Tag: statistics

Sensors (Basel). 2023 Apr 27;23(9):4346. doi: 10.3390/s23094346.

ABSTRACT

The use of artificial intelligence (AI) to detect phishing emails is primarily dependent on large-scale centralized datasets, which has opened it up to a myriad of privacy, trust, and legal issues. Moreover, organizations have been loath to share emails, given the risk of leaking commercially sensitive information. Consequently, it has been difficult to obtain sufficient emails to train a global AI model efficiently. Accordingly, privacy-preserving distributed and collaborative machine learning, particularly federated learning (FL), is a desideratum. As it is already prevalent in the healthcare sector, questions remain regarding the effectiveness and efficacy of FL-based phishing detection within the context of multi-organization collaborations. To the best of our knowledge, the work herein was the first to investigate the use of FL in phishing email detection. This study focused on building upon a deep neural network model, particularly recurrent convolutional neural network (RNN) and bidirectional encoder representations from transformers (BERT), for phishing email detection. We analyzed the FL-entangled learning performance in various settings, including (i) a balanced and asymmetrical data distribution among organizations and (ii) scalability. Our results corroborated the comparable performance statistics of FL in phishing email detection to centralized learning for balanced datasets and low organizational counts. Moreover, we observed a variation in performance when increasing the organizational counts. For a fixed total email dataset, the global RNN-based model had a 1.8% accuracy decrease when the organizational counts were increased from 2 to 10. In contrast, BERT accuracy increased by 0.6% when increasing organizational counts from 2 to 5. However, if we increased the overall email dataset by introducing new organizations in the FL framework, the organizational level performance improved by achieving a faster convergence speed. In addition, FL suffered in its overall global model performance due to highly unstable outputs if the email dataset distribution was highly asymmetric.

PMID:37177549 | DOI:10.3390/s23094346

Sensors (Basel). 2023 Apr 26;23(9):4303. doi: 10.3390/s23094303.

ABSTRACT

Temperature-controlled closed-loop systems are vital to the transportation of produce. By maintaining specific transportation temperatures and adjusting to environmental factors, these systems delay decomposition. Wireless sensor networks (WSN) can be used to monitor the temperature levels at different locations within these transportation containers and provide feedback to these systems. However, there are a range of unique challenges in WSN implementations, such as the cost of the hardware, implementation difficulties, and the general ruggedness of the environment. This paper presents the novel results of a real-life application, where a sensor network was implemented to monitor the environmental temperatures at different locations inside commercial temperature-controlled shipping containers. The possibility of predicting one or more locations inside the container in the absence or breakdown of a logger placed in that location is explored using combinatorial input-output settings. A total of 1016 machine learning (ML) models are exhaustively trained, tested, and validated in search of the best model and the best combinations to produce a higher prediction result. The statistical correlations between different loggers and logger combinations are studied to identify a systematic approach to finding the optimal setting and placement of loggers under a cost constraint. Our findings suggest that even under different and incrementally higher cost constraints, one can use empirical approaches such as neural networks to predict temperature variations in a location with an absent or failed logger, within a margin of error comparable to the manufacturer-specified sensor accuracy. In fact, the median test accuracy is 1.02 degrees Fahrenheit when using only a single sensor to predict the remaining locations under the assumptions of critical system failure, and drops to as little as 0.8 and 0.65 degrees Fahrenheit when using one or three more sensors in the prediction algorithm. We also demonstrate that, by using correlation coefficients and time series similarity measurements, one can identify the optimal input-output pairs for the prediction algorithm reliably under most instances. For example, discrete time warping can be used to select the best location to place the sensors with a 92% match between the lowest prediction error and the highest similarity sensor with the rest of the group. The findings of this research can be used for power management in sensor batteries, especially for long transportation routes, by alternating standby modes where the temperature data for the OFF sensors are predicted by the ON sensors.

PMID:37177507 | DOI:10.3390/s23094303

Mult Scler Relat Disord. 2023 Apr 16;75:104719. doi: 10.1016/j.msard.2023.104719. Online ahead of print.

ABSTRACT

BACKGROUND: Teriflunomide (TER) (Aubagio™) is an FDA-approved disease-modifying therapy (DMT) for relapsing-remitting multiple sclerosis (RRMS). The mechanism of action of TER is thought to be related to the inhibition of dihydroorotate dehydrogenase (DHODH), a key mitochondrial enzyme in the de novo pyrimidine synthesis pathway required by rapidly dividing lymphocytes. Several large pivotal studies have established the efficacy and safety of TER in patients with RRMS. Despite this, little is known about how the adaptive and innate immune cell subsets are affected by the treatment in patients with MS.

METHODS: We recruited 20 patients with RRMS who were newly started on TER and performed multicolor flow cytometry and functional assays on peripheral blood samples. A paired t-test was used for the statistical analysis and comparison.

RESULTS: Our data showed that TER promoted a tolerogenic environment by shifting the balance between activated pathogenic and naïve or immunosuppressive immune cell subsets. In our cohort, TER increased the expression of the immunosuppressive marker CD39 on regulatory T cells (Tregs) while it decreased the expression of the activation marker CXCR3 on CD4⁺ T helper cells. TER treatment also reduced switched memory (sm) B cells while it increased naïve B cells and downregulated the expression of co-stimulatory molecules CD80 and CD86. Additionally, TER reduced the percentage and absolute numbers of natural killer T (NKT) cells, as well as the percentage of natural killer (NK) cells and showed a trend toward reducing the CD56^dim NK pathogenic subset.

CONCLUSION: TER promotes the tolerogenic immune response and suppresses the pathogenic immune response in patients with RRMS.

PMID:37172367 | DOI:10.1016/j.msard.2023.104719

J Environ Manage. 2023 May 10;341:118029. doi: 10.1016/j.jenvman.2023.118029. Online ahead of print.

ABSTRACT

Over the last two decades, forest cover has experienced significant impacts from fires and deforestation worldwide due to direct human activities and climate change. This paper assesses trends in forest cover loss and land use and land cover changes in northern Algeria between 2000 and 2020 using datasets extracted from Google Earth Engine (GEE), such as the Hanssen Global Forest Change and MODIS Land Cover Type products (MCD12Q1). Classification was performed using the pixel-based supervised machine-learning algorithm called Random Forest (RF). Trends were analyzed using methods such as Mann-Kendall and Sen. The study area comprises 17 basins with high rainfall variability. The results indicated that the forest area decreased by 64.96%, from 3718 to 1266 km², during the 2000-2020 period, while the barren area increased by 40%, from 134,777 to 188,748 km². The findings revealed that the Constantinois-Seybousse-Mellegue hydrographic basin was the most affected by deforestation and cover loss, exceeding 50% (with an area of 1018 km²), while the Seybouse River basin experienced the highest percentage of cover loss at 40%. Nonparametric tests showed that seven river basins (41%) had significantly increasing trends of forest cover loss. According to the obtained results, the forest loss situation in Algeria, especially in the northeastern part, is very alarming and requires an exceptional and urgent plan to protect forests and the ecological system against wildfires and climate change. The study provides a diagnosis that should encourage better protection and management of forest cover in Algeria.

PMID:37172351 | DOI:10.1016/j.jenvman.2023.118029

J Environ Manage. 2023 May 10;341:118124. doi: 10.1016/j.jenvman.2023.118124. Online ahead of print.

ABSTRACT

Currently, the phenomenon of direct interspecies electron transfer (DIET) is of great interest in the technology of anaerobic digestion (AD) due to potential performance benefits. However, the conditions for the occurrence of DIET and its limits on improving AD under conditions close to real have not been studied enough. This research is concentrated on the effect of conductive carbon cloth (R3), in comparison with a dielectric fiberglass cloth (R2) and control (R1), on the AD performance in large (90 L) thermophilic reactors, fed with a mixture of simulated organic fraction of municipal solid waste and sewage sludge. While organic loading rate (OLR) was gradually increased from 2.4 to 8.66 kg VS/(m³ day), a statistically significant (p < 0.05) difference in biogas production was observed between R1 and both R2 and R3. However, at a maximum OLR of 12.12 kg VS/(m³ day) in R3, an increase in biogas production (p < 0.05) was observed both compared to R1 (by 8.97%) and R2 (by 4.24%). The content of volatile fatty acids in R3 as a whole was the lowest, especially at the maximum OLR. Biofilm on carbon cloth was rich in syntrophic microorganisms of the genera Tepidanaerobacter, as well as Defluviitoga, capable of DIET in mixed cultures with Methanothrix, which was the most abundant methanogen in biofilm. Suspended Bifidobacterium, Fervidobacterium and Anaerobaculum were negatively affected, while Defluviitoga, Methanothermobacter and Methanosarcina, on the contrary, were positively affected by the increase in OLR and showed, respectively, a negative and positive correlation (p < 0.05) with the main AD performance parameters.

PMID:37172349 | DOI:10.1016/j.jenvman.2023.118124

J Environ Manage. 2023 May 10;341:118030. doi: 10.1016/j.jenvman.2023.118030. Online ahead of print.

ABSTRACT

PM_2.5 has been a hot concern in the recent decade. Many studies have focused on metropolises or those areas with poor air quality, but the PM_2.5 of more widespread areas is less considered. Considering the challenges of rapid economic growth and environmental problems against a developing region, we took Guiyang as a study case to assess the spatiotemporal variations and mechanism of PM2.5 pollution in an urban area from 2000 to 2020 in an extended sense. Based on PM_2.5 concentration data from 14 monitoring points in Guiyang, spatiotemporal variations and formation mechanism were assessed using wavelet, moving maximal information coefficients, and spatial correlation analysis. The urban Nighttime light data was selected to evaluate the impacts of socioeconomic factors on PM2.5 concentration using spatial correlation analysis. Further, wavelet and statistical analysis were adopted to analyze multi-dimensional temporal variations of PM_2.5 hourly concentration and the relationship with pressure, temperature, vapor pressure, relative humidity, wind, and visibility. The PM_2.5 hourly concentration was obtained from the monitoring points in downtown Guiyang according to data continuity and availability. PM_2.5 had different temporal variations at daily, monthly, seasonal, and annual levels, and interannual variation was the most obvious. The temperature was the main factor leading to the interannual temporal variation of PM_2.5. Wind and pressure were more significant for the responses of a shorter period variation with -0.76 and -0.80 of the minimum of correlation coefficient, respectively. Meanwhile, human activities significantly influenced spatiotemporal variations of PM_2.5. A spatial correlation analysis between PM2.5 and the related influencing factors from 2000 to 2018 was implemented based on a geographic information system. Besides, the landcovers within a buffer zone with a radius of 1 km on 14 monitoring points were visually interpreted to analyze the relationship between PM_2.5 and landcovers. Moreover, multivariate wavelet coherence analysis revealed the PM2.5 interaction among monitoring points. The PM_2.5 concentration in Guiyang dropped from 49 μg/m³ in 2012 to about 27 μg/m³ in 2018, and the air quality greatly improved. As in most cities, Guiyang has a significant PM_2.5 pollution island effect, with traffic and building land density contributing to higher PM_2.5 concentrations. There were some typical nonlinear spatiotemporal variations between PM_2.5 and its influencing factors, and these variations varied with the selected scale.

PMID:37172348 | DOI:10.1016/j.jenvman.2023.118030

Biomed Pharmacother. 2023 May 10;163:114823. doi: 10.1016/j.biopha.2023.114823. Online ahead of print.

ABSTRACT

Polypharmacy is becoming increasingly prevalent in society. Patients with polypharmacy are at greater risk for drug-drug interactions, which can influence the efficacy of treatment. Especially, in oncology this is a concern since neoplasms are increasing prevalent with age, as well as polypharmacy is. Besides drug-drug interactions, also herb-drug and food-drug interactions could be present. Knowledge of these interactions is of great importance for safe and effective anti-cancer treatment, because the therapeutic window of most of these oncologic drugs are small. To study pharmacokinetic interaction effects, a cross-over pharmacokinetic study is a widely used, efficient and scientifically robust design. Yet, several aspects need to be considered when carrying out an interaction study. This includes the knowledge of the advantages and disadvantages of a cross-over design. Furthermore, determination of the end point and research question of interest, calculation of the required sample size, analysis of the generated data with a robust statistical plan and consideration of the logtransformation for some pharmacokinetic parameters are important aspects to consider. Even though some guidelines exist regarding these key issues, no clear overview exists. In this article an overview of these aspects is provided and their effect is discussed.

PMID:37172331 | DOI:10.1016/j.biopha.2023.114823

Otolaryngol Head Neck Surg. 2023 May 12. doi: 10.1002/ohn.367. Online ahead of print.

ABSTRACT

OBJECTIVE: Previous behavioral studies on listening effort in tinnitus patients did not consider extended high-frequency hearing thresholds and had conflicting results. This inconsistency may be related that listening effort is not evaluated by the central nervous system (CNS) and autonomic nervous system (ANS), which are directly related to tinnitus pathophysiology. This study matches hearing thresholds at all frequencies, including the extended high-frequency and reduces hearing loss to objectively evaluate listening effort over the CNS and ANS simultaneously in tinnitus patients.

STUDY DESIGN: Case-control study.

SETTING: University hospital.

METHODS: Sixteen chronic tinnitus patients and 23 matched healthy controls having normal pure-tone averages with symmetrical hearing thresholds were included. Subjects were evaluated with 0.125 to 20 kHz pure-tone audiometry, Montreal Cognitive Assessment Test (MoCA), Tinnitus Handicap Inventory (THI), Visual Analog Scale (VAS), electroencephalography (EEG), and pupillometry.

RESULTS: Pupil dilation and EEG alpha band in the “coding” phase of the sentence presented in tinnitus patients was less than in the control group (p < .05). VAS score was higher in the tinnitus group (p < .01). Also, there was no statistically significant relationship between EEG and pupillometry components and THI or MoCA (p > .05).

CONCLUSION: This study suggests that tinnitus patients may need to make an extra effort to listen. Also, pupillometry may not be sufficiently reliable to assess listening effort in ANS-related pathologies. Considering the possible listening difficulties in tinnitus patients, reducing the listening difficulties, especially in noisy environments, can be added to the goals of tinnitus therapy protocols.

PMID:37172313 | DOI:10.1002/ohn.367

Foodborne Pathog Dis. 2023 May;20(5):169-176. doi: 10.1089/fpd.2022.0063.

ABSTRACT

This study evaluated the antagonistic effect of the Lacticaseibacillus paracasei JLM strain isolated from aguamiel, against Brucella abortus RB51, S19, and 2308 strains, during the manufacture of soft-ripened cheese. First, the tolerance of Lc. paracasei JLM was tested with pH values and bile salt concentrations for 3 h to simulate digestive tract conditions. The antagonistic effect against B. abortus strains was evaluated through double-layer diffusion and agar well diffusion assays. In addition, the stability of the cell-free supernatant (CFS) was tested with the agar well diffusion method under different conditions of temperature, pH, and treatment with digestive enzymes. Finally, the antagonistic effect against B. abortus strains was observed during the manufacture of ripened cheese for 31 days at 4°C and 25°C using the Lc. paracasei JLM strain as starter culture. The results showed that the Lc. paracasei JLM strain remains viable after exposure to different pH values (from 3.00 to 7.00) and concentrations of bile salts (from 0.5% to 7%). Moreover, the results demonstrate that the growth of the three B. abortus strains was inhibited in both antagonism tests and that CFS maintained 86% activity after heat treatment at 100°C, 121°C, or enzymatic digestion (proteinase K, trypsin, chymotrypsin), but it was inactivated at pH levels above 6. Finally, Lc. paracasei JLM completely inhibited the growth of B. abortus in ripened cheese at 25°C from day 17 and showed greater inhibition on the B. abortus RB51 strain in the ripened cheese at 4°C, showing statistical differences for the B. abortus S19 and B. abortus 2308 strains. The current research concluded that the Lc. paracasei JLM strain has an antagonistic effect on B. abortus, enhancing the potential of its use in the future as a probiotic.

PMID:37172300 | DOI:10.1089/fpd.2022.0063

Phys Rev Lett. 2023 Apr 28;130(17):171002. doi: 10.1103/PhysRevLett.130.171002.

ABSTRACT

We present the results of a direct measurement of the cosmic-ray helium spectrum with the CALET instrument in operation on the International Space Station since 2015. The observation period covered by this analysis spans from October 13, 2015, to April 30, 2022 (2392 days). The very wide dynamic range of CALET allowed for the collection of helium data over a large energy interval, from ∼40 GeV to ∼250 TeV, for the first time with a single instrument in low Earth orbit. The measured spectrum shows evidence of a deviation of the flux from a single power law by more than 8σ with a progressive spectral hardening from a few hundred GeV to a few tens of TeV. This result is consistent with the data reported by space instruments including PAMELA, AMS-02, and DAMPE and balloon instruments including CREAM. At higher energy we report the onset of a softening of the helium spectrum around 30 TeV (total kinetic energy). Though affected by large uncertainties in the highest energy bins, the observation of a flux reduction turns out to be consistent with the most recent results of DAMPE. A double broken power law is found to fit simultaneously both spectral features: the hardening (at lower energy) and the softening (at higher energy). A measurement of the proton to helium flux ratio in the energy range from 60 GeV/n to about 60 TeV/n is also presented, using the CALET proton flux recently updated with higher statistics.

PMID:37172251 | DOI:10.1103/PhysRevLett.130.171002