Frequency Patterns Research Articles

The elemental intelligence of the cosmos and the scale invariance of universal consciousness: role of AI in the fate of our universe

Elemental intelligence is a metaphysical concept. We propose that elemental intelligence is an intrinsic part of the fabric of the universe. It suggests that everything in existence might have a sort of proto-consciousness, with larger and more complex systems like living beings having more developed or differentiated forms of awareness. Additionally, we identify the challenges of how AI interacts with this universal consciousness in our universe. In this article, an analysis is carried out on the basic mechanisms inherent in the functioning of the living and conscious universe that seems permeated by an elemental intelligence, the latter seen as a metaphysical concept. We substantiate this framework and submit that primordial proton/electron composite units, covered with multiple phonons (forming quasi-particles), exhibit attractive and repulsive charge interactions or generate chiral vortex dynamics, thereby generating the forces of gravity and anti-gravity (dark energy). Density fluctuation of phonons is preferred over photon oscillations, assuming dense super-fluid space conditions. The frequency pattern of an “Acoustic Quantum Code of Resonant Coherence” is detected in a multi-scale spectrum, including cosmic gravitational waves at the macro-scale, in measured oscillations of Zero-point Energy field, as well as in Electro-Magnetic frequencies (EMF) that promote entanglement and superconductivity. With regard to brain function, an almost perfect frequency fit of our acoustic code was revealed for brain microtubule oscillations and blackbody radiation at the Planck scale, numerically supporting the Orch-OR consciousness theory. The present results also confirm the Creation Field model for Life, proposed by others and framed as a “General Music Code”. The acoustic quantum code is conceived as primordial, with its scale-invariant correlation of (renormalized) EMF wave frequencies at the Planck scale, at the Zero-point Energy field-, Cosmic Microwave Background-, and Gravitational levels. A 4th spatial dimension is required in this context, with time constituting a 5-D universe space-time. So, an intrinsic elementary intelligence of the cosmos is revealed that, in superposition with human-created artificial intelligence, is considered in the nexus of our Universe, offering both potential and inherent challenges. Although present and future AI may allow a major acceleration of human scientific endeavors, AI-generated products require stringent top-down and bottom-up quality surveillance through a protective “immune system” for the Internet. A reconstructive universe is proposed in which elemental intelligence functions as a ”recipe” (a set of rules) that also may enable the rebirth of our universe in a time-reversed mode. The Acoustic code script was also shown to have been instrumental in biological evolution and the creation of first life. Thus, a dedicated information field of harmonic acoustics guides the past and ongoing fabric of reality. The present concept provides a novel basis for the further study of macro- and micro-structures in the cosmos and reveals the crucial role of a growing universal consciousness, as supported by human observation and participation.

Framing Child Abuse: Analyzing Media Coverage of CSA in Lahore's Newspapers (2020-2023)

Media coverage significantly influences public understanding and policy responses to child abuse. This study examines the portrayal of child abuse, particularly child sexual abuse (CSA), in Lahore’s newspapers from 2020 to 2023. Findings reveal distinct patterns in coverage frequency, framing, and narrative presentation across English and Urdu newspapers. The analysis highlights issues such as sensationalism, lack of sensitivity, and politicization. Despite these challenges, media coverage remains essential for raising awareness and fostering societal dialogue on child protection. The study emphasizes the need for ethical reporting practices, improved journalist training, and stronger collaboration between media, government, and civil society to effectively address child abuse.

Source attribution of human Campylobacter infection: a multi-country model in the European Union

IntroductionInfections caused by Campylobacter spp. represent a severe threat to public health worldwide. National action plans have included source attribution studies as a way to quantify the contribution of specific sources and understand the dynamic of transmission of foodborne pathogens like Salmonella and Campylobacter. Such information is crucial for implementing targeted intervention. The aim of this study was to predict the sources of human campylobacteriosis cases across multiple countries using available whole-genome sequencing (WGS) data and explore the impact of data availability and sample size distribution in a multi-country source attribution model.MethodsWe constructed a machine-learning model using k-mer frequency patterns as input data to predict human campylobacteriosis cases per source. We then constructed a multi-country model based on data from all countries. Results using different sampling strategies were compared to assess the impact of unbalanced datasets on the prediction of the cases.ResultsThe results showed that the variety of sources sampled and the quantity of samples from each source impacted the performance of the model. Most cases were attributed to broilers or cattle for the individual and multi-country models. The proportion of cases that could be attributed with 70% probability to a source decreased when using the down-sampled data set (535 vs. 273 of 2627 cases). The baseline model showed a higher sensitivity compared to the down-sampled model, where samples per source were more evenly distributed. The proportion of cases attributed to non-domestic source was higher but varied depending on the sampling strategy. Both models showed that most cases could be attributed to domestic sources in each country (baseline: 248/273 cases, 91%; down-sampled: 361/535 cases, 67%;).DiscussionThe sample sizes per source and the variety of sources included in the model influence the accuracy of the model and consequently the uncertainty of the predicted estimates. The attribution estimates for sources with a high number of samples available tend to be overestimated, whereas the estimates for source with only a few samples tend to be underestimated. Reccomendations for future sampling strategies include to aim for a more balanced sample distribution to improve the overall accuracy and utility of source attribution efforts.

Seasonal spatial-temporal trends of vegetation recovery in burned areas across Africa.

Africa is entering a new fire paradigm, with climate change and increasing anthropogenic pressure shifting the patterns of frequency and severity. Thus, it is crucial to use available information and technologies to understand vegetation dynamics during the post-fire recovery processes. The main objective of this study was to evaluate the seasonal spatio-temporal trends of vegetation recovery in response to fires across Africa, from 2001 to 2020. Non-parametric tests were used to analyze MODIS Normalized Difference Vegetation Index (NDVI) products comparing the following three-month seasonal periods: December-February (DJF), March-May (MAM), June-August (JJA), and September-November (SON). We evaluated the seasonal spatial trends of NDVI in burned areas by hemisphere, territory, or country, and by land cover types, and fire recurrences, with a focus on forested areas. The relationships between the seasonal spatial trend and three climatic variables (i.e. maximum air temperature, precipitation, and vapor pressure deficit) were then analyzed. For the 8.7 million km2 burned in Africa over the past 22 years, we observed several seasonal spatial trends of NDVI. The highest proportions of areas with increasing trend (p < 0.05) was recorded in MAM for both hemispheres, with 22.0% in the Northern Hemisphere and 17.4% in the Southern Hemisphere. In contrast, areas with decreasing trends (p < 0.05), showed 4.8-5.5% of burned area in the Northern Hemisphere, peaking in JJA, while the Southern Hemisphere showed a range of 7.1 to 10.9% with the highest proportion also in JJA. Regarding land cover types, 48.0% of fires occurred in forests, 24.1% in shrublands, 16.6% in agricultural fields, and 8.9% in grasslands/savannas. Consistent with the overall trend, the area exhibiting an increasing trend in NDVI values (p < 0.05) within forested regions had the highest proportion in MAM, with 19.9% in the Northern Hemisphere and 20.6% in the Southern Hemisphere. Conversely, the largest decreasing trend (p < 0.05) was observed in DJF in the Northern Hemisphere (2.7-2.9%) and in JJA in the Southern Hemisphere (7.2-10.4%). Seasonally, we found a high variability of regeneration trends of forested areas based on fire recurrences. In addition, we found that of the three climatic variables, increasing vapor pressure deficit values were more related to decreasing NDVI levels. These results indicate a strong component of seasonality with respect to fires, trends of vegetation increase or decrease in the different vegetation covers of the African continent, and they contribute to the understanding of climatic conditions that contribute to vegetation recovery. This information is helpful for researchers and decision makers to act on specific sites during restoration processes.

Online Payment Fraud Detection Model Using Machine Learning

The dependability and safety of UPI-based financial transactions are vital for maintaining public confidence, facilitating seamless digital payments, and ensuring economic stability. This paper introduces a software model aimed at identifying and predicting fraudulent behavior in UPI transactions through the use of advanced technologies, which encompass machine learning algorithms, real-time monitoring, and behavioral analysis. The Use of the software is to reduce financial risks by implementing a fraud assessment system that relies on historical transaction data and current information. By utilizing machine learning algorithms along with rule-based methods, the system is able to recognize abnormal transaction patterns, evaluate user behavior, and identify irregularities. The Prediction of model find the risk of transactions based on factors such as the amount, frequency, location, and behavioral patterns of users to highlight potentially suspicious activities. The suggested system functions by implementing four main phases: user engagement, analysis of historical data, continuous monitoring of real-time data, and fraud prediction analysis. This methodology produces comprehensive reports on the risks associated with transactions and offers proactive measures to identify and thwart fraudulent actions within UPI transactions Key Words UPI Transactions, Fraud Detection, Machine Learning, Real-Time Monitoring, Behavioral Analysis, Risk Assessment,

Leveraging Cannabis-Centric Reddit Communities to Explore Patterns of Cannabis Product, Modes and Frequency of Use Between 2010-2019

Leveraging Cannabis-Centric Reddit Communities to Explore Patterns of Cannabis Product, Modes and Frequency of Use Between 2010-2019

P-1031. Frequency and resistance patterns of Candida auris causing candidemia in 3 teaching hospitals in Illinois: a routine data analysis

Abstract Background Despite a reported increase in the prevalence of Candida auris in the US, a potential emergent multidrug-resistant health care associated pathogen, data on its prevalence and drug resistance patterns is still scarce. Methods Sub-analysis or routinely collected data from 3 teaching hospitals in Chicago, Illinois. Isolates from patients with positive blood cultures for any species of Candida between April 2022 and April 2024 were included. The percentage of samples positive for Candida auris, considering one isolate per patient, and the prevalence or resistance to several antifungals (echinocandins, azoles, and amphotericin B) was reported. Results Among 422 candidemia isolates, 210 (49.8%) were Candida auris, isolated from 64 patients: 23 (36.5%), 34 (54.0%) and 6 (9.5%) from 2022, 2023 and 2024 respectively. Four isolates (6%) were resistant to echinocandins, nine (14%) isolates were resistant to fluconazole and one (2%) was resistant to amphotericin B. Conclusion A large proportion of candidemia isolates were caused by Candida auris. An important percentage was resistant to fluconazole and to echinocandins, supporting amphotericin B or high dose echinocandins as first line therapy. Disclosures All Authors: No reported disclosures

Declining precipitation frequency may drive earlier leaf senescence by intensifying drought stress and enhancing drought acclimation

Precipitation is an important factor influencing the date of foliar senescence, which in turn affects carbon uptake of terrestrial ecosystems. However, the temporal patterns of precipitation frequency and its impact on foliar senescence date remain largely unknown. Using both long-term carbon flux data and satellite observations across the Northern Hemisphere, we show that, after excluding impacts from of temperature, radiation and total precipitation by partial correlation analysis, declining precipitation frequency may drive earlier foliar senescence date from 1982 to 2022. A decrease in precipitation frequency intensifies drought stress by reducing root-zone soil moisture and increasing atmospheric dryness, and limit the photosynthesis necessary for sustained growth. The enhanced drought acclimation, showing a more rapid response to drought, also explains the positive relationship between precipitation frequency and foliar senescence date. Finally, we find 30 current state-of-art Earth system models largely fail to capture the sensitivity of DFS to changes in precipitation frequency and incorrectly predict the direction of correlations for approximately half of the northern global lands, in both historical simulations and future predictions. Our results therefore highlight the critical need to include precipitation frequency, rather than just total precipitation, into models to accurately forecast plant phenology under future climate change.

Amelioration in Indonesian Classics: A Corpus Analysis of Concrete Nouns in Indonesian Literary Works

This research analyzes the phenomenon of amelioration on concrete nouns in the novels Layar Terkembang by Sutan Takdir Alisjahbana and Sitti Nurbaya by Marah Roesli. Amelioration is the process of changing the meaning of a word that leads to a more positive connotation. The purpose of this study is to identify the forms of amelioration, the positive connotations formed, and how these changes in meaning reflect the social and cultural context of colonial Indonesia. The research method used is corpus linguistics with documentation techniques through the KORTARA (Korpus Nusantara) application to identify frequency patterns and word collocation in literary texts. The results showed that there were 57 words undergoing amelioration that reflected changes in social views, culture, and religious values. For example, the word "khalikulalam" in Sitti Nurbaya's novel has undergone improvements, a shift in meaning that increases its value and respect; The word "virgin" in the novel Layar Terkembang carries a more subtle and respectful connotation, describing a young woman who is seen not only by her status but also associated with beauty, purity. The words not only have basic meanings, but also additional connotations that symbolize respect, sanctity, spiritual power, and cultural pride. The amelioration of these concrete nouns shows the changes in colonial society's perspective towards social roles and cultural values in daily life. The findings support the theory that amelioration is closely related to broader social dynamics, where words with high moral and cultural values tend to experience an increase in meaning. This research is expected to contribute to the study of Indonesian linguistics and semantic education, as well as add to the understanding of the interaction between language and social values in society.

The System for Classification of Low‐Pressure Systems (SyCLoPS): An All‐In‐One Objective Framework for Large‐Scale Data Sets

AbstractWe propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low‐pressure systems (LPSs) in a given data set. We use the state‐of‐the‐art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high‐impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high‐altitude and drier LPSs, differentiating tropical and non‐tropical LPSs using novel criteria, and optimizing for the detection of the four types of high‐impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high‐impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

Clinical Profile and Antibiotic Susceptibility Patterns of Cronobacter sakazakii in the Northern Region of Oman

Abstract Background: Cronobacter sakazakii is an opportunistic pathogen that mostly affects neonates, infants, and elderly people with weakened immune systems. No study has reported the frequency and antibiotic susceptibility patterns of C. sakazakii from Oman, and thus this study was conducted to fill this gap in the literature. Materials and Methods: This single-center retrospective study included C. sakazakii isolates identified from different clinical samples of patients treated at Sohar Hospital, Oman, between January 2017 and December 2023. Bacterial identification and antibiotic susceptibility testing were done using the VITEK II automated microbiological system in accordance with the Clinical Laboratory Standards Institute (CLSI) guidelines. Results: A total of 185 C. sakazakii isolates were included, most commonly from patients aged &gt;60 years (42.7%) and &lt;1 year (11.4%). C. sakazakii strains had high susceptibility (&gt;80%) to most of the tested antibiotics; however, for beta-lactam antibiotics, it ranged from 0% to 50%. Approximately 26.5% of the strains were multidrug resistant. Independent risk factors for increased frequency of multidrug-resistant strains were urinary catheterization (P = 0.002), surgery (P = 0.021), previous antibiotic therapy (P = 0.047), and critical care unit admission (P = 0.048). About one-fifth of the patients experienced life-threatening C. sakazakii infections such as septicemia (15%) and pneumonia (4.7%). All deaths due to septicemia occurred in the &gt;60 years (n = 12) and &lt;1 year (n = 4) age groups. Conclusions: Cronobacter sakazakii isolates from the North Batinah region of Oman were most frequently isolated from elderly and infant patients and had high antibiotic susceptibility; however, the significant resistance against beta-lactams suggests their low effectiveness. The high number of multidrug-resistant strains coupled with the independent risk factors suggests the need for following stricter antibiotic stewardship protocols and infection control practices.

KIC 4150611: A quadruply eclipsing heptuple star system with a g-mode period-spacing pattern

Context. KIC 4150611 is a high-order (seventh-order) multiple composed of a triple system with: a F1V primary (Aa), which is eclipsed on a 94.2 d period by a tight binary composed of two K/M dwarfs (Ab1 and Ab2) that also eclipse each other; an eccentric, eclipsing binary composed of two G stars (Ba and Bb); and another faint eclipsing binary composed of two stars of unknown spectral type (Ca and Cb). In addition to its many eclipses, the system is an triple-lined spectroscopic multiple (Aa, Ba, and Bb) and the primary (Aa) is a hybrid pulsator that exhibits high amplitude pressure and gravity modes (g-modes). Furthermore, its g-modes are arrayed in a period-spacing pattern, which greatly assists with mode identification and asteroseismic modelling. In aggregate, this richness in physics offers an excellent opportunity to obtain a precise physical characterisation for some of the stars in this system. Aims. In this work we estimate the stellar parameters of the primary (Aa) by performing asteroseismic analysis on its period-spacing pattern. Methods. We used the C-3PO neural network to perform asteroseismic modelling of the g-mode period-spacing pattern of Aa, examining the interplay of this information with external constraints from spectroscopy (Teff and log(g)) and eclipse modelling (R). To estimate the level of uncertainty due to different frequency extraction and pattern identification processes, we considered four different variations of the period-spacing patterns. To better understand the correlations between and the uncertainty structure of our parameter estimates, we also employed a classical, parameter-based Markov chain Monte Carlo (MCMC) grid search on four different stellar grids. Results. The externally constrained model that best fits the period-spacing pattern arrives at estimates of the stellar properties for Aa of M = 1.51 ± 0.05 M⊙, Xc = 0.43 ± 0.04, R = 1.66 ± 0.1 R⊙, fov = 0.010, Ωc = 1.58 ± 0.01 d−1 with rigid rotation to within the measurement errors, log(Teff) = 3.856 ± 0.008 dex, log(g) = 4.18 ± 0.04 dex, and log(L) = 0.809 ± 0.005 dex, which agree well with previous measurements from eclipse modelling, spectroscopy, and the Gaia DR3 luminosity. Conclusions. We find that the near-core properties of the best-fitting asteroseismic models are consistent with external constraints from eclipse modelling and spectroscopy. For stellar properties not related to the near-core region, external constraints on the asteroseismic best-fitting models are informative. Aa appears to be a typical example of a γ Dor star, fitting well within existing populations. We find that Aa is quasi-rigidly rotating to within the uncertainties, and note that the asteroseismic age estimate for Aa (1100 ± 100 Myr) is considerably older than the young age (35 Myr) implied by previous isochrone fits to the B binary in the literature. Our MCMC parameter-based grid search agrees well with our pattern-modelling approach. Improved future modelling could come from detailed coverage of metallicity effects and a careful treatment of envelope physics.

Exploring Contact Distance Distributions with Google Colaboratory.

Hi-C and Micro-C are the three-dimensional (3D) genome assays that use high-throughput sequencing. In the analysis, the sequenced paired-end reads are mapped to a reference genome to generate a two-dimensional contact matrix for identifying topologically associating domains (TADs), chromatin loops, and chromosomal compartments. On the other hand, the distance distribution of the paired-end mapped reads also provides insight into the 3D genome structure by highlighting global contact frequency patterns at distances indicative of loops, TADs, and compartments. This chapter presents a basic workflow for visualizing and analyzing contact distance distributions from Hi-C data. The workflow can be run on Google Colaboratory, which provides a ready-to-use Python environment accessible through a web browser. The notebook that demonstrates the workflow is available in the GitHub repository at https://github.com/rnakato/Springer_contact_distance_plot.

Evaluation of Articulatory Dynamics in Palatalized Articulation Using Electropalatography and Analysis of Factors in Its Occurrence

ABSTRACTAimWe aimed to visually evaluate the place of articulation of palatalized articulation (PA) using electropalatography (EPG) and to analyze the involvement of fistula and velopharyngeal function (VPF) as factors in the occurrence of PA.MethodsTen patients with postoperative cleft palate and auditory PA were included. The test sounds were three alveolar sounds, [t], [d], and [s], with [a] inserted before each consonant and [a], [e], and [o] inserted afterward. The test sounds were consecutively recorded five times using the EPG, and a cumulative frequency pattern was created by accumulating the maximum contact frames at the time of each consonant production to visually determine the PA. The place of articulation in the cumulative frequency pattern was subsequently evaluated in detail. The relationship between the place of articulation and fistula and VPF was statistically analyzed.ResultsAll 10 patients had PA for any of the tested sounds. The place of articulation was divided into three patterns: anterior, middle, and posterior. The relationship between the place of articulation and the fistula for PA showed a significant difference between the groups with and without a fistula (U = 0, p = 0.0167, p &lt; 0.05). The relationship with VPF showed no statistically significant differences.ConclusionUsing EPG to visually evaluate the place of articulation of the PA, we could divide it into three positions. Furthermore, there was an association between the place of articulation and fistula, suggesting that the place of articulation is more posterior in the presence of a fistula.

Enhanced Detection of Diffusion Model-Generated Deepfakes Using CNN Feature Maps and Forgery Traces

Recent advancements in generative artificial intelligence powered by deep learning have significantly improved image generation and manipulation, resulting in highly realistic images that pose substantial risks to multimedia security. The increasing similarity between authentic and deepfake images, especially those generated by Diffusion Models, highlights the pressing need for effective detection mechanisms. This study provides a comprehensive evaluation of counterfeit facial image detection, focusing on the generalizability and robustness of various detection methods. Using a dataset comprising real images from CelebA-HQ and synthetic images generated by five state-of-the-art models (StyleGAN2, VQGAN, DDPM, PNDM, and LDM), we benchmark four leading detection algorithms: Wang2020, Grag2021, Mandelli2022, and Ojha2023. The performance of these detectors was evaluated across different generative models and under various image perturbations, such as resizing, noise, blur, and compression. Additionally, we analyzed frequency-domain artifacts, revealing that GAN-generated images exhibit distinct frequency patterns, whereas DM-generated images closely resemble authentic ones. A novel hybrid approach combining spatial and frequency-domain features was proposed, yielding superior performance in detecting AI-generated human faces. Among the methods tested, Mandelli2022 achieved an AUC of 98.38%, while our ResNet-50+FFT model outperformed it slightly with an AUC of 98.42%. These results highlight the effectiveness of hybrid approaches in improving detection accuracy. However, detectors still face challenges in generalizing to diverse datasets, emphasizing the need for more adaptable and robust detection strategies.

Auditory temporal order and speech perception in late talkers

Abstract Background Auditory temporal processing skills to perceive rapid changes in intensity, duration, and frequency of sounds over time are essential for early spoken language acquisition and speech perception. This study aimed to assess auditory temporal order and speech perception in late talkers. Methods Fifty children (25 with late-talking and 25 with typical development) aged 7 to 9 years were included in the study. All subjects had typical audiometric thresholds between 125 Hz and 8 kHz (≤ 20 dB HL) and no middle ear pathology. The frequency pattern test, duration pattern test, and speech intelligibility tests in quiet and noise conditions were used to assess auditory temporal order and speech perception. Results Late talkers performed lower than typically developing children on tests of frequency pattern, duration pattern, and speech intelligibility in noise (p &lt; 0.05). When the correlations between the tests used were calculated, there were correlations between the tests for both groups. Conclusions The results indicate that children who talk later than their typically developing peers in the early years of life may have difficulties with some auditory processing skills, even if they catch up with their typically developing peers in speech and language skills in middle childhood. Thus, it is very crucial to monitor auditory processing skills as well as speech and language skills in late talkers.

Frequency, demographics, diagnoses and consultation patterns associated with low-acuity attendances in German emergency departments: a retrospective routine healthcare data analysis from the INDEED project

ObjectiveEvidence suggests interventions targeting low-acuity attendances have been hampered by insufficient characterisation of potential target groups. This study aimed to estimate the frequency of low-acuity emergency department (ED) attendances and...

Дискурсивные маркеры имиджеобразующей деятельности российских губернаторов в социальных медиа

The article analyzes discursive markers used by Russian governors to shape their digital image in social media. The authors examine how political leaders use social media to construct public opinion, enhance trust, and manage their image in the context of modern digital challenges. The study covers the content of Telegram channels of eight governors representing regions with a medium response level for June 2023. The authors highlight key discursive topics (patriotism, socio-economic aspects, interaction with citizens), analyze their frequency and usage patterns. The data obtained demonstrate significant differences in governors’ strategies. Some focus on youth policy and social stability, while others focus on the regions’ economic achievements or maintaining patriotic sentiment. At the same time, the importance of social responsibility, transparency, and interaction with the population in the digital environment is emphasized.

Exploring the Correlations Between Language Impairments, Central Auditory Processing Disorder, Neuropsychiatric Functions, and Seizure Timing in Children With Self-Limited Epilepsy With Centrotemporal Spikes.

Children with self-limited epilepsy with centrotemporal spikes often face language impairments and central auditory processing difficulties. The correlations between these issues, seizure timing, and neuropsychiatric challenges are not fully understood. This study delves into the connections between language impairments and central auditory processing difficulties in cases with self-limited epilepsy with centrotemporal spikes, examining their links with seizure occurrence and neuropsychiatric function. Patients with self-limited epilepsy with centrotemporal spikes were categorized based on seizure timing: group 1 experienced seizures postbedtime, and group 2 prewaking. Both, alongside controls, underwent the Turkish Expressive and Receptive Language Test (TIFALDI) for language skills, and the Frequency Pattern and Duration Pattern tests for central auditory processing difficulties. Neuropsychiatric assessments involved the Wechsler Intelligence Scale for Children-Revised, the Strengths and Difficulties Questionnaire, the Conners Parent Rating Scale-Revised Short, and the Barratt Impulsiveness Scale-11. The study comprised 56 patients with self-limited epilepsy with centrotemporal spikes (ages 6-13) and 32 healthy controls. Both groups significantly lagged behind controls on the Frequency Pattern and Duration Pattern tests (P < .001). In the TIFALDI, the expressive language scores varied between group 1 and controls (P = .04) but not the receptive language scores or the test's expressive and receptive language results between group 2 and controls (P > .05). In the Strengths and Difficulties Questionnaire, group 1 diverged from controls in behavioral and kind and helpful behavior scores (P = .016 and P = .012). Group 1's Barratt Impulsiveness Scale-11 values surpassed controls' (P = .038). Children with self-limited epilepsy with centrotemporal spikes have a high central auditory processing difficulties prevalence, regardless of seizure timing. Those with postsleep seizures tend to confront expressive language difficulties, alongside issues in prosocial behavior and impulsivity.

What Drives Herbal Traditions? The Influence of Ecology and Cultural Exchanges on Wild Plant Teas in the Balkan Mountains

This study investigates the ethnobotanical diversity of wild plant teas across various populations in the Balkan mountain regions, focusing on cultural and ecological influences. Data were collected through ethnobotanical field surveys conducted in thirteen distinct areas, encompassing approximately 900 interviews with local populations, including Albanians, Bosniaks, North Macedonians, Goranis, and Serbs. The study identifies 143 genera used in traditional teas, with species frequency and distribution patterns analysed concerning elevation and cultural factors. Statistical analyses using Principal Component Analysis (PCA) and Cluster Analysis revealed clear grouping patterns between populations based on ecological zones. The results show a clear correlation between altitude and the herbal use of plant genera, with higher elevations (above 700 m) supporting a greater variety of local species. Cultural practices, such as tea consumption during communal gatherings, also significantly shaped the selection of plants across different populations. For instance, Sideritis species were most prevalent among Albanian and North Macedonian communities, while Thymus and Mentha species were widely used across all groups. Moreover, cultural exchanges can explain the similarity of wild teas reported by Bosniaks (in Bosnia) and North Albanians, located far away from each other but showing similar traits due to possible common origins or the effect of centuries of pastoralism, which may have generated a constant exchange of local plant practices. The study concludes that ecological conditions and cultural exchanges significantly influence the choice, use, and resilience of wild plant herbal traditions in the Balkans. However, modern pressures such as urbanisation and market-driven consumption are increasingly threatening these practices. This highlights the need for conservation strategies that integrate ecological preservation and cultural heritage safeguarding.