Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction of Multidrug-Resistant (MDR) Bacterial Infections during the COVID-19 Pandemic: A Retrospective Study

Multidrug-resistant (MDR) organisms are emerging as some of the main healthcare problems worldwide. During the COVID-19 pandemic, several Infection Prevention and Control (IPC) measures have been adopted to reduce nosocomial microorganism transmission. We performed a case–control study to identify if the incidence of MDR bacterial infections while using pandemic-related preventive measures is lower than in previous years. From 2017 to 2020, we monitored hospital discharges over a four-month period (P #) (1 March to 30 June) in St. Andrea Hospital, Rome. In total, we reported 1617 discharges. Pearson’s chi-squared test was used to identify significant differences. A value of p ≤ 0.05 was considered statistically significant. A significant reduction in the incidence of total MDR bacterial infections was observed during the pandemic compared to in prepandemic years (p < 0.05). We also found a significantly higher incidence of MDR bacterial infections in COVID-19 departments compared with other medical departments (29% and 19%, respectively), with extended-spectrum β-lactamase Klebsiella pneumoniae as the pathogens presenting the highest increase. This study demonstrates that maintaining a high level of preventive measures could help tackle an important health problem such as that of the spread of MDR bacteria.
Early Adolescent Social Media–Related Body Dissatisfaction: Associations with Depressive Symptoms, Social Anxiety, Peers, and Celebrities

ABSTRACT: Objective: It is critical to examine the powerful socializing effects of networked media on early adolescents when social media use, body self-consciousness, and social comparisons are at their peak. Method: Using 2 subsamples (N = 374 and N = 396) of those aged 11 to 14 years from a larger survey sample of 700 middle school participants in the Northeast United States, we conducted a cross-sectional pilot survey using brief, descriptive body dissatisfaction measures directly related to social media use. Results: Within our body dissatisfaction subsample, 19% reported dissatisfaction to body image issues. Participants' most common concerns around body image included not being thin enough, not attractive enough, and feeling dissatisfaction with body shape, hair, and face. The results from analysis of covariance analyses showed that those reporting social media–related body dissatisfaction checked their social media more frequently. When compared with those who did not feel negatively about their body image because of social media, those who did had higher rates of depressive symptoms, had online social anxiety, had found it harder to make new friends, and were more socially isolated. Those who followed celebrities checked social media more frequently and were more likely to have depressive symptoms and online social anxiety. Conclusion: There may be negative socioemotional health consequences of early adolescent social media users with exposure to particular sources of social media content, such as photographs of celebrities.
A General Framework for Making Context-Recognition Systems More Energy Efficient †

Context recognition using wearable devices is a mature research area, but one of the biggest issues it faces is the high energy consumption of the device that is sensing and processing the data. In this work we propose three different methods for optimizing its energy use. We also show how to combine all three methods to further increase the energy savings. The methods work by adapting system settings (sensors used, sampling frequency, duty cycling, etc.) to both the detected context and directly to the sensor data. This is done by mathematically modeling the influence of different system settings and using multiobjective optimization to find the best ones. The proposed methodology is tested on four different context-recognition tasks where we show that it can generate accurate energy-efficient solutions—in one case reducing energy consumption by 95% in exchange for only four percentage points of accuracy. We also show that the method is general, requires next to no expert knowledge about the domain being optimized, and that it outperforms two approaches from the related work.
Identification of factors influencing severity of motorcycle crashes in Dhaka, Bangladesh using binary logistic regression model

Abstract Dhaka, the capital and megacity of the developing country Bangladesh, has experienced a sharp rise in motorcycle users in the last decade, especially after the introduction of ridesharing services. Therefore, the morbidity and mortality rates of motorcycle crash injuries have also increased and become one of the major safety concerns. However, there is scant empirical evidence on motorcycle crash severity in the context of developing countries. Hence, this study was conducted to identify the factors that influenced the severity of motorcycle crashes in Dhaka. A binary logistic regression model was developed using motorcycle crash data of Dhaka over the period of 2006–2015 to identify the contributing factors of motorcycle crash severity. The model output showed that eleven factors significantly increased the probability of fatal motorcycle crashes. These factors were crashes occurring on weekends, during the rainy season, during dawn and night period, at non-intersections, on straight and flat roads, on highways, hit pedestrian type crashes, crashes involving motorcycles with no defect, crashes with heavier vehicles, crashes involving motorcyclists not wearing helmets, and drivers with alcohol suspicion. These findings would help to formulate prevention strategies to reduce the injury severity of motorcycle crashes in the developing countries.
Periodic Analysis of Surface Acoustic Wave Resonator with Dimensionally Reduced PDE Model Using COMSOL Code

Radio-frequency (RF) surface acoustic wave (SAW) resonators used as filters and duplexers are mass-produced and widely used in current mobile phones. With the numerous emergences of the diverse device structure, a universal method used for the accurate and fast simulation of the SAW resonator calls for urgent demand. However, there are too many instances where the behavior of the entire acoustic resonator cannot be characterized rapidly and efficiently due to limitations in the current computer memory and speed. This is especially true for SAW resonators configured with long arrays of inter-digital transducers (IDTs), and we have to resort to a periodic analysis. In this paper, the previously reported generalized partial differential equations (PDE) based on the two-dimensional finite element method (2D-FEM) model is extended to analysis for the periodic structure of the SAW resonator. We present model order reduction (MOR) techniques based on FEM and periodic boundary conditions to achieve a dimensionally reduced PDE model without decreasing the accuracy of computations. Examples of different SAW devices, including the regular SAW, IHP-SAW and TC-SAW resonators, are provided which shows the results of the periodic analysis compared with the experimental results of the actual resonators. The investigation results demonstrate the properties of the proposed methodology and prove its effectiveness and accuracy.
Association between intra‐operative cardiac arrest and country Human Development Index status: a systematic review with meta‐regression analysis and meta‐analysis of observational studies *

Intra‐operative cardiac arrests differ from most in‐hospital cardiac arrests because they reflect not only the patient's condition but also the quality of surgery and anaesthesia care provided. We assessed the relationship between intra‐operative cardiac arrest rates and country Human Development Index (HDI), and the changes occurring in these rates over time. We searched PubMed, EMBASE, Scopus, LILACS, Web of Science, CINAHL and SciELO from inception to 29 January 2020. For the global population, rates of intra‐operative cardiac arrest and baseline ASA physical status were extracted. Intra‐operative cardiac arrest rates were analysed by time, country HDI status and ASA physical status using meta‐regression analysis. Proportional meta‐analysis was performed to compare intra‐operative cardiac arrest rates and ASA physical status in low‐ vs. high‐HDI countries and in two time periods. Eighty‐two studies from 25 countries with more than 29 million anaesthetic procedures were included. Intra‐operative cardiac arrest rates were inversely correlated with country HDI (p = 0.0001); they decreased over time only in high‐HDI countries (p = 0.040) and increased with increasing ASA physical status (p < 0.0001). Baseline ASA physical status did not change in high‐HDI countries (p = 0.106), while it decreased over time in low‐HDI countries (p = 0.040). In high‐HDI countries, intra‐operative cardiac arrest rates (per 10,000 anaesthetic procedures) decreased from 9.59 (95%CI 6.59–13.16) pre‐1990 to 5.17 (95%CI 4.42–5.97) in 1990–2020 (p = 0.013). During the same time periods, no improvement was observed in the intra‐operative cardiac arrest rates in low‐HDI countries (p = 0.498). Odds ratios of intra‐operative cardiac arrest rates in ASA 3–5 patients were 8.48 (95%CI 1.67–42.99) times higher in low‐HDI countries than in high‐HDI countries (p = 0.0098). Intra‐operative cardiac arrest rates are related to country‐HDI and decreased over time only in high‐HDI countries. The widening gap in these rates between low‐ and high‐HDI countries needs to be addressed globally.
Reported differences in the flg22 response of the null mutation of AtRGS1 correlates with fixed genetic variation in the background of Col-0 isolates

ABSTRACT A role for the heterotrimeric G protein complex in the induction of a transient burst of reactive oxygen species (ROS) by the Microbial-Associated Molecular Pattern, flg22, a 22-amino acid peptide derived from bacterial flagella, is well established. However, the evidence for a negative or positive role for one component of the Arabidopsis G protein complex, namely, Regulator of G Signaling 1 (AtRGS1) leads to opposing conclusions. We show that the reason for this difference is due to the isolate of Col-0 ecotype used as the wildtype control in flg22-induced ROS and our data further support the idea that AtRGS1 is a negative regulator of the flg22-induced ROS response. Whole-genome genotyping led to the identification and validation of polymorphism in five genes between two Col-0 isolates that are candidates for the different ROS response relative to the rgs1 null mutant.
Pneumococcal Colonization and Virulence Factors Identified Via Experimental Evolution in Infection Models

Abstract Streptococcus pneumoniae is a commensal of the human nasopharynx and a major cause of respiratory and invasive disease. We examined adaptation and evolution of pneumococcus, within nasopharynx and lungs, in an experimental system where the selective pressures associated with transmission were removed. This was achieved by serial passage of pneumococci, separately, in mouse models of nasopharyngeal carriage or pneumonia. Passaged pneumococci became more effective colonizers of the respiratory tract and we observed several examples of potential parallel evolution. The cell wall-modifying glycosyltransferase LafA was under strong selection during lung passage, whereas the surface expressed pneumococcal vaccine antigen gene pvaA and the glycerol-3-phosphate dehydrogenase gene gpsA were frequent targets of mutation in nasopharynx-passaged pneumococci. These mutations were not identified in pneumococci that were separately evolved by serial passage on laboratory agar. We focused on gpsA, in which the same single nucleotide polymorphism arose in two independently evolved nasopharynx-passaged lineages. We describe a new role for this gene in nasopharyngeal carriage and show that the identified single nucleotide change confers resistance to oxidative stress and enhanced nasopharyngeal colonization potential. We demonstrate that polymorphisms in gpsA arise and are retained during human colonization. These findings highlight how within-host environmental conditions can determine trajectories of bacterial evolution. Relative invasiveness or attack rate of pneumococcal lineages may be defined by genes that make niche-specific contributions to bacterial fitness. Experimental evolution in animal infection models is a powerful tool to investigate the relative roles played by pathogen virulence and colonization factors within different host niches.
Teicoplanin‐Based Enantioselective, Potentiometric Membrane Electrodes for the Determination of R‐Baclofen in Pharmaceutical Formulations

Abstract Two enantioselective, potentiometric membrane electrodes were proposed for the assay of R‐baclofen. The electrodes were designed using a macrocyclic glycopeptide antibiotic, teicoplanin. Acetonitrile was added to the teicoplanin to design a modified teicoplanin‐based electrode. The linear concentration ranges for the proposed enantioselective, membrane electrodes were 10−7–10−4 mol/L for teicoplanin‐based electrode and 10−6–10−4 mol/L for the electrode based on teicoplanin modified with acetonitrile. The slopes of the electrodes were 60.0 mV/pR‐baclofen and 57.2 mV/pR‐baclofen for teicoplanin and teicoplanin modified with acetonitrile‐based electrodes, respectively. The enantioselectivity was determined over S‐baclofen. The proposed electrodes can be employed reliably for the assay of R‐baclofen raw material and from its pharmaceutical formulation, Norton‐Baclofen® tablets. The surfaces of the electrodes are stable and easily renewable by polishing on alumina paper.
The case for iron

Excess major nutrients occur in offshore areas ranging from the tropical equatorial Pacific to the polar Antarctic. In spite of the great ecological differences in these environments, the authors believe they share a common trait: iron deficiency. Here they present the case of iron; they point out that all of these areas are far from Fe-rich terrestrial sources and that atmospheric dust loads in these regions are among the lowest in the world. The authors summarize experiments performed in three nutrient-rich areas: The Gulf of Alaska, the Ross Sea, and the equatorial Pacific. In general, populations without added Fe doubled at rates 11-40% of the expected maxima at various temperatures. The additions of nanomole quantities of Fe increased these doubling rates by factors of 2-3. In spite of the lack of Fe, tightly coupled phytoplankton/zooplankton communities seem to inhabit these major nutrient-rich areas. Since Fe is required for the synthesis of chlorophyll and nitrate reductase, little chlorophyll is found and NH{sub 3} is the favored N source. Normal rate values of specific productivity indicate that these populations are healthy, but limited by the insufficient Fe supply. When Fe becomes available either artificially in bottle experiments or in the environment asmore » Fe-rich land masses are approached, diatoms quickly bloom, chlorophyll levels increase, and nutrient stocks are rapidly depleted. These combined results indicate that Fe availability is the primary factor controlling phytoplankton production in nutrient-rich areas of the open sea. « less
IoT-Based Bee Swarm Activity Acoustic Classification Using Deep Neural Networks

Animal activity acoustic monitoring is becoming one of the necessary tools in agriculture, including beekeeping. It can assist in the control of beehives in remote locations. It is possible to classify bee swarm activity from audio signals using such approaches. A deep neural networks IoT-based acoustic swarm classification is proposed in this paper. Audio recordings were obtained from the Open Source Beehive project. Mel-frequency cepstral coefficients features were extracted from the audio signal. The lossless WAV and lossy MP3 audio formats were compared for IoT-based solutions. An analysis was made of the impact of the deep neural network parameters on the classification results. The best overall classification accuracy with uncompressed audio was 94.09%, but MP3 compression degraded the DNN accuracy by over 10%. The evaluation of the proposed deep neural networks IoT-based bee activity acoustic classification showed improved results if compared to the previous hidden Markov models system.
Let’s Not Joke about It Too Much! Exposure to COVID-19 Messaging, Attitudes and Protective Behavioral Intentions

Our study evaluates the role of exposure to COVID-19 messaging in negativity towards COVID-19 and the intentions to engage in protective behaviors. Building on the theory of planned behavior (TPB), we derive a mediation model and test it in a sample of 737 participants (556 Romanians and 181 Kazakhs). The exposure to general information concerning COVID-19 positively predicts negative attitudes, negative emotions and the emergence of subjective norms in relation to COVID-19, as well as the likelihood of engaging in protective behavioral intentions. The exposure to humoristic communication, however, diluted the positive association between exposure to general information and negative attitudes, as well as negative emotions. The results support the overall predictions of the TPB and report positive associations between negative attitudes towards COVID-19, subjective norms and behavioral control on the one hand, and protective behavioral intentions on the other. Negative emotions significantly predict the likelihood of engaging in protective behaviors. Our results also show that older respondents tend to develop more negative attitudes towards COVID-19, yet they do not report stronger intentions to engage in protective behaviors than younger respondents. An important emergent result shows that time lapse seems to increase negativity towards COVID-19, yet it does not directly increase the likelihood of engaging in protective behaviors. Implications for public health communication related to COVID-19 are discussed.
Repolarization Stratification for Dipole Electrocardiotopography

The dipole component of the heart electric field has been analyzed in the context of distribution of the action potential onset timing and its duration. It has been demonstrated that the process of repolarization can be visualized as a sequence of layers with equal action potential (AP) completion time. Dipole moments of these layers can be calculated from the repolarization part of VCG and visualized as by dipole electrocardiography method (DECARTO) with the use of simple biophysical models. Such presentation will be useful for the analysis of heterogeneity of action potential characteristics in the ventricular myocardium and evaluation of its vulnerability to life-threatening arrhythmias.
Rumor surveillance in support of minimally invasive tissue sampling for diagnosing the cause of child death in low-income countries: A qualitative study

In low-and middle-income countries, determining the cause of death of any given individual is impaired by poor access to healthcare systems, resource-poor diagnostic facilities, and limited acceptance of complete diagnostic autopsies. Minimally invasive tissue sampling (MITS), an innovative post-mortem procedure based on obtaining tissue specimens using fine needle biopsies suitable for laboratory analysis, is an acceptable proxy of the complete diagnostic autopsy, and thus could reduce the uncertainty of cause of death. This study describes rumor surveillance activities developed and implemented in Bangladesh, Mali, and Mozambique to identify, track and understand rumors about the MITS procedure. Our surveillance activities included observations and interviews with stakeholders to understand how rumors are developed and spread and to anticipate rumors in the program areas. We also engaged young volunteers, local stakeholders, community leaders, and study staff to report rumors being spread in the community after MITS launch. Through community meetings, we also managed and responded to rumors. When a rumor was reported, the field team purposively conducted interviews and group discussions to track, verify and understand the rumor. From July 2016 through April 2018, the surveillance identified several rumors including suspicions of organs being harvested or transplanted; MITS having been performed on a living child, and concerns related to disrespecting the body and mistrust related to the study purpose. These rumors, concerns, and cues of mistrust were passed by word of mouth. We managed the rumors by modifying the consent protocol and giving additional information and support to the bereaved family and to the community members. Rumor surveillance was critical for anticipating and readily identifying rumors and managing them. Setting up rumor surveillance by engaging community residents, stakeholders, and volunteers could be an essential part of any public health program where there is a need to identify and react in real-time to public concern.
Relationship Between Residual Catalyst in Finished Cotton and Formaldehyde Release

An attempt was made to isolate the influence of residual catalysts on formaldehyde release from finished cotton fabrics. The study was conducted to separate the effects of free formaldehyde and formaldehyde liberated by finish degradation, attributed to hydrolytic action or equilibrium reversal from the presence of catalyst in the finished fabric. Differences were found among finishes in their stabilities to the action of residual catalysts, and among catalysts on a given finish.