after a sports injury in athletes. Therefore, the aim of this PRISMA in Exercise, Rehabilitation, Sport Medicine and Sports Science PERSiST-based systematic integrative review was to perform an update on nutritional strategies during the rehabilitation phase of musculoskeletal injuries in elite athletes. After searching the following databases: PubMed/Medline, Scopus, PEDro, and Google Scholar, a total of 18 studies met the inclusion criteria (Price Index: 66.6%). The risk of bias assessment for randomized controlled trials was performed using the RoB 2.0 tool while review articles were evaluated using the AMSTAR 2.0 items. Based on the main findings of the selected studies, nutritional strategies that benefit the rehabilitation process in injured athletes include balanced energy intake, and a high-protein and carbohydrate-rich diet. Supportive supervision should be provided to avoid low energy availability. The potential of supplementation with collagen, creatine monohydrate, omega-3 (fish oils), and vitamin D requires further research although the effects are quite promising. It is worth noting the lack of clinical research in injured athletes and the higher number of reviews in the last 10 years. After analyzing the current quantitative and non-quantitative evidence, we encourage researchers to conduct further clinical research studies evaluating doses of the discussed nutrients during the rehabilitation process to confirm findings, but also follow international guidelines at the time to review scientific literature.
A Novel Three-Phase Multiobjective Unified Power Quality Conditioner

The decarbonization of the economy and the increasing integration of renewable energy sources into the generation mix are bringing new challenges, requiring novel technological solutions in the topic of smart grids, which include smart transformers and energy storage systems. Additionally, power quality is a vital concern for the future smart grids; therefore, the continuous development of power electronics solutions to overcome power quality problems is of the utmost importance. In this context, this article proposes a novel three-phase multiobjective unified power quality conditioner (MO-UPQC), considering interfaces for solar PV panels and for energy storage in batteries. The MO-UPQC is capable of compensating power quality problems in the voltages (at the load side) and in the currents (at the power grid side), while it enables injecting power into the grid (from the PV panels or batteries) or charging the batteries (from the PV panels or from the grid). Experimental results were obtained with a three-phase four-wire laboratory prototype, demonstrating the feasibility and the large range of applications of the proposed MO-UPQC.
Study of the Effect of Cell Prestress on the Cell Membrane Penetration Behavior by Atomic Force Microscopy

In recent years, atomic force microscopes have been used for cell transfection because of their high-precision micro-indentation mode; however, the insertion efficiency of the tip of AFM into cells is extremely low. In this study, NIH3T3 mouse fibroblast cells cultured on a flexible dish with micro-groove patterns were subjected to various substrate strains at 5%, 10%, 15%, and 20%. It was found that the cell stiffness depends on the prestress of the cell membrane, and that the insertion rate of AFM tips into the cell membrane is proportional to the stiffness through the AFM indentation experiment. The finite element analysis proves that prestress increases the bending stiffness of the cytoskeleton, allowing it to better support the cell membrane, which realizes the stress concentration in the contact area between the AFM tip and the cell membrane. The results indicate that the prestress contributes to the mechanical properties of the cell and suggest that the insertion efficiency could be greatly improved with an increase of the prestress of the cell membrane.
Validation of 3D Knee Kinematics during Gait on Treadmill with an Instrumented Knee Brace

To test a novel instrumented knee brace intended for use as a rehabilitation system, based on inertial measurement units (IMU) to monitor home-based exercises, the device was compared to the gold standard of motion analysis. The purpose was to validate a new calibration method through functional tasks and assessed the value of adding magnetometers for motion analysis. Thirteen healthy young adults performed a 60-second gait test at a comfortable walking speed on a treadmill. Knee kinematics were captured simultaneously, using the instrumented knee brace and an optoelectronic camera system (OCS). The intraclass correlation coefficient (ICC) showed excellent reliability for the three axes of rotation with and without magnetometers, with values ranging between 0.900 and 0.972. Pearson’s r coefficient showed good to excellent correlation for the three axes, with the root mean square error (RMSE) under 3° with the IMUs and slightly higher with the magnetometers. The instrumented knee brace obtained certain clinical parameters, as did the OCS. The instrumented knee brace seems to be a valid tool to assess ambulatory knee kinematics, with an RMSE of <3°, which is sufficient for clinical interpretations. Indeed, this portable system can obtain certain clinical parameters just as well as the gold standard of motion analysis. However, the addition of magnetometers showed no significant advantage in terms of enhancing accuracy.
Screening of Candidate Effectors from Magnaporthe oryzae by In Vitro Secretomic Analysis

Magnaporthe oryzae is the causal agent of rice blast, one of the most serious diseases of rice worldwide. Secreted proteins play essential roles during a M. oryzae–rice interaction. Although much progress has been made in recent decades, it is still necessary to systematically explore M. oryzae-secreted proteins and to analyze their functions. This study employs a shotgun-based proteomic analysis to investigate the in vitro secretome of M. oryzae by spraying fungus conidia onto the PVDF membrane to mimic the early stages of infection, during which 3315 non-redundant secreted proteins were identified. Among these proteins, 9.6% (319) and 24.7% (818) are classified as classically or non-classically secreted proteins, while the remaining 1988 proteins (60.0%) are secreted through currently unknown secretory pathway. Functional characteristics analysis show that 257 (7.8%) and 90 (2.7%) secreted proteins are annotated as CAZymes and candidate effectors, respectively. Eighteen candidate effectors are selected for further experimental validation. All 18 genes encoding candidate effectors are significantly up- or down-regulated during the early infection process. Sixteen of the eighteen candidate effectors cause the suppression of BAX-mediated cell death in Nicotiana benthamiana by using an Agrobacterium-mediated transient expression assay, suggesting their involvement in pathogenicity related to secretion effectors. Our results provide high-quality experimental secretome data of M. oryzae and will expand our knowledge on the molecular mechanisms of M. oryzae pathogenesis.
Habitat use patterns suggest that climate‐driven vegetation changes will negatively impact mammal communities in the Amazon

Climate change will affect species persistence and distribution, particularly in high‐diversity ecosystems like the Amazon. Studies predict that as temperature and deforestation increase and precipitation patterns change in the Amazon, areas along its southern and eastern borders will suffer large‐scale savannization, the conversion of tropical forest to degraded savannah‐like vegetation. Here, we aim to identify the terrestrial mammal species potentially most at risk from savannization by studying their use of natural forest and savannah habitats within four protected areas, using camera‐trap surveys and community occupancy models. We grouped species into categories according to the overlap of their global distributions with the Amazon and Cerrado biome (Amazon, Cerrado and generalist species) and investigated the effect on their space use of savannah cover within a 100‐m buffer, and of the immediate habitat type (continuous forest, riparian forest and savannah) at the camera trap. Both savannah cover and savannah habitat type affected space use of most Amazon and generalist species strongly negatively. Only Cerrado species ever showed strong positive responses to savannah cover. These results suggest that most of the terrestrial mammal community is potentially vulnerable to savannization, including several species typically considered habitat generalists. Negative effects of disturbed savannah‐like habitats are likely even stronger than effects of natural savannah reported here. Although less favorable than continuous forest, riparian forest had a strong negative effect for only a small fraction of species, indicating that effects of savannization may be buffered to some extent by riparian forests. Our results suggest that climate change‐induced vegetation changes may reduce the ability of protected areas in the southern Brazilian Amazon to safeguard populations of terrestrial mammals and should be considered when assessing potential climate‐change effects on these species.
Employee associations with R&D investment, firm performance, disruption risk, and supply chain performance during the COVID-19 pandemic: A multiple mediational model

Purpose: To timely manage supply chain disruptions, experts have focused their attention on the impact of COVID-19 on industries worldwide. Epidemic outbursts are a specific supply chain risk with long disruption propagation, disruption persistence, and high uncertainty. This study aimed to investigate the role of R&D investment and firm performance in mediating the relationship between disruption risk and supply chain performance in Pakistani manufacturing industries and supply chain employees during the recovery phase of the COVID-19 pandemic via the application of the dynamic capability theory. Methodology: From 21 July 2020 to 23 August 2020, 318 employees from supply chains of manufacturing industries in Rawalpindi and Islamabad, Pakistan, participated in this cross-sectional online web-based survey. The four standard research scales were used to examine the research and development, disruption risk, firm, and supply chain performance. The response link was distributed to respondents via Facebook, WhatsApp, and email. The study analyzed the data using structural equation modeling and a partial least squares technique. Results: The study’s findings suggest that disruption risk, research and development investment, and firm performance all improve supply chain performance, but the mediation effect is unsupported by the data. These measures help plan a better supply chain in the face of disruption risk. They provide one of the timely empirical conclusions on the role of R&D investment in mitigating risk disruptions and improving supply chain performance.