ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Cannabinoids in Neurodegenerative Disorders and Stroke/Brain Trauma: From Preclinical Models to Clinical Applications

Cannabinoids form a singular family of plant-derived compounds (phytocannabinoids), endogenous signaling lipids (endocannabinoids), and synthetic derivatives with multiple biological effects and therapeutic applications in the central and peripheral nervous systems. One of these properties is the regulation of neuronal homeostasis and survival, which is the result of the combination of a myriad of effects addressed to preserve, rescue, repair, and/or replace neurons, and also glial cells against multiple insults that may potentially damage these cells. These effects are facilitated by the location of specific targets for the action of these compounds (e.g., cannabinoid type 1 and 2 receptors, endocannabinoid inactivating enzymes, and nonendocannabinoid targets) in key cellular substrates (e.g., neurons, glial cells, and neural progenitor cells). This potential is promising for acute and chronic neurodegenerative pathological conditions. In this review, we will collect all experimental evidence, mainly obtained at the preclinical level, supporting that different cannabinoid compounds may be neuroprotective in adult and neonatal ischemia, brain trauma, Alzheimer's disease, Parkinson's disease, Huntington's chorea, and amyotrophic lateral sclerosis. This increasing experimental evidence demands a prompt clinical validation of cannabinoid-based medicines for the treatment of all these disorders, which, at present, lack efficacious treatments for delaying/arresting disease progression, despite the fact that the few clinical trials conducted so far with these medicines have failed to demonstrate beneficial effects.
Ethnoracial Disparities in Posttraumatic Stress Disorder Symptoms during the COVID-19 Pandemic: A Brief Report

Despite the well-identified vulnerability of older adults during the COVID-19 pandemic, it is unclear about their experiences with COVID-related posttraumatic stress disorder symptomology (COVID-PTSD). This study examined ethnoracial disparities in the level of, and factors associated with, COVID-PTSD using a national data set, including 1926 Whites and 488 ethnoracial minorities. Results showed that ethnoracial minorities reported a greater COVID-PTSD than Whites. COVID-related distress was the common risk factor of COVID-PTSD for the both groups. Being a female and greater social support were associated with COVID-PTSD only for Whites, whereas higher education, greater IADL and fewer ADL limitations were associated with COVID-PTSD for ethnoracial minorities. The findings provided preliminary, but generalizable understanding of ethnoracial disparities in COVID-PTSD, among the Medicare beneficiaries aged ≥65.
CED-Net: Crops and Weeds Segmentation for Smart Farming Using a Small Cascaded Encoder-Decoder Architecture

Convolutional neural networks (CNNs) have achieved state-of-the-art performance in numerous aspects of human life and the agricultural sector is no exception. One of the main objectives of deep learning for smart farming is to identify the precise location of weeds and crops on farmland. In this paper, we propose a semantic segmentation method based on a cascaded encoder-decoder network, namely CED-Net, to differentiate weeds from crops. The existing architectures for weeds and crops segmentation are quite deep, with millions of parameters that require longer training time. To overcome such limitations, we propose an idea of training small networks in cascade to obtain coarse-to-fine predictions, which are then combined to produce the final results. Evaluation of the proposed network and comparison with other state-of-the-art networks are conducted using four publicly available datasets: rice seeding and weed dataset, BoniRob dataset, carrot crop vs. weed dataset, and a paddy-millet dataset. The experimental results and their comparisons proclaim that the proposed network outperforms state-of-the-art architectures, such as U-Net, SegNet, FCN-8s, and DeepLabv3, over intersection over union (IoU), F1-score, sensitivity, true detection rate, and average precision comparison metrics by utilizing only (1/5.74 x U-Net), (1/5.77 x SegNet), (1/3.04 x FCN-8s), and (1/3.24 x DeepLabv3) fractions of total parameters.
Worsening Heart Failure and Atrial Flutter in a Patient Secondary to Cardiac Resynchronization Therapy Dyssynchrony: A Case Report

Cardiac resynchronization therapy-defibrillator (CRT-D) and/or cardiac resynchronization therapy-pacemaker (CRT-P) play an important role in improving cardiac synchronization and reducing the risk of ventricular fibrillation arrest (VFA) in patients with severe left ventricular systolic dysfunction (LVSD). Patients with LVSD may notice worsening symptoms when CRT-D or CRT-P is in dyssynchrony. We present a case of 59-year-old patient who presented with worsening shortness of breath (SOB) and progressive exertional dyspnea for the past few weeks accompanied by pink, frothy sputum, occasional urinary incontinence and urge. He was known to have severe LVSD with an ejection fraction of 10% and had CRT-D in situ. Clinical examination revealed bilateral crepitation and normal heart sounds. A chest radiograph showed pulmonary oedema. An electrocardiogram (ECG) showed atrial fibrillation (AF)/flutter with wide QRS complexes. The patient was treated for acute pulmonary oedema and had CRT-D reprogrammed to achieve biventricular synchrony. He was treated with intravenous furosemide and alternate day metolazone initially. He showed significant subjective and objective improvement and was planned for outpatient synchronized intra-device cardioversion. This case is important because patients with severe LVSD with malfunctioning cardiac resynchronization therapy can result in worsening heart failure (HF) leading to higher morbidity and mortality.
Emission estimates and air quality simulation on Lombardy during lockdown

This paper illustrates the study carried out by ARPA Lombardia to quantify the variation in daily emissions of the main pollutants and their impacts on air quality in Lombardy during the anti-COVID-19 lockdown between the end of February and the end of May 2020. A methodology for emission estimates was developed over Lombardy for this purpose and later was extended to larger areas: the Po-basin, (LIFE PREPAIR 2020) and the entire Italy (PULVIRUS 2021). In this study, the daily emissions estimates were derived by combining data from air emission inventory of Lombardy and a set of indicators that allowed to update the estimates and describe the temporal and spatial variations of the emission sources. The calculation of emission variation was conducted for all the main pollutants (PM10, NH3, NOx, SO2, NMVOC) and the greenhouse gases; then, the impact on air quality concentrations was simulated by the chemical and transport model FARM, that also allows to track secondary particulate and its variability in time and space on the basis of nonlinear processes and weather conditions. The estimated emission reduction, compared to the expected average value in the absence of anti-COVID-19 measures, daily varies depending on pollutants and is mainly affected by reductions in road traffic emissions and an estimated increase in domestic heating emissions. Simulations confirm strong reductions of NO2 atmospheric average concentrations, slightly variations of PM10 averages and a potential growth of tropospheric ozone.
Clinical Predictors of Subacute Myocardial Dysfunction in Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with COVID-19

Multisystem Inflammatory Syndrome in Children (MIS-C) often involves a post-viral myocarditis and associated left ventricular dysfunction. We aimed to assess myocardial function by strain echocardiography after hospital discharge and to identify risk factors for subacute myocardial dysfunction. We conducted a retrospective single-center study of MIS-C patients admitted between 03/2020 and 03/2021. Global longitudinal strain (GLS), 4-chamber longitudinal strain (4C-LS), mid-ventricular circumferential strain (CS), and left atrial strain (LAS) were measured on echocardiograms performed 3-10 weeks after discharge and compared with controls. Among 60 MIS-C patients, hypotension (65%), ICU admission (57%), and vasopressor support (45%) were common, with no mortality. LVEF was abnormal (< 55%) in 29% during hospitalization but only 4% at follow-up. Follow-up strain abnormalities were prevalent (GLS abnormal in 13%, 4C-LS in 18%, CS in 16%, LAS in 5%). Hypotension, ICU admission, ICU and hospital length of stay, and any LVEF < 55% during hospitalization were factors associated with lower strain at follow-up. Higher peak C-reactive protein (CRP) was associated with hypotension, ICU admission, total ICU days, and with lower follow-up GLS (r = - 0.55; p = 0.01) and CS (r = 0.41; p = 0.02). Peak CRP < 18 mg/dL had negative predictive values of 100% and 88% for normal follow-up GLS and CS, respectively. A subset of MIS-C patients demonstrate subclinical systolic and diastolic function abnormalities at subacute follow-up. Peak CRP during hospitalization may be a useful marker for outpatient cardiac risk stratification. MIS-C patients with hypotension, ICU admission, any LVEF < 55% during hospitalization, or a peak CRP > 18 mg/dL may warrant closer monitoring than those without these risk factors.
Obese older adults suffer foot pain and foot-related functional limitation

There is evidence to suggest being overweight or obese places adults at greater risk of developing foot complications such as osteoarthritis, tendonitis and plantar fasciitis. However, no research has comprehensively examined the effects of overweight or obesity on the feet of individuals older than 60 years of age. Therefore we investigated whether foot pain, foot structure, and/or foot function is affected by obesity in older adults. Three hundred and twelve Australian men and women, aged over 60 years, completed validated questionnaires to establish the presence of foot pain and health related quality of life. Foot structure (anthropometrics and soft tissue thickness) and foot function (ankle dorsiflexion strength and flexibility, toe flexor strength, plantar pressures and spatiotemporal gait parameters) were also measured. Obese participants (BMI >30) were compared to those who were overweight (BMI=25-30) and not overweight (BMI <25). Obese participants were found to have a significantly higher prevalence of foot pain and scored significantly lower on the SF-36. Obesity was also associated with foot-related functional limitation whereby ankle dorsiflexion strength, hallux and lesser toe strength, stride/step length and walking speed were significantly reduced in obese participants compared to their leaner counterparts. Therefore, disabling foot pain and altered foot structure and foot function are consequences of obesity for older adults, and impact upon their quality of life. Interventions designed to reduce excess fat mass may relieve loading of the foot structures and, in turn, improve foot pain and quality of life for older obese individuals.
Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.
FISTA-Net: Learning a Fast Iterative Shrinkage Thresholding Network for Inverse Problems in Imaging

Inverse problems are essential to imaging applications. In this letter, we propose a model-based deep learning network, named FISTA-Net, by combining the merits of interpretability and generality of the model-based Fast Iterative Shrinkage/Thresholding Algorithm (FISTA) and strong regularization and tuning-free advantages of the data-driven neural network. By unfolding the FISTA into a deep network, the architecture of FISTA-Net consists of multiple gradient descent, proximal mapping, and momentum modules in cascade. Different from FISTA, the gradient matrix in FISTA-Net can be updated during iteration and a proximal operator network is developed for nonlinear thresholding which can be learned through end-to-end training. Key parameters of FISTA-Net including the gradient step size, thresholding value and momentum scalar are tuning-free and learned from training data rather than hand-crafted. We further impose positive and monotonous constraints on these parameters to ensure they converge properly. The experimental results, evaluated both visually and quantitatively, show that the FISTA-Net can optimize parameters for different imaging tasks, i.e. Electromagnetic Tomography (EMT) and X-ray Computational Tomography (X-ray CT). It outperforms the state-of-the-art model-based and deep learning methods and exhibits good generalization ability over other competitive learning-based approaches under different noise levels.
COMPUTER MODELLING AND RECOMMENDATIONS FOR RESTORATION OF THE HISTORICAL TRANSLUCENT STRUCTURES OF THE PUSHKIN STATE MUSEUM OF FINE ARTS

On the basis of the previous examinations of the historical windows of the main building of the Pushkin State Museum of Fine Arts by the authors [1] using a certified software package, the multi-variant analysis of the methods of increasing efficiency of the existing translucent structures was conducted. The recommendations for restoration of the historical translucent structures which are the parts of this state-protected cultural heritage object were developed.
Methodological approach and tools for systems thinking in health systems research: technical assistants' support of health administration reform in the Democratic Republic of Congo as an application

In the field of development cooperation, interest in systems thinking and complex systems theories as a methodological approach is increasingly recognised. And so it is in health systems research, which informs health development aid interventions. However, practical applications remain scarce to date. The objective of this article is to contribute to the body of knowledge by presenting the tools inspired by systems thinking and complexity theories and methodological lessons learned from their application. These tools were used in a case study. Detailed results of this study are in process for publication in additional articles. Applying a complexity 'lens', the subject of the case study is the role of long-term international technical assistance in supporting health administration reform at the provincial level in the Democratic Republic of Congo. The Methods section presents the guiding principles of systems thinking and complex systems, their relevance and implication for the subject under study, and the existing tools associated with those theories which inspired us in the design of the data collection and analysis process. The tools and their application processes are presented in the results section, and followed in the discussion section by the critical analysis of their innovative potential and emergent challenges. The overall methodology provides a coherent whole, each tool bringing a different and complementary perspective on the system.
Climbing experience in glass eels: A cognitive task or a matter of physical capacities?

The European eel is a panmictic species, whose decline has been recorded since the last 30 years. Among human-induced environmental factors of decline, the impact of water dams during species migration is questioned. Indeed, water impoundments can be a severe obstacle for young eels trying to reach the upstream freshwater zones, even if they are equipped with fish-friendly passes. The passage by such devices could be an important event shaping the outcome of the future life and life history traits of eels. We studied what phenotypic traits were associated with the event of experience of passage by water obstacles. We analyzed specific enzyme activities and/or gene transcription levels in the muscle and brain to test whether the obstacle passage is rather a physical or cognitive task. We found that after a long period of maintenance under homogenous conditions, transcription levels of several genes linked to synaptic plasticity, neurogenesis and thyroid activity differed among the field-experience groups. In contrast, muscle gene transcription levels or enzymatic activities did not show any differences among fish groups. We suggest that cognitive processes such as learning and memory acquisition rather than swimming-related metabolic capacities are involved in passage of water obstacles by young eels.
Trying to Interpret Modern Art as a Finite-Element Practitioner

In this essay, our main aim is to identify the similarities between the techniques used by the 19th and 20th century painters, and scientists dealing with the Finite-Difference/Finite-Element methods. First, we discuss the concept of representation in art, together with its mathematical formulation. We next formulize the perception, and conclude with a discussion about the analogies between artistic movements and some concepts of the Finite-Element Method.
Social Play Behavior Is Critical for the Development of Prefrontal Inhibitory Synapses and Cognitive Flexibility in Rats

Sensory driven activity during early life is critical for setting up the proper connectivity of the sensory cortices. We ask here whether social play behavior, a particular form of social interaction that is highly abundant during postweaning development, is equally important for setting up connections in the developing prefrontal cortex (PFC). Young male rats were deprived from social play with peers during the period in life when social play behavior normally peaks [postnatal day 21-42] (SPD rats), followed by resocialization until adulthood. We recorded synaptic currents in layer 5 cells in slices from medial PFC of adult SPD and control rats and observed that inhibitory synaptic currents were reduced in SPD slices, while excitatory synaptic currents were unaffected. This was associated with a decrease in perisomatic inhibitory synapses from parvalbumin-positive GABAergic cells. In parallel experiments, adult SPD rats achieved more reversals in a probabilistic reversal learning (PRL) task, which depends on the integrity of the PFC, by using a more simplified cognitive strategy than controls. Interestingly, we observed that one daily hour of play during SPD partially rescued the behavioral performance in the PRL, but did not prevent the decrease in PFC inhibitory synaptic inputs. Our data demonstrate the importance of unrestricted social play for the development of inhibitory synapses in the PFC and cognitive skills in adulthood and show that specific synaptic alterations in the PFC can result in a complex behavioral outcome.SIGNIFICANCE STATEMENT This study addressed the question whether social play behavior in juvenile rats contributes to functional development of the prefrontal cortex (PFC). We found that rats that had been deprived from juvenile social play (social play deprivation - SPD) showed a reduction in inhibitory synapses in the PFC and a simplified strategy to solve a complex behavioral task in adulthood. Providing one daily hour of play during SPD partially rescued the cognitive skills in these rats, but did not prevent the reduction in PFC inhibitory synapses. Our results demonstrate a key role for unrestricted juvenile social play in PFC development and emphasize the complex relation between PFC circuit connectivity and cognitive function.
BAS: A BTI-based aging aware synthesis in FPGAs

Aging mechanisms in FPGA devices cause performance degradation and lead to lifetime reduction. Among multiple aging mechanisms, Biased-Temperature-Instability (BTI) aging mechanism is the dominant one. BTI decreases the Static-Noise-Margin (SNM) of SRAM cells leading to more Soft-Error-Rate (SER) and lower SRAMs' stability in FPGAs. This paper proposes the BAS (BTI Aware Synthesis), a three-step post-synthesis and pre-place-and-route tool to reduce the impact of BTI in FPGA's LUTs significantly using the Bit-Flipping and Boolean Matching techniques. BAS receives a standard EDIF format synthesis output file from a synthesis tool (e.g., C.edf) and finally creates two output EDIF files with the same functionality as the original input file (e.g., C1.edf and C2.edf), while all LUT SRAMs contents are mutually flipped. The two BTI-Aware-created EDIF synthesis files are periodically used for FPGA's reconfiguration. Our experimental results demonstrates that BAS improves SNM and SER on average by 16.1% and 15.7% compared to previous state-of-the-art techniques, respectively. BAS has two main advantages over previous state-of-the-art techniques: (1) it is more flexible and applicable as an embedded tool within worldwide commercial synthesis tools, and (2) unlike the previous state-of-the-art techniques, it does not need the map and details of the FPGAs.
Catalase-peroxidase StKatG is a bacterial manganese oxidase from endophytic Salinicola tamaricis

Manganese (Mn) oxides in iron/manganese plaques are widely distributed in the rhizosphere of wetland plants and contribute significantly to elemental cycling and pollutant removal. Mn oxides are primarily produced by bacterial processes using Mn oxidases. However, the molecular mechanism underlying the formation of rhizosphere Mn oxides is still largely unknown. This study identified a manganese-oxidizing enzyme, the catalase-peroxidase StKatG, from an endophytic bacterium Salinicola tamaricis from the wetland plant. The gene encoding StKatG was cloned and overexpressed in Escherichia coli. The recombinant StKatG displayed different structure and enzymatic properties from the previously reported Mn oxidases. The enzyme activity of StKatG yielded Mn oxides with the mixed-valent state: Mn(II), Mn(III), and Mn(IV). The optimum pH and temperature for StKatG are 7.5 and 50 °C, respectively. Structurally, StKatG is organized into two domains, whereas the reported Mn oxidases are mainly single-domain proteins. Based on the site-directed mutagenesis studies, the presence of aspartic acid (Asp) residues in the loop of StKatG are critical to Mn-oxidizing activity. These findings identified a novel bacterial Mn oxidase and provided insights into the molecular mechanism of Mn oxidation in the plant rhizosphere.