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An Approach to Knee Osteoarthrosis as a Significant Pathology in the General and Military Population
Get PDFOsteoarthrosis (OA) is one of the most common joint diseases. It affects a significant portion of the population, among which the military, who suffer mainly from post-traumatic knee osteoarthrosis. Being aware of this relationship fosters early preventive and/or protective behaviours among health personnel and allows them to proceed with timely therapeutic measures
A Multicenter, Randomized, Placebo-Controlled Study to Evaluate the Efficacy and Safety of long-Acting Injectable Formulation of Vanoxerine (Vanoxerine Consta 394.2 mg) for Treatment of Amphetamine-Type Stimulant (ATS) Dependence
Get PDFObjective: To determine efficacy and tolerability of a long-acting intramuscular formulation of Vanoxerine (Vanoxerine Consta 394.2 mg) for treatment of Amphetamine-Type Stimulant (ATS)� dependent patients.Design, Setting, And Participants: A 12 weeks, A multicenter, randomized, placebo-controlled trial� conducted between November 2022--- December 2023, at 16 Hospital-based drug clinics, in the 15 countries. Participants were 18 years or older, had Diagnostic and Statistical Manual of Mental Disorders-5 Stimulant Use Disorder Amphetamine-Type (ATS). Of the 4000 individuals screened, 3300� (82.5%) adults were randomized, 1650 participants to receive injections of Long-acting depot formulations of�Vanoxerine (Vanoxerine Consta 394.2 mg) given intramuscularly once in 12 weeks and 1650� participants to receive Placebo injections, given intramuscularly once in 12 weeks
A Short Study on Relationship between ‘ABO’ Blood Groups and Coronavirus Disease 2019
Get PDFA Short study based on 204 patients with RT-PCR and Rapid Antigen Test proven SARS-CoV2 infection occurred in an urban municipality areas of total population more than 2 lakhs from March 2020 to August 2021, finding the relationship of covid -19 positive patients and their blood groups to search the link between susceptibility, severity and mortality with the blood groups. Current clinical observation suggest that gender and age of the patients are important risk factors in the susceptibility of Covid-19 infection. It is evident from the study that among the �ABO� Blood group system, B positive groups are more affected and AB positive groups are less affected but the severity or complications leading to death is evident among more in Blood Group �A� Positive and less in O positive cases. Among the negative groups. It has been shown that very less incidence is noted in O negative group. Why the negative groups are least affected, it is not clear to the researchers but it can be studied in details in near future.
 
Level of Awareness of Boat Captains in Terms of International Regulations for Preventing Collision at Sea in Region V1
Get PDFEpidemiological Profile of Asymptomatic Bacteriuria in Pregnant Women at the Mother and Child University Hospital Center of N’djamena: Associated Risk Factors and Antibiotic Resistance
Get PDFAsymptomatic bacteriuria in pregnant women is a bacterial urinary tract infection without any of the typical symptoms that are associated with a urinary tract infection whose urine culture meets the criteria for urinary tract infection corresponding to a colony count greater than 100 x 106 forming units of bacteria per liter.The objective of this work was to determine the prevalence of asymptomatic bacteriuria in pregnant women and to evaluate the effectiveness of antibiotics against isolated bacteria to better care for pregnant women
Agriculture Development and its Impact: A Comprehensive Time Series Analysis of Climate Variables
Get PDFClimate change poses significant challenges that necessitate the development of policies aimed at managing aggregate inputs and social costs. For formulating such policies, an analysis of its factors and their current trends needs to be studied. This paper explores the factors influencing climate change and provides insights into their impact through changes in arable land and greenhouse gas (GHG) emissions in India from 1990 to 2020. Utilizing time series analysis, the study examines trends in GHG emissions from agriculture and develops a simulation model to estimate overall GHG emissions through methane and nitrous oxide emissions. Results indicate that enteric fermentation and agricultural soil are major contributors to methane and nitrous oxide emissions, respectively, with enteric fermentation contributing approximately 69.33% to methane emissions and agricultural soil contributing approximately 97.66% to nitrous oxide emissions. Additionally, a higher growth rate is observed for nitrous oxide emissions than methane emissions, with nitrous oxide emissions showing a 161% increase from 1960 to 2010. Furthermore, a positive correlation (i.e. r=0.587) between GHG emissions and changes in annual mean temperature underscores the direct impact of agricultural emissions on climate dynamics in India, with a regression coefficient factor of 0.176. It is estimated that the overall GHG emission from agriculture through methane and nitrous oxide emission will be approximately 695.87 to 818.73 MMTCDE in the year 2030; while the change in annual mean temperature is estimated to be about 1.65 � 0.58o C from 1990 to 2030 in India. The findings highlight the urgent need for effective mitigation strategies within the agricultural sector to address the growing threat of climate change
Time Has Two Dimensions-Exploring Coordinate Connotation of Five-Dimensional Space
Get PDFFollowing Theodor Kaluza, Itzhak Bars and David Bohm�s idea, recognizing the rationality of B. Feng�s new physics theory, based on five-dimensional space, the corresponding coordinate connotation has determined through reasoning, represent as form as (x, y, z, ict, iat 2 ). Where, a is the curvature acceleration of light, and equals to 10 31 m/s 2 . It is believed to be the
limit acceleration in universe, nothing could beyond
Safeguarding our Atmosphere: Legal Measures and Health
Get PDFThe depletion of the ozone layer, a critical shield protecting the Earth from harmful ultraviolet (UV) radiotion, has become a global environ- mental concern. This paper highlights the legal dimensions surrounding Ozone-depleting substances (ODS), their impact on the Ozone layer, and the subsequent risk on human health specially regarding skin cancer and blindness. As countries navigate international agreements, domestic reg- ulations, and enforcement mechanisms, the intricate interplay between legal frameworks and health implication of ozone layer depletion comes to the forefront.
The paper also highlights specific cases of illegal trade in ozone deplet- ing substances provided by parities to the Montreal Protocol, examining statistics provided by parties to the Montreal Protocol. China emerges as a major producer of contraband ODS, while countries such as Bulgaria, Lithuania, Poland, and France report numerous cases. Analyzing these cases provides insights into the effectiveness of legal frameworks and enforcement agencies.
The paper concludes with a set of recommendations designed to spread control and enforcement against the illegal trade of ozone-depleting substances. These recommendations encompass multiple aspects, in- cluding production monitoring, customs collaboration, mutual verifica- tion, cross-border agreements, public-private partnerships, international cooperation, detection equipment, global regulatory standards, resource allocation, public awareness campaigns, alternative substance develop- ment, and controlling the trade at its source. By applying these recom- mendations and enhancing enforcement measures, we aim to protect the ozone layer and create a healthier and safer world for future generations and achieving the sustainable developments goals
Effect of the Plant Growth-forms on the Hydrological Fluxes in the Venezuelan Andean Paramos
Get PDFParamos are an important mountain ecosystem; they are essential water supplier to Andean population. Understanding its hydrological function is fundamental to preserve it, manage and to implement conservation programs. Little is known about the effect of paramos� vegetation upon the water fluxes. Evapotranspiration (EVT) is the main water output in this ecosystem and the most complex to measure. Using an ecosystem approach was estimated EVT through the net daily variation of soil water content (SWC) and was abstracted information about the other fluxes. The aim was assessing the effect of different plant life forms upon SWC and ETV. Therefore, TDR sensors were installed in the first 10cm into soils beneath different sort of covers (rossette, shrub and bare soil) and they were set up 10minute register, from March 2012 to November 2013. The shrub kept a SWC mean 36% higher than the rosette and like bare soils (bs). In the dry season, the rosette hold a SWC close to bs, but its SWCs were more stable, despite the rain decrease and its fluctuation.� In bs the soil water discharge was two times faster than under plant covers. In the driest period, the shrub maintained 120% much water and the rosette a half extra than bs. Below the shrub and bs the drainage had high likely. The runoff was not detected in any cover condition. The EVT was reduced a half by plants in the dry season, being the shrub effect more markable
Autonomous Phase Identification in X-ray Diffraction: A Hybrid Approach with Bayesian FusionNet and Feature-Optimized Ensemble Learning
Get PDFX-ray diffraction (XRD) plays a pivotal role in material characterization, offering valuable insights into crystalline structures. This study introduces a comprehensive framework for autonomous phase identification through a machine learning-guided approach. The proposed methodology comprises four key stages. In the pre-processing phase, raw data undergoes meticulous cleaning to eliminate noise, followed by normalization and smoothing procedures to ensure data integrity. Feature extraction involves a multi-faceted approach. Peak identification meticulously captures critical features such as peak position, intensity, and width within XRD patterns. Statistical features, encompassing mean, standard deviation, skewness, and kurtosis, provide a robust characterization of the dataset. The incorporation of Discrete Wavelet Transform further enriches the feature space by capturing both high and low-frequency information. For feature selection, a Hybrid Optimization Approach, combining the Kookaburra Optimization Algorithm (KOA) and White Shark Optimizer, is employed. This ensures an optimal subset of features for subsequent analysis. Phase identification is facilitated by a Bayesian FusionNet, integrating the strengths of Improved GhostNetV2, Bayesian Neural Network (BNN), and Feedforward Neural Network (FNN). The outcomes from these models are aggregated by taking the mean, enhancing the reliability and accuracy of phase identification. This innovative framework not only automates phase identification in X-ray diffraction but also showcases the efficacy of a hybridized machine learning approach, amalgamating optimization algorithms and neural networks for enhanced performance and interpretability. The proposed methodology holds significant promise for advancing material science research and facilitating efficient analysis in diverse applications