Search Results (85)

This paper presents the results of a comprehensive technological study of three bronze sculptures from the Jin Empire period (1115–1234 AD) from the collection of the Museum of Archaeology and Ethnography at the Institute of History, Archaeology and Ethnography of the Peoples of the Far East, Far Eastern Branch of the Russian Academy of Sciences (IHAE FEB RAS). Using photon-counting computed tomography (PCCT) and energy-dispersive X-ray spectroscopy (EDS), the production techniques were reconstructed, differences in alloy composition were identified, and specific features of the casting processes were determined. Tomographic analysis revealed two fundamentally different manufacturing approaches: a multi-stage technology involving the use of different alloys and the assembly of separately cast elements, and a single-cast technology with a homogeneous structure. Elemental analysis of the three sculptures using EDS demonstrated significant compositional variability—from 21% to 67% copper and from 9% to 69% tin in different parts of the objects—confirming the complexity of the technological processes. An expanded study of 20 bronze sculptures using portable X-ray fluorescence analysis (pXRF) allowed for the identification of four typological alloy groups: classic balanced lead–tin bronzes (Cu 30–58%, Sn 16–23%, Pb 16–28%), high-lead bronzes (Pb up to 52%), high-tin bronzes (Sn up to 30%), and low-tin alloys (Sn less than 11%). The morphological features of the sculptures suggest one of their possible interpretations as ancestor spirits used in ritual practices. The research findings contribute to the study of Jurchen metallurgical traditions and demonstrate the potential of interdisciplinary, non-destructive analytical methods for reconstructing the technological, social, and cultural aspects of medieval Far Eastern societies. Full article

Background/Objectives: The treatment of Hematogenous Primary Septic Spinal Infection (HPSSI) typically involves either conservative management or surgical intervention. Previous studies have suggested that conservative treatment with antibiotics is the mainstay conventional procedure in treating HPSSI, but relevant conclusions remain controversial regarding mortality, recurrence, and hospital stay. There is a lack of systematic reviews and meta-analyses comparing conservative vs. surgical treatment specifically in non-TBC, non-fungal, and non-postsurgical HPSSI in adults. This systematic review and meta-analysis aim to systematically evaluate the therapeutic effectiveness of conservative versus surgical intervention for the management of HPSSI, through a meta-analysis of key outcomes including mortality, recurrence, and length of hospital stay. Methods: A comprehensive literature search was performed across four major databases: PubMed, Cochrane, Science Direct, and Scopus. Using defined inclusion and exclusion criteria, we identified twelve studies encompassing 1199 patients with hematogenous, primary, septic spinal infection, which was not post-surgical, not due to TBC, and not fungal, who were treated conservatively (n = 519) or surgically (n = 680) for inclusion in the meta-analysis. PRISMA guidelines were used for this analysis. The primary outcome analyzed was mortality; secondary outcomes were infection recurrence and length of hospital stay, comparing conservative treatment versus operative intervention for HPSSI. Results: Mortality rates for surgical versus conservative treatment varied across five studies. Some studies reported significantly lower mortality with surgical intervention vs. conservative treatment (2.3–6% vs. 17.8–18%), while others showed no difference (11% for both treatments). This meta-analysis indicates that surgical treatment does not significantly alter mortality rates compared to conservative management, although study heterogeneity is considerable. Infection recurrence was reported in three studies, with rates ranging from 5 to 16.4% for conservative treatment and 5 to 11.6% for surgical intervention. These differences were not statistically significant in studies that provided group-specific data. Findings on hospital length of stay were mixed: two studies reported shorter stays for surgical patients (23.9–33.4 days vs. 40.5–51.2 days), while another study found no meaningful difference between the groups. Across multiple studies, advanced age, frailty, higher comorbidity burden, and neurological impairment were consistently identified as independent predictors of increased mortality, irrespective of treatment modality. Although some data suggest a short-term survival advantage associated with surgical intervention, the overall mortality outcomes remain heterogeneous across the literature. Conclusions: Overall, the findings of this meta-analysis remain inconclusive regarding which treatment—surgical or conservative—is more advantageous in reducing mortality, infection recurrence, and hospital stay. The variability across studies highlights the influence of patient selection, treatment protocols, and local clinical practices. To enhance our understanding and improve outcomes in HPSSI, future randomized controlled trials are essential. These studies should incorporate clear selection criteria, standardized terminology for spinal infection subgroups, and homogenous patient populations with well-defined comorbidities to allow for meaningful data comparisons. Additionally, emphasis should be placed on early diagnosis, rapid identification of causative pathogens, using modern diagnostic tools, and timely initiation of appropriate treatment—whether surgical or conservative—to optimize patient outcomes, including reduced mortality, lower recurrence rates, and shorter hospitalizations. Full article

Background/Objectives: High differentiation rates provided by Y-chromosomal short tandem repeats (Y-STRs) are highly advantageous in most forensic and genealogical casework, as they enhance the ability to exclude close or moderately related individuals, refine an individual’s position within a pedigree, and uncover the population substructure in otherwise homogeneous groups. However, the impact for historical remains identification casework is underexplored. Methods: We present a pedigree analysis of 366 males from 183 pedigrees, separated by 4 to 16 meioses at 27 Y-STR loci, from the Yfiler Plus kit. The differentiation rate for a given degree of separation was defined as the proportion of pairs at that specific number of meioses showing at least one allelic difference, relative to the total number of such pairs. Results: Our pedigree-based locus-specific mutation rates were consistent with published father–son values for 22 of 25 loci, with 3 loci (DYS389II, DYS449, and DYS570) being significantly different (p < 0.05). These results were consistent with previous pedigree-based estimates, and the strong agreement between father–son and pedigree-based mutation rates supports the use of pedigrees as a reliable method for estimating mutation rates. The probability of differentiating male relatives reached 60.1%, which is similar to previous studies using the Yfiler Plus kit. Conclusions: This high male differentiation rate is advantageous for distinguishing unrelated individuals within the same population, reducing false inclusions. However, when comparing distantly related individuals, excessive mutations accumulated over many generations may obscure genuine patrilineal relationships, increasing the risk of false exclusions. Our findings are likely to be highly valuable for future interpretation of Y-STR haplotypes from patrilineal relatives across a wide range of applications, with significant relevance to historical remains identification casework. Full article

The classification of urban residential settlements through Machine Learning (ML) and Deep Learning (DL) remains a complex task due to the intrinsic heterogeneity of urban environments and the scarcity of large, accurately labeled training datasets. To overcome these limitations, this study introduces a novel GIS-based unsupervised classification framework that exploits Fuzzy C-Means (FCM) clustering for the detection and interpretation of urban morphologies. Compared to unsupervised classification approaches that rely on crisp-based clustering algorithms, the proposed FCM-based method more effectively captures heterogeneous urban fabrics where no clear predominance of specific building types exists. Specifically, the method applies fuzzy clustering to census units—considered the fundamental scale of urban analysis—based on construction techniques and building periods. By grouping census areas with similar structural features, the framework provides a flexible, data-driven approach to the characterization of urban settlements. The identification of cluster centroids’ dominant attributes enables a systematic interpretation of the spatial distribution of the built environment, while the subsequent mapping process assigns each cluster a descriptive label reflecting the prevailing building fabric. The generated thematic maps yield critical insights into urban morphology and facilitate evidence-based planning. The framework was validated across ten Italian cities selected for their diverse physical, morphological, and historical characteristics; comparisons with the results of urban zone classifications in these cities conducted by experts show that the proposed method provides accurate results, as the similarity to the classifications made by experts, measured by the use of the Adjusted Rand Index, is always higher than or equal to 0.93; furthermore, it is robust when applied in heterogeneous urban settlements. These results confirm the effectiveness of the method in delineating homogeneous urban areas, thereby offering decision makers a robust instrument to guide targeted interventions on existing building stocks. The proposed framework advances the capacity to analyze urban form, to strategically support renovation and urban regeneration policies, and demonstrates a strong potential for portability, as it can be applied to other cities for urban scale analyses. Full article

Difference in Differences (DiD) is a useful statistical technique employed by researchers to estimate the effects of exogenous events on the outcome of some response variables in random samples of treated units (i.e., units exposed to the event) ideally drawn from an infinite population. The term “effect” should be understood as the discrepancy between the post-event realisation of the response and the hypothetical realisation of that same outcome for the same treated units in the absence of the event. This theoretical discrepancy is clearly unobservable. To circumvent the implicit missing variable problem, DiD methods utilise the realisations of the response variable observed in comparable random samples of untreated units. The latter are samples of units drawn from the same population, but they are not exposed to the event under investigation. They function as the control or comparison group and serve as proxies for the non-existent untreated realisations of the responses in treated units during post-treatment periods. In summary, the DiD model posits that, in the absence of intervention and under specific conditions, treated units would exhibit behaviours that are indistinguishable from those of control or untreated units during the post-treatment periods. For the purpose of estimation, the method employs a combination of before–after and treatment–control group comparisons. The event that affects the response variables is referred to as “treatment.” However, it could also be referred to as “causal factor” to emphasise that, in the DiD approach, the objective is not to estimate a mere statistical association among variables. This review introduces the DiD techniques for researchers in economics, public policy, health research, management, environmental analysis, and other fields. It commences with the rudimentary methods employed to estimate the so-called Average Treatment Effect upon Treated (ATET) in a two-period and two-group case and subsequently addresses numerous issues that arise in a multi-unit and multi-period context. A particular focus is placed on the statistical assumptions necessary for a precise delineation of the identification process of the cause–effect relationship in the multi-period case. These assumptions include the parallel trend hypothesis, the no-anticipation assumption, and the SUTVA assumption. In the multi-period case, both the homogeneous and heterogeneous scenarios are taken into consideration. The homogeneous scenario refers to the situation in which the treated units are initially treated in the same periods. In contrast, the heterogeneous scenario involves the treatment of treated units in different periods. A portion of the presentation will be allocated to the developments associated with the DiD techniques that can be employed in the context of data clustering or spatio-temporal dependence. The present review includes a concise exposition of some policy-oriented papers that incorporate applications of DiD. The areas of focus encompass income taxation, migration, regulation, and environmental management. Full article

Small noncoding RNAs are recognized as crucial regulators of seed germination, but their role in seed aging remains unclear. To address this, we performed RNA sequencing (RNA-seq) on barley (Hordeum vulgare L.) seeds with varying viability levels after long-term storage in hermetically sealed containers since the 1972 harvest. This globally unique material, characterized by genetic homogeneity and contrasting germination capacities, enabled an in-depth analysis of microtranscriptomic changes during germination. We identified 62 known miRNAs from 11 families and 234 novel miRNAs, with miR159, miR168, and miR166 showing consistently high expression across all germination stages and viability groups. Differential expression analysis revealed 28 miRNAs whose abundance varied significantly with seed viability and germination phase. Functional predictions supported by quantitative reverse transcription PCR (qRT–PCR) and degradome-based target identification indicated that these miRNAs regulate key developmental and metabolic pathways. Several isomiRs exhibited sample-specific expression, suggesting the viability-dependent activation of distinct molecular mechanisms. Gene Ontology analysis highlighted processes related to nucleic acid binding, nuclear organization, and cytoplasmic metabolism as central during germination. We propose that miRNA profiles may reflect an “epigenetic inheritance”—a molecular memory of aging stored in seeds—rather than solely a response to current conditions. This concept may help explain aging-related phenotypes such as delayed germination and reduced vigor, warranting further investigation. Full article

This study examines how educational attainment and creative-class identity influence public library use among Black homeowners in Ward 8, Washington, D.C., a historically disinvested, yet resilient, Black community. Using an adapted theoretical framework (Chatman’s Small World Theory, Florida’s creative class theory, and Crenshaw’s intersectionality), the research investigates how symbolic capital informs institutional engagement in a racially homogeneous but economically stratified setting. A survey of 56 Black homeowners examined the relationships among education, income, creative-class identity, and library use. Logistic regression analysis revealed that higher educational attainment was a significant predictor of identification with the Black Creative Class^TM. However, neither income nor creative-class identity significantly predicted public library use. These findings challenge the assumption that middle-class status or creative-class affiliation ensures participation in educational or cultural institutions. Instead, they suggest that deeper dynamics, such as cultural relevance, perceived alignment, and trust, may shape engagement with public libraries. The study advances knowledge in library and information science (LIS) and urban studies by demonstrating how spatial context and class distinctions within Black communities shape library engagement. The results underscore the need for culturally responsive library strategies that recognize class-based variation within racial groups, moving beyond monolithic models of community outreach. Full article

Biotechnological research increasingly focuses on developing new drugs to counter the rise of antibiotic-resistant strains in hospitals. This study aimed to create bacterial lysates from antibiotic-resistant pathogens isolated from patients and medical instruments across hospital departments. Identification was performed based on morphological, cultural, and biochemical characteristics, as well as 16S rRNA gene sequencing using the BLAST algorithm. Strain viability was assessed using the Miles and Misra method, while sensitivity to eight antibacterial drug groups and biosafety between cultures were evaluated using agar diffusion. From 15 clinical sources, 25 pure isolates were obtained, and their phenotypic and genotypic properties were studied. Carbohydrate fermentation testing confirmed that the isolates belonged to the genera Escherichia, Citrobacter, Klebsiella, Acinetobacter, Pseudomonas, Staphylococcus, Haemophilus, and Streptococcus. The cultures exhibited good viability (10⁹–10¹⁰ CFU/mL) and compatibility with each other. Based on prevalence and clinical significance, three predominant hospital pathogens (Klebsiella pneumoniae 12 BL, Pseudomonas aeruginosa 3 BL, and Acinetobacter baumannii 24 BL) were selected to develop a bacterial lysate consortium. Lysates were prepared with physical disruption using a French press homogenizer. The resulting product holds industrial value and may stimulate the immune system to combat respiratory pathogens prevalent in Kazakhstan’s healthcare settings. Full article

Cymbidium are endangered and ornamental orchids, and the taxonomy and species identification of this genus have been debated due to some overlapping morphological features between taxa and limited data being available. The leaf morpho-anatomy of 12 Cymbidium species from China was investigated using light microscopy and paraffin sectioning. Based on a comparative analysis, some leaf morphological features that varied between species were selected and used for taxonomic differentiation as follows: (1) The shape and structure of leaves were varied and could be used for species delimitation. (2) Microscopic characteristics show that the leaves lacked trichomes and displayed polygonal to rectangular epidermal cells on both surfaces, with larger adaxial cells and more abaxial stigmata. Stomata were mostly distributed only on the abaxial side, but on both sides in Cymbidium mastersii, which exhibited a rare amphistomatic type. The stomatal complex was uniformly tetracytic in 11 species, while it was observed to be anomocytic in C. floribundum. (3) Anatomically, two distinct midrib configurations were identified, a shallow V-shape and V-shape. The mesophyll cells were homogeneous in 10 species, with the exception of a layer of parenchyma cells resembling palisade cells occurring in C. lancifolium and C. qiubeiense. The thickness of the cuticle varied between species, with the adaxial surface covered by a thicker cuticle than the abaxial surface and displaying either a smooth or corrugated surface. A fiber bundle was observed in six species, but absent in the other six. In the former group, the fiber bundle occurred adjacent to both epidermal cells in C. mastersii and C. hookerianum, while it was adjacent to the abaxial epidermis in four other species. The stegmata, with conical, spherical silica bodies, were associated with fiber bundles and mesophyll in seven species, but absent in the other five (C. kanran, C. defoliatum, C. floribundum, C. lancifolium, and C. serratum). Three kinds of crystals were identified, namely the terete bundle, the long tube bundle, and the raphide. (4) It was suggested that some of these variable features could be selected and used for the delimitation of the species and taxonomy of Cymbidium. In addition, a key to the 12 Cymbidium species based on their leaf morpho-anatomic features was proposed, which could lead to a better understanding of the taxonomy and conservation of Orchidaceae. Full article

The main purpose of this study was to evaluate the morphological characteristics of a sample of young international elite basketball players to create new reference values, using both somatotype and Bioelectrical Impedance Vector Analysis (BIVA). Moreover, we analyze the influence of age and maturation on anthropometric characteristics. Anthropometric measures (stature, body mass, body circumferences, skinfold thicknesses, and diameters) have been collected in a sample of 153 young basketball players of different age categories. From these measures, the endo-, ecto-, and mesomorph somatotypes components were calculated. In addition, impedance measurements were performed with a hand-to-foot bioimpedance analyser, and, subsequently, BIVA was carried out and biological maturity was estimated. A principal component analysis (PCA) has been assessed to reduce somatotype dimensionality. Almost all the collected variables differed between age groups. As regards the somatotype, the majority of the athletes were mesomorph–ectomorphal and the degree of homogeneity of the sample was high; the somatotype is aligned with that of the older athletes. Strong relationships were observed between mesomorphy, age, and bio-electric phase angle. Moreover, a tolerance ellipse graph was proposed as a reference for young elite athletes in basketball, and a new PCA-based method with one component was created to synthesize somatotype contents (eigenvalue = 2.42, R² = 0.807). Reference values for basketball players are needed by researchers, coaches, and practitioners for the process of talent identification and development. There are too many biological features to easily account for during growth, and field personnel need synthetic and more reliable approaches. Full article

The growing demand for plant-based beverages has underscored the importance of investigating their volatile profiles, which play a crucial role in sensory perception and consumer acceptance. This is especially true for plant-based milks (PBMs) that have a clear reference model in bovine milk. This study characterises the volatile organic compounds (VOCs) in soy, almond and oat beverages compared to bovine milk using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) as a rapid and noninvasive screening tool, complemented by gas chromatography-mass spectrometry (GC-MS) for compound identification. A total of 188 mass peaks were detected by PTR-ToF-MS, all showing significant differences from the blank, while GC-MS allowed the identification of 50 compounds, supporting the tentative identifications performed with PTR-MS analysis. In order to facilitate a comparison of different milks, after statistical analysis, these 188 mass peaks were further categorised into two groups: one consisting of VOCs with minimal variability across all samples and another comprising VOCs with significantly different abundances, distinctly characterising each beverage. Principal component analysis revealed a clear separation between bovine milk and PBMs, with almond beverages exhibiting the richest volatilome, while oat beverages displayed a more homogeneous volatile profile. PTR-ToF-MS demonstrated its ability to analyse volatile profiles rapidly, with excellent complementarity to GC-MS in terms of analytical versatility. The results provided a valuable basis for testing new experimental designs aimed to characterise and enhance flavour profiles in plant-based beverages, also after processing, in case of new product development that considers using these milks as raw materials. Full article

The area postrema (AP) is a key circumventricular organ involved in the regulation of autonomic functions. Accurate identification of the AP via MRI is essential in neuroimaging but it is challenging. This study evaluated 3D FSE Cube T2WI, 3D FSE Cube FLAIR, and 3D DIR sequences to improve AP detection in patients with and without multiple sclerosis (MS). A case–control study included 35 patients with MS and 35 with other non-demyelinating central nervous system diseases (ND-CNSD). MRI images were acquired employing 3D DIR, 3D FSE Cube FLAIR, and 3D FSE Cube T2WI sequences. The evaluation of AP was conducted using a 3-point scale. Statistical analysis was performed with the chi-square test used to assess group homogeneity and differences between sequences. No significant differences were found in the visualization of the AP between the MS and ND-CNSD groups across the sequences or planes. The AP was not visible in 27.6% of the 3D FSE Cube T2WI sequences, while it was visualized in 99% of the 3D FSE Cube FLAIR sequences and 100% of the 3D DIR sequences. The 3D DIR sequence showed superior performance in identifying the AP. Full article

Background: Currently, there is a need for approaches to understand and manage the multidimensional autism spectrum and quantify its heterogeneity. The diagnosis is based on behaviors observed in two key dimensions, social communication and repetitive, restricted behaviors, alongside the identification of required support levels. However, it is now recognized that additional modifiers, such as language abilities, IQ, and comorbidities, are essential for a more comprehensive assessment of the complex clinical presentations and clinical trajectories in autistic individuals. Different approaches have been used to identify autism subgroups based on the genetic and clinical heterogeneity, recognizing the importance of autistic behaviors and the assessment of modifiers. While valuable, these methods are limited in their ability to evaluate a specific individual in relation to a normative reference sample of autistic individuals. A quantitative score based on axes of phenotypic variability could be useful to compare individuals, evaluate the homogeneity of subgroups, and follow trajectories of an individual or a specific group. Here we propose an approach by (i) combining measures of phenotype variability that contribute to clinical presentation and could impact different trajectories in autistic persons and (ii) using it with normative modeling to assess the clinical heterogeneity of a specific individual. Methods: Using phenotypic data available in a comprehensive reference sample, the Simons Simplex Collection (n = 2744 individuals), we performed principal component analysis (PCA) to find components of phenotypic variability. Features that contribute to clinical heterogeneity and could impact trajectories in autistic people were assessed by the Autism Diagnostic Interview-Revised (ADI-R), Vineland Adaptive Behavior Scales (VABS) and the Child Behavior Checklist (CBCL). Cognitive assessment was estimated by the Total Intelligence Quotient (IQ). Results: Three PCs embedded 72% of the normative sample variance. PCA-projected dimensions supported normative modeling where a multivariate normal distribution was used to calculate percentiles. A Multidimensional General Functionality Score (MGFS) to evaluate new prospective single subjects was developed based on percentiles. Conclusions: Our approach proposes a basis for comparing individuals, or one individual at two or more times and evaluating homogeneity in phenotypic clinical presentation and possibly guides research sample selection for clinical trials. Full article

The use of various mathematical and statistical methods for modelling economic processes and phenomena requires compliance with certain conditions/rules. To formulate general conclusions or predictions, in economic research, large databases are often used, related to more or less homogeneous samples, without taking into account the spatial or structural differences of the analysed processes or phenomena. Starting from the results of previous research focused on the identification and evaluation of difficulties in the business environment, the present study is based on the principles of mathematical induction, with the objective of testing these results, in order to assess whether the conclusions formulated are valid for a limited number of cases. Based on the primary data collected and tested (using Cronbach alpha, Meyer-Olkin Measure of Sampling Adequacy and Bartlett tests) it was shown that the difficulties selected for evaluation are present in the analysed business environment. Then, factor analysis was applied to identify the most important groups of factors, which bring together one or more difficulties specific to the analysed population. After the validation of the factorial model and after a preliminary test of the normality of the variables, the Mann-Whitney U test was applied to assess whether, at the level of independent groups (constructed on the basis of three dichotomous variables), the difficulties identified are common or show significant differences. Contrary to the results of previous studies, the present study indicates that the difficulties analysed affect more new businesses (recently established), which have fewer employees and are classified as micro-enterprises. Full article

Pesticides are playing a dominant role in modern cultivation practices to increase agricultural production but are also criticized for environmental depletion and soil and underground water degradation in field applications. An imperative need for greener pesticides has emerged in alignment with new innovations in agrarian and agricultural practices. This study provides a comprehensive review of marketable and banned pesticides that have been applied in past times or are still in use in agriculture. The collected literature production disclosed 35 distinct pesticides that were identified either isolated or in mixtures and residues. These pesticides are primarily applied in agricultural fields, but some of them were also criticized for human implications. Then, these 35 pesticides were grouped into four categories: insecticides (18), herbicides (9), fungicides (6), and acaricides (2). Furthermore, their molecular types, chemical structures, pKa or log Kow values were presented. Based on their chemical structure, the pesticides were also organized into two domains: “marketable simulated” and “banned simulated”, representing 43% and 57% of total pesticides, respectively. The simulations were generated by linking the elemental composition of each pesticide in the corresponding category; therefore, three “marketable simulated” (the acaricides were not marketable representative) and four “banned simulated” were demonstrated. In addition, the calculation of “adjustment factors” (−0.33 up to +0.50) and the “as calculated/marketable (or banned) simulated pesticides” ratios (0.946 up to 1.013) enabled the identification of four clusters of homogeneous characteristics: cluster 1: “Insecticides, Fungicides, marketable”, cluster 2: “Herbicides, marketable”, cluster 3: “Insecticides, Fungicides, banned”, and cluster 4: “Acaricides, Herbicides, banned”. Subsequently, the composition of the elements of C and H enabled the crystallography characterization of only the “marketable” pesticides, not those that are “banned”, with compounds that have been already registered in the “Crystallography Open Database”. Conclusively, implications, challenges, and future research recommendations have been proposed. Full article