Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and safety of novel carbapenem-β-lactamase inhibitor combinations: imipenem-cilastatin/relebactam results from randomized controlled trials

Background Gram-negative bacteria is a global public health problem. Treatment options include novel beta-lactamase inhibitors. Objectives The objective of this study was to collect information on the efficacy and safety of novel β-lactamase inhibitor combinations such as imipenem-cilastatin/relebactam (IMI/REL). Methods In order to comprehensively evaluate the clinical, microbiological, and adverse events outcomes, a meta-analysis was conducted on clinical trials comparing novel β-lactamase inhibitor combinations with existing comparator therapies. Results Four studies comprising 948 patients were included in the analysis. IMI/REL therapy demonstrated similar clinical responses to comparators across various treatment visits, including discontinuation of intravenously administered therapy visits [DCIV, RR = 1.00 (0.88, 1.12)], early follow-up visits [EFU, RR = 1.00 (0.89, 1.14)], late follow-up visits [LFU, RR = 1.00 (0.88, 1.13)]. Moreover, no significant difference in the microbiologic response of MITT patients was observed between IMI/REL and comparators across DCIV [RR = 0.99 (0.89, 1.11)], EFU [RR = 1.01 (0.95, 1.07)], and LFU visits [RR = 1.00 (90.94, 1.07)]. In terms of safety, therapy with IMI/REL and comparators exhibited similar risks of at least one adverse event (AE), drug-related AEs, and discontinuation due to AEs. The incidence of serious AEs (SAEs) was significantly lower in the IMI/REL group compared to the comparison groups. The predominant AEs were gastrointestinal disorders, with no significant difference observed between the IMI/REL group and comparators. Conclusion The clinical and microbiologic response to IMI/REL in the treatment of bacterial infection was comparable to that of the comparator. Furthermore, the incidence of AEs and the tolerability of IMI/REL were similar among the comparators. Based on these findings, IMI/REL can be considered as a viable alternative treatment option.
Insights into the behavior and kinetics of purun tikus degradation during slow pyrolysis

Purun tikus (Elocharis dulcis), a type of wetland biomass feedstock, is a challenge to the swamp ecosystem as it contributes to pollution in the area. Hence, integrating the use of purun tikus as a source of bioenergy, particularly in the form of bio-oil, is of the highest priority. Nevertheless, there is a lack of research on the degradation rate of purun tikus conversion to bio-oil through pyrolysis. Thus, this study aims to evaluate the rate of destruction of purun tikus in the process of conversion into bio-oil via pyrolysis. In the experiment, a batch reaction vessel was used to carry out slow pyrolysis at temperatures ranging from 300 to 500 °C, and the reaction times ranged from 60 to 120 min. By assuming a first-order process and using the Arrhenius equation, it was possible to figure out the activation energy and the preexponential factort. To determine whether purun tikus destroyed during pyrolysis, an activation energy of 43.317 kJ mol-1 and a pre-exponential factor of 0.351 s-1 were identified.
An Integrated ddPCR Lab-on-a-Disc Device for Rapid Screening of Infectious Diseases

Digital droplet PCR (ddPCR) is a powerful amplification technique for absolute quantification of viral nucleic acids. Although commercial ddPCR devices are effective in the lab bench tests, they cannot meet current urgent requirements for on-site and rapid screening for patients. Here, we have developed a portable and fully integrated lab-on-a-disc (LOAD) device for quantitively screening infectious disease agents. Our designed LOAD device has integrated (i) microfluidics chips, (ii) a transparent circulating oil-based heat exchanger, and (iii) an on-disc transmitted-light fluorescent imaging system into one compact and portable box. Thus, droplet generation, PCR thermocycling, and analysis can be achieved in a single LOAD device. This feature is a significant attribute for the current clinical application of disease screening. For this custom-built ddPCR setup, we have first demonstrated the loading and ddPCR amplification ability by using influenza A virus-specific DNA fragments with different concentrations (diluted from the original concentration to 107 times), followed by analyzing the droplets with an external fluorescence microscope as a standard calibration test. The measured DNA concentration is linearly related to the gradient–dilution factor, which validated the precise quantification for the samples. In addition to the calibration tests using DNA fragments, we also employed this ddPCR-LOAD device for clinical samples with different viruses. Infectious samples containing five different viruses, including influenza A virus (IAV), respiratory syncytial virus (RSV), varicella zoster virus (VZV), Zika virus (ZIKV), and adenovirus (ADV), were injected into the device, followed by analyzing the droplets with an external fluorescence microscope with the lowest detected concentration of 20.24 copies/µL. Finally, we demonstrated the proof-of-concept detection of clinical samples of IAV using the on-disc fluorescence imaging system in our fully integrated device, which proves the capability of this device in clinical sample detection. We anticipate that this integrated ddPCR-LOAD device will become a flexible tool for on-site disease detection.
Emotional Intelligence Model in Educational Computer Games

This article explores the relationship between emotional intelligence and game development, proposing a unique game EI model based on the ambivalence of emotions. The model suggests that a player's emotional state affects their game strategy and addresses how to overcome frustration and aggression. It also recommends taking breaks, live communication, and self-analysis during gameplay to avoid limiting cognitive function. The impersonal EI test question's transformation into game components of mechanics, dynamics and aesthetics, as well as active and deeper learning strategies, is described. Recommendations are created for conducting any game under the dynamic model of EI, or for the educational games design.
Neural Network Architectures for Recognizing Military Objects on Satellite Images

This paper is devoted to the research and comparison of neural network architectures for recognizing military objects on satellite images. The paper analyzes the current state of the problem of object recognition, in particular, military objects on satellite images. In addition, the authors researched existing technologies and tools for recognizing military objects on satellite images, and also implemented models of neural networks with different architectures for detecting military objects. The influence of learning indicators of neural network models on the recognition and detection of objects on satellite and aerial photographs was investigated. As a result of the work, one multilayer perceptron, three models of convolutional neural networks, and neural networks with VGG and XCeption architectures were implemented and investigated, their main advantages and disadvantages were determined, and software with corresponding neural network architectures was developed using the Google Colab cloud service. The best results were shown by sixth model with a convolutional neural network architecture, the main difference of which was a gradual reduction in the number of filters and the size of the kernel on the convolutional layers.
Court Detection Using Masked Perspective Fields Network

Court detection is an important step in sports video analytics. Its goal is to find a projective transformation matrix which projects a standard court to the one visible in the video frame. The inverse of the transformation matrix allows the pixels in the video frame to be projected back to the standard court, hence, provides measurements in the physical world coordinates. Instead of finding the transformation matrix directly, we design a deep fully convolutional neural network to estimate a Perspective Fields (PF) between the court in the source image and the court in a reference image. Our network has two branches, one outputs the PF, the other outputs the court lines which serves as the mask to guide the network to focus on the relevant parts of the input images, thereby finding the transformation pertaining to the court only. Our network is sport-agnostic, which means it is easily generalizable to different types of sports.
The Clinical Performance of Cell Population Data for Diagnosis of Bloodstream Infection in Cancer Patients

Background Bloodstream infection (BSI) induces a change in the number and morphology of blood cells. In this study, we compared cell population data (CPD) parameters between cancer patients with or without BSI to determine whether these parameters could serve as biomarkers of BSI. Methods Between April and June 2021, 43 BSI-negative and 22 BSI-positive cancer patients were enrolled in this study. We compared 18 CPD parameters and biomarkers between cancer patients with BSI-positive and BSI-negative. Results There were significant differences in the levels of several CPD parameters, including MO-WZ (p=0.040), MO-X (p<0.01), MO-Y (p=0.012), NE-SFL (p<0.01), and NE-WX (p=0.037), but not C-reactive protein (p=0.347) and procalcitonin (p=0.237) between BSI-positive and BSI-negative patients. The areas under the receiver-operating characteristic curves (AUCs) were above 0.7 for MO-X (0.762; 95% confidence intervals (CI): 0.624-0.901), NE-SFL (0.766; 95% CI: 0.625-0.880). And LY-WY (p=0.024) showed a significant difference between gram-negative and gram-positive BSI patients with high AUC (0.883; 95% CI: 0.703-1). Conclusion CPD parameters (MO-X and NE-SFL) provide additional information for discriminating between BSI-negative and BSI-positive BSI. And LY-WY provides useful information for discriminating between cancer patients with gram-negative BSI and gram-positive BSI.
Indoor Positioning Based on the Integration of IMU and UWB

Accurate indoor location information is of utmost importance for the navigation of modern indoor mobile robots. However, achieving accurate positioning solely with ultra-wideband (UWB) technology in indoor environments is challenging due to the susceptibility of UWB measurements to non-line-of-sight (NLOS) effects. To address this issue, this paper proposes an indoor positioning system that integrates an inertial measurement unit (IMU) with UWB. Firstly, an analysis of the errors present in UWB measurement data leads to the development of a two-step calibration method based on least squares (LS) to estimate error parameters. Subsequently, an Extended Kalman Filter (EKF)-based integration localization algorithm for IMU and UWB is proposed to mitigate the impact of NLOS. Through comprehensive simulations, the suggested algorithm's performance is assessed and contrasted with the weighted least squares (WLS) approach. Experimental findings show that the two-step LS-based calibration method estimates error parameters with accuracy. Moreover, the EKF-based IMU and UWB integration algorithm achieves approximately half improvement in localization accuracy compared to WLS, it also demonstrates excellent robustness. Consequently, the suggested indoor positioning system, which integrates IMU and UWB, satisfies the requirements for accuracy for indoor mobile robot navigation.
Impact of SNR, peripheral auditory sensitivity, and central cognitive profile on the psychometric relation between pupillary response and speech performance in CI users

Despite substantial technical advances and wider clinical use, cochlear implant (CI) users continue to report high and elevated listening effort especially under challenging noisy conditions. Among all the objective measures to quantify listening effort, pupillometry is one of the most widely used and robust physiological measures. Previous studies with normally hearing (NH) and hearing-impaired (HI) listeners have shown that the relation between speech performance in noise and listening effort (as measured by peak pupil dilation) is not linear and exhibits an inverted-U shape. However, it is unclear whether the same psychometric relation exists in CI users, and whether individual differences in auditory sensitivity and central cognitive capacity affect this relation. Therefore, we recruited 17 post-lingually deaf CI adults to perform speech-in-noise tasks from 0 to 20 dB SNR with a 4 dB step size. Simultaneously, their pupillary responses and self-reported subjective effort were recorded. To characterize top-down and bottom-up individual variabilities, a spectro-temporal modulation task and a set of cognitive abilities were measured. Clinical word recognition in quiet and Quality of Life (QoL) were also collected. Results showed that at a group level, an inverted-U shape psychometric curve between task difficulty (SNR) and peak pupil dilation (PPD) was not observed. Individual shape of the psychometric curve was significantly associated with some individual factors: CI users with higher clinical word and speech-in-noise recognition showed a quadratic decrease of PPD over increasing SNRs; CI users with better non-verbal intelligence and lower QoL showed smaller average PPD. To summarize, individual differences in CI users had a significant impact on the psychometric relation between pupillary response and task difficulty, hence affecting the interpretation of pupillary response as listening effort (or engagement) at different task difficulty levels. Future research and clinical applications should further characterize the possible effects of individual factors (such as motivation or engagement) in modulating CI users’ occurrence of ‘tipping point’ on their psychometric functions, and develop an individualized method for reliably quantifying listening effort using pupillometry.
Biosimilars in rheumatoid arthritis in 2022 – data from the Romanian Registry of Rheumatic Diseases

Objective. The study aimed at determining whether RA patients starting or stopping biosimilars differ in any regard from those starting or stopping originals. Methods. Data on RA patients was obtained from the Romanian Registry of Rheumatic Diseases (RRBR) database between January 1st, 2022, and December 31st, 2022, encompassing all Romanian RA patients fulfilling the national criteria for bo/bsDMARD initiation, continuation or switching. Results. Etanercept and adalimumab predominated for initiations of biosimilars. Most entries on biosimilars originated from originals (including non-medical switches) and from bDMARDs without biosimilars. A historical effect of accumulation of patients was observed, manifested in the fact that originals still dominated the group of patients continuing their treatment, with the exception of infliximab, while biosimilars tended to be continued in younger patients and in patients with shorter disease duration. Cases categorized more severe by both patients, their doctors and their disease activity were preferably reserved for originals. In patients continuing their previous bDMARD, biosimilars exhibited higher DAS28 and SDAI remission rates. Conclusion. RRBR data from 2022 confirm the market rise of biosimilars in RA, but also physicians’ prudence in prescribing them to highly active cases. In the Romanian RA cohort, biosimilars are overall more effective in holding remission than originals.
An assessment of the Determinants of Inflation in Nepal: A study between 1974/75 and 2021/22

Inflation is one of the important and interestingly touchy macroeconomic variables that influences other macroeconomic variables such as investment, consumption, saving and others. Therefore, it has become renewed interest in recent years mainly for both developed and developing countries. This paper examined the short-run and long-run relationship between inflation and its determinants in Nepal using time series data over the period of 1974/75-2021/22. The ARDL bound test approach to co-integration and error correction model have been used to examine the long-run and short-run relationship between variables. The results from ARDL bound test approach to co-integration show that broad money supply, Indian inflation and budget deficit have a significant positive effect on inflation while exchange rate negatively affect it in the long-run. The result from error correction model also found that Nepalese inflation and Indian inflation are significantly and positively related even in the short-run. However, real GDP affects inflation negatively as expected but it is statistically insignificant. A corollary of the results is that broad money supply, budget deficit, Indian inflation and exchange rate are the main drivers of inflation in Nepal.
Drinking patterns, alcoholic beverage types, and esophageal cancer risk in Africa: a comprehensive systematic review and meta-analysis

Africa is the continent most affected by esophageal cancer in the world. Alcoholic beverages are controversially blamed, as esophageal cancer is a rare disease in several other countries ranked in the top 10 for consumption of alcoholic beverages. This study aims to conduct a comprehensive systematic review of published literature, statistically summarizing the strength of the association between drinking patterns and types, and the risk of esophageal cancer in Africa. A computerized search of reputable databases such as Medline/PubMed, EMBASE, Web of Science, and African Journals Online was performed to identify relevant studies published up to September 2023. The quality of the studies was evaluated using the Newcastle-Ottawa scale for case-control studies and the Agency for Healthcare Research and Quality tool for cross-sectional studies. A funnel plot and Egger test were utilized to assess potential publication bias. Meta-analyses were conducted using random-effects models with RevMan 5.3 and Stata software to estimate summary effects. The systematic review identified a total of 758,203 studies, primarily from Eastern and Southern Africa. The pooled samples across all studies comprised 29,026 individuals, including 11,237 individuals with cancer and 17,789 individuals without cancer. Meta-analysis revealed a significant association between alcohol consumption and the risk of esophageal cancer (odds ratio [OR] = 1.81; 95% confidence interval [CI], 1.50-2.19). Further analysis based on the frequency of alcoholic beverage consumption indicated a stronger association with daily (OR = 2.38; 95% CI, 1.81-3.13) and weekly (OR = 1.94; 95% CI, 1.32-2.84) drinkers in contrast to occasional drinkers (OR = 1.02; 95% CI, 0.81-1.29). Additionally, consumption of traditional alcoholic beverages was significantly associated with the risk of esophageal cancer in African populations (OR = 2.00; 95% CI, 1.42-2.82). However, no relationship has been established between the exclusive consumption of non-traditional drinks and the risk of esophageal cancer. In conclusion, the results of this study confirm the hypothesis that daily and weekly drinking patterns, significantly increase the risk of esophageal cancer in Africa, while occasional consumption does not show a significant association. Additionally, the consumption of traditional alcoholic beverages is notably linked to the risk of esophageal cancer in African populations.
Disentangling a metabolic cross-feeding in a halophilic archaea-bacteria consortium

Microbial syntrophy, a cooperative metabolic interaction among prokaryotes, serves a critical role in shaping communities, due to the auxotrophic nature of many microorganisms. Syntrophy played a key role in the evolution of life, including the hypothesized origin of eukaryotes. In a recent exploration of the microbial mats within the exceptional and uniquely extreme Cuatro Cienegas Basin (CCB), a halophilic isolate, designated as AD140, emerged as a standout due to its distinct growth pattern. Subsequent genome sequencing revealed AD140 to be a co-culture of a halophilic archaeon from the Halorubrum genus and a marine halophilic bacterium, Marinococcus luteus, both occupying the same ecological niche. This intriguing coexistence hints at an early-stage symbiotic relationship that thrives on adaptability. By delving into their metabolic interdependence through genomic analysis, this study aims to uncover shared characteristics that enhance their symbiotic association, offering insights into the evolution of halophilic microorganisms and their remarkable adaptations to high-salinity environments.
Lidar observations of aerosol loadings extended throughout the troposphere

Durable aerosol/dust loadings affecting the atmosphere over the city of Sofia, Bulgaria (42.65 N, 23.38 E) were monitored by a Nd:YAG-laser-based lidar, from April to July 2009. The events lasted almost throughout the entire period. This study is only focused on the experimental results obtained on 15 and 23 April, when extraordinary in altitude (up to 15 km) aerosol layers were detected. For the two days, Dust Regional Atmospheric Model, provided by the Barcelona Super-Computing Center, had forecast Saharan dust incursions over Bulgaria. The origin of the aerosol layers detected by the lidar was identified using the Hybrid Single-Particle Lagrangian Integrated Trajectory model for calculations of the backward air-mass trajectories. The results of measurements are presented in terms of time-averaged vertical profiles of the atmospheric backscatter coefficient and color maps in height-time coordinates, which illustrate the aerosol-mass spatial distribution and its temporal evolution, within the stable layers registered. Retrieved profiles at the two lidar wavelengths (532 nm and 1064 nm) are used to calculate the corresponding profiles of the backscatter-related Ǻngström exponent as a qualitative indicator of the dominant aerosol particle size fractions in the layers observed.
SBCDNet: An Efficient Sparse-Based Deep Cascade Blood Cancer Detection Network

Automated and early diagnosis of blood cancer is an essential task. Currently, deep learning-based systems are widely used for medical diagnosis. However, the major drawbacks of such systems are the requirement of huge labeled databases and slow training. Thus, an efficient sparse-based deep cascade model is proposed to make the diagnosis of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) more accurate. The major contributions are as follows. 1) A novel sparse-based deep cascade blood cancer detection network (SBCDNet) is proposed to yield outstanding performance in small databases. 2) An efficient single-level deep cascade model is suggested for selecting more important features and making the system faster and more accurate. 3) Softmax vector coding of errors is used to achieve nonlinear transformation in layer-wise learning. 4) Modified Fast Iterative Shrinkage, and Thresholding Algorithm is employed to solve inverse linear problems. Experimental results demonstrate that the proposed SBCDNet outperforms its competitors with the best performances, including 98.15% and 97.50% accuracies for ALL and AML detection, respectively.
Producing Renewable Energy from Municipal Wastewater Treatment Using a Bio–electrochemical System

: Concurrent renewable energy production and wastewater treatment are two main reasons for using microbial fuel cells (MFCs). In this study, real wastewater was used for treating and power generation by air cathode microbial desalination cells (ACMFC). The total duration of voltage generation by ACMFC was about 151.9 ±23.2 h. The maximum voltage produced from municipal wastewater treatment was 270 mV. The maximum power and current density calculated as 103 mW/m 2 and 382 mA/m 2 , respectively. The change percentage of EC in wastewater obtained 28.87 ±9.77. The average change percentage of pH at the beginning and end of a fed–bacth phase in wastewater was about 7.3 ±0.34. The COD removal efficiency of wastewater was about 81.40 ±0.74%. The columbic efficiency was obtained 68.58 ±7.95.