Background: The AWaRe tool was set up by the World Health Organization (WHO) to promote the rational use of antimicrobials. Indeed, this tool classifies antibiotics into four groups, Access, Watch, Reserve and not-recommended antibiotics. In Republic Democratic of Congo, data on antibiotic dispensing (prescribing) by health professionals according to the AWaRe classification are scarce. In this research work, we aimed to explore antibiotic dispensing pattern from health professionals according to the WHO AWaRe classification to strengthen the national antimicrobial resistance plan. Methods: For this purpose, a survey was conducted from July to December 2022 in the district of Tshangu in Kinshasa. From randomly selected drugstores, drug-sellers were interviewed and randomly selected customers attending those drugstores were included in the study for medical prescriptions collection. The prescribed antibiotics were classified into the Access, Watch, Reserve and not recommended antibiotics group and by antibiotics number by prescription among pharmacies surveyed. Results: Of 400 medical prescriptions collected, 301 (75.25%) contained antibiotics. Of 301 prescriptions containing antibiotics, 164 (164/301; 54.5%) contained one antibiotic, 117 (117/301; 38.9%) two antibiotics, 15 (15/301; 5%) three antibiotics and 5 (5/301; 1.6%) 4 antibiotics. Out of the total of 463 antibiotics prescribed, 169 (169/463; 36.5%) were from the Access group, 200 (200/463; 43.2%) from the Watch group and 94 (94/463; 20.3%) from not recommended antibiotics group, respectively. Based on the anatomical, therapeutic and chemical (ATC) classification, it can be seen that third generation cephalosporins contained 34.33% of the prescribed antibiotics, followed by penicillins 17.17%, macrolides 7.63%, aminoglycosides 7. 36% and Imidazoles 7.36%, thus accounting approximately for 74% of the classes of antibiotics prescribed. Of the 463 antibiotics prescribed, the most frequently prescribed antibiotics were Ceftriaxone (21.38%), Amoxicillin (11.01%), Gentamycin (5.61%), Amoxicillin-clavulanic acid (5 .61%), Azithromycin (4.97%) and Metronidazole (4.75%), thus accounting for approximately 54% of all antibiotics prescribed. Conclusion: These results highlight the importance of strict implementation of the national plan to combat antimicrobial resistance and the need to train health workers in the correct application of the WHO AWaRe classification.

Many studies have focused on the impacts of rainfall duration and intensity while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and intensive tillage erosion on surface runoff and soil loss on sloping farmland in the purple-soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising-falling, and falling-rising) with the same total precipitation were designed, and the intensive tillage erosion treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrodynamic characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy-Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and soil loss were found among different rainfall patterns and stages (P < 0.05). The falling pattern and falling-rising pattern had faster runoff-initiating times and larger sediment yields than those of the other rainfall patterns. f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34%–16.21% among different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% on surface runoff and 10.14%–78.95% on soil loss on sloping farmland. Surface runoff and soil loss were positively correlated with rainfall intensity, V, and Fr but negatively correlated with f irrespective of tillage intensive (P < 0.05). For varying-intensity rainfall patterns, soil and water loss fluctuated during rainfall events, suggesting that the changes in rainfall intensity and tillage intensity would result in drastic variations in soil hydrological characteristics and sediment transport mechanisms. The time sequences of rainfall intensity in each rainfall pattern significantly affected surface runoff, soil erosion, and their contribution rates to total soil and water loss. Moreover, tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage-water erosion prediction models to evaluate soil and water loss on cultivated hillslopes.

Alfalfa (Medicago sativa L.) is the most cultivated forage legume around the world. Under a variety of growing conditions, forage yield in alfalfa is stymied by biotic and abiotic stresses including heat, salt, drought, and disease. Given the sessile nature of plants, they use strategies such as differential gene expression to respond to environmental cues. Transcription factors control the expression of genes that contribute to or enable tolerance and survival during periods of stress. Basic-leucine zipper (bZIP) transcription factors have been demonstrated to play a critical role in regulating plant growth and development as well as mediate the responses to abiotic stress in several species, including Arabidopsis thaliana, Oryza sativa, Lotus japonicus, and Medicago truncatula. However, there is little information about bZIP transcription factors in cultivated alfalfa. In the present study, 237 bZIP genes were identified in alfalfa from publicly available sequencing data. Multiple sequence alignments showed the presence of intact bZIP motifs in the identified sequences. Based on previous phylogenetic analyses in Arabidopsis thaliana, alfalfa bZIPs were similarly divided and fell into 10 groups. The physicochemical properties, motif analysis, and phylogenetic study of the alfalfa bZIPs revealed high specificity within groups. The differential expression of alfalfa bZIPs in a suite of tissues indicates that particular bZIP genes are specifically expressed at different developmental stages in alfalfa. Similarly, expression analysis in response to ABA, cold, drought, and salt stresses, indicates that a subset of bZIP genes are also differentially expressed and likely play a role in abiotic stress signaling and/or tolerance. These expression patterns were further verified by qRT-PCR. However, further functional characterization of bZIP transcription factors in alfalfa will help illuminate the role they play in stress tolerance mechanisms in legumes and facilitate the molecular breeding of stress tolerance in alfalfa.

Josephson junctions (JJs) in the presence of a magnetic field exhibit qualitatively different interference patterns depending on the spatial distribution of the supercurrent through the junction. In JJs based on two-dimensional topological insulators (2DTIs), the electrons/holes forming a Cooper pair (CP) can either propagate along the same edge or be split into the two edges. The former leads to a SQUID-like interference pattern, with the superconducting flux quantum $\phi_0$ (where $\phi_0=h/2e$) as a fundamental period. If CPs’ splitting is additionally included, the resultant periodicity doubles. Since the edge states are typically considered as being strongly localized, the critical current does not decay as a function of the magnetic field. Here we go beyond this approach and inspect a topological JJ in the tunneling regime featuring extended edge states. We consider the possibility that the two electrons of a CP propagate and explore the junction independently over length scales comparable with the superconducting coherence length. As a consequence of the spatial extension, we obtain a decaying pattern with different possible periods. In particular, we show that, if crossed Andreev reflections (CARs) are dominant and the edge states overlap, the resulting interference pattern features oscillations whose periodicity approaches $2\phi_0$.

The emerging advancements in separation and classification of various biological matters (e.g., living cells and proteins) using magnetic levitation (MagLev) technology have proven to be effective for improving disease diagnostics. MagLev technique has the capacity to detect and separate useful diagnostic biomarkers from biocomplex environments (e.g., blood and plasma), minimizing the unpleasant daunting task of sample preparations and labeling procedures. Here, we demonstrate the capability of this technique combined with image analysis and machine learning approaches for discriminating the various types of multiple sclerosis (MS) as an important model disease. To arrive at a systematic expert system, we combined robust statistical analysis with machine learning to (1) detect and remove outliers from the raw MagLev image datasets; then (2) process the images and output a low dimensional representation of massive data without losing the main statistical features; and finally (3) predict the MS clinical disease type (Relapsing-Remitting, Primary–Progressive, or Secondary–Progressive) using a classifier. This is expected to improve MS diagnostics since the current practices rely solely on clinical observation and central nervous system imaging, making management approaches are often reactional and inefficient. Thus, there is a need to identify the disease type early on. MagLev is expected to improve MS diagnostics, thereby aiding in prognosis and guiding adequate treatment choices before the patient exhibits signs of permanent neurological deficits.

The prevalence of obesity in Korean adults was 56.1% in 2019. This study aimed to find obesity phenotypes from the KNHANES(2015–2019) and determine the risk factors associated with each type. In 15,179 participants, three obesity phenotypes, high BMI (short heavy obesity, n=1,685), high waist circumference (WC) (tall abdominal obesity, n=549), and BMI/WC combination (heavy abdominal obesity, n=3,538), were compared to non-OB (n=9,425). Marital status, lower income and education levels were highly associated with abdominal obesity. Insufficient exercise or skipping breakfast were associated with the WC or BMI/WC obesity type. The BMI/WC risk was 3.25 times higher in males with high TG and 4.6–4.8 times higher in females with high FAS or TG, and the risk increased to 7-8 times higher in three combinations (HYP+HDLc+FBS) compared to the control. The K-Score to test balanced diets was lower in BMI/WC than in others. Low intakes of FI-4(fruits) in men and FI-2(meat), FI-3 (vegetables), and FI-5 (milk/milk products) in women with BMI/WC and WC types, but BMI type was not associated with diets. Compared to BMI, the BMI/WC or WC obesity type was an indicator of metabolically unhealthy obesity associated with obesogenic environments including food/diets pattern and unhealthy behaviors.

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

Glycine is an important neurotransmitter in vertebrates, performing both excitatory and inhibitory actions. Synaptic levels of glycine are tightly controlled by the action of two glycine transporters, GlyT1 and GlyT2, located on the surface of glial cells and glycinergic or glutamatergic neurons, respectively. Glycinergic neurotransmission in invertebrates has so far only been investigated in a very limited number of species, and, although it was suggested that its functions are to some extent conserved with vertebrates, the evolution of glycinergic neurotransmission remains very poorly understood. Here, by combining phylogenetic and gene expression analyses, we characterized the glycine transporter complement of amphioxus, an important invertebrate model for studying the evolution of chordates. We show that amphioxus possesses three glycine transporter genes, two of which (GlyT2.1 and GlyT2.2) are closely related to GlyT2 of vertebrates, while the other (GlyT) is a member of an ancestral clade of deuterostome glycine transporters. While expression of GlyT2.2 is predominantly non-neural, GlyT and GlyT2.1 are widely expressed in the amphioxus nervous system and are characterized by differential expression in neurons and glia, respectively. However, in vertebrates, glycinergic neurons express GlyT2 and glia GlyT1, suggesting that the evolution of the chordate glycinergic system was accompanied by complex genetic remodeling leading to the paralog-specific inversion of gene expression. Albeit this genetic divergence between amphioxus and vertebrates, we found strong evidence for a general conservation of the role of glycinergic neurotransmission during larval swimming, allowing us to hypothesize that the neural networks controlling the rhythmic movement of chordate bodies are homologous.

With the exponential growth in today’s technology and its expanding areas of application it has become vital to incorporate it in education. One such application is Knowledge Discovery in Databases (KDD) which is a subset of data mining. KDD deals with extracting useful information and meaningful patterns from the database that were not known before. This study is a detailed application of KDD and focuses on analyzing why a particular set of students performed better than others and what factors influenced the results. The study is conducted on a dataset of 480 students and across 16 different features. The authors implemented 4 major classification techniques namely Logistic Regression, Decision Tree, Random Forest and XGB classifier. Obtaining the key features from the top performing ML algorithms that have a major impact on the performance of the student, the study takes these features as a baseline for further analysis. Further data analysis highlights patterns in the data. The study concludes that there are a lot of non-academic factors that influence the overall performance of a student and should be taken into consideration by universities and other relevant bodies.

Buyer practices have changed as individuals are figuring out how to live with the new truth of COVID-19. Take-out and conveyance orders have expanded, and our customer has added new items to their menu because of new client inclinations. With every one of the continuous changes, the customer had numerous unanswered inquiries, for example, Smartbridge has broad involvement with café innovation development Café TECHNOLOGY CAPABILITIES :Are the most famous items as yet unchanged after COVID? :Which are the most sold item blends now? :What is the acknowledgment of new things? :What are clients purchasing alongside new things? :How have liquor deals changed? The customer previously had reports that followed item deals and operational measurements, notwithstanding, there was a need to get a more profound knowledge into item examination. The customer expected to recognize what items and introductions were being sold all the more frequently, measure the acknowledgment of new items, and figure out what items clients buy together to improve advertising efforts, advancements, and deals. he E-business industry is filling immensely in the Indian market. The modest 4G web bundles in India clearly gives a push to these ventures. Thus, as Covid19 first hit in Quite a while, individuals got terrified to go out from their homes in light of the fact that, in their mind, it's a dread of Covid. They even wonder whether or not to go out to purchase fundamental (FMCG) products. Frenzy purchasing additionally has seen and to stay away from this dread of COVID-19, individuals are offering inclinations to the E-Commerce destinations to purchase fundamental products and a few clients are new which joined to purchase fundamental merchandise during this Pandemic Lockdown period. Numerous clients are moving their purchasing conduct from disconnected retail locations to online stores. This paper examines the customer buying pattern during lockdown.

The Mediterranean diet represents one of the most studied dietary patterns, however, there is no single tool for measuring the grade of adherence and no single criteria to adapting these indices to pregnant women. We characterized the adherence to the Mediterranean diet (MDA) of pregnant women participating in the NELA cohort and identified the sociodemographic determinants and lifestyle habits associated with a higher risk of a low MDA. Maternal diet during gestation was assessed by a validated Food Frequency Questionnaire (FFQ) (n=665). We estimated Relative Mediterranean Diet score (rMED), Alternative Mediterranean Diet score (aMED) and Alternate Healthy Index-2010 (AHEI-2010). Multivariate regression models were performed to identify the sociodemographic and lifestyle factors associated to each index. Mothers with lower age and more previous deliveries had a greater probability of low MDA (P &lt;0.05). Only, for aMED index, mothers with university education and / or who practiced 2 or more hours per week sport activities had a lower probability of a low MDA (P &lt;0.01). These results may be useful in order to design intervention strategies and dietary recommendation for pregnant women.

：Sleep stage on the whole night is not steady. Sleepers generally pass through three to five cycles. In each cycle, there are occur four typical sleep stages, such as wake stage (WS), light stage (LS), deep sleep (DS), rapid eye movement sleep stage (REM). According to the natural routine, in this paper, we investigate the stage transition and analyze the feature of stage transition using the local cluster Algorithm (LCA). Two-cycle sleep model (TCSM) is proposed to automatically classify sleep stages using over-night continuous heart rate variability (HRV) data. The generated model is based on the characteristics of the nested cycle's sleep stage distribution and the transition probabilities of sleep stages. Experiments were conducted using a public data set including 400 healthy subjects (female 239, male 161) and the model’s classification accuracy was evaluated for four sleep stages: WS, LS, DS, REM. The experimental results showed that based on the TCSM model, the segmentation classification of pure sleep is 5.2% higher than that of the traditional method, and the accuracy of segmentation classification is 11.2% higher than the traditional sleep staging accuracy. The experimental performance is promising in terms of the accuracy, sensitivity, and specificity rates compared with the ones of the state-of-the-art methods. The study contributes to improve the quality of sleep monitoring in daily life using easy-to-wear HRV sensors.

Cortical actomyosin flows, among other mechanisms, scale up spontaneous symmetry breaking and thus play pivotal roles in cell differentiation, division, and motility. According to many model systems, myosin motor-induced local contractions of initially isotropic actomyosin cortices are nucleation points for generating cortical flows. However, the positive feedback mechanisms by which spontaneous contractions can be amplified towards large-scale directed flows remain mostly speculative. To investigate such a process on spherical surfaces, we reconstituted and confined initially isotropic minimal actomyosin cortices to the interfaces of emulsion droplets. The presence of ATP leads to myosin-induced local contractions that self-organize and amplify into directed, large-scale actomyosin flows. By combining our experiments with theory, we found that the feedback mechanism leading to a coordinated, directional motion of actomyosin clusters can be described as asymmetric cluster vibrations, caused by intrinsic non-isotropic ATP consumption, in conjunction with spatial confinement. By tracking individual actomyosin clusters, we identified fingerprints of vibrational states as the basis of directed motions. These vibrations may represent a generic key driver of directed actomyosin flows under spatial confinement in vitro and in living systems.

We propose a novel method for salient object detection in different images. Our method integrates spatial features for efficient and robust representation to capture meaningful information about the salient objects. We then train a conditional random field (CRF) using the integrated features. The trained CRF model is then used to detect salient objects during the online testing stage. We perform experiments on two standard datasets and compare the performance of our method with different reference methods. Our experiments show that our method outperforms the compared methods in terms of precision, recall, and F-Measure.

Populaces are prominent indicators of livability in creating ‘street life’ for cities and public spaces. Evaluating people’s experiences is significant in creating a city liveliness and urban heritage trail. The exploration of design strategies that could allow them to integrated and connected with other spaces in the context of city and heritage as well as creating a social life among them. The measuring variables are people’s experience on the spaces; thus, create the pattern of behavior, which cause spaces liveliness, using Kuala Lumpur Heritage Trail as an example of pedestrian priority streets, city environment and heritage value. The aim of this research is to evaluate people’s experiences and analyze their behavior towards the urban street design within cities environment and Malaysia heritage values. The analyzed review comprising on the livability of the street in the context of interrelation between behavioral patter of people and the preferences of urban heritage. Hence, this paper will give an understanding of how people experiences the presence of urban streets and heritage values, thus, bringing liveliness to the streets.

Identifying group movement patterns of crowds and understanding group behaviors is valuable for urban planners, especially when the groups are special such as tourist groups. In this paper, we present a framework to discover tourist groups and investigate the tourist behaviors using mobile phone call detail records (CDRs). Unlike GPS data, CDRs are relatively poor in spatial resolution with low sampling rates, which makes it a big challenge to identify group members from thousands of tourists. Moreover, since touristic trips are not on a regular basis, no historical data of the specific group can be used to reduce the uncertainty of trajectories. To address such challenges, we propose a method called group movement pattern mining based on similarity (GMPMS) to discover tourist groups. To avoid large amounts of trajectory similarity measurements, snapshots of the trajectories are firstly generated to extract candidate groups containing co-occurring tourists. Then, considering that different groups may follow the same itineraries, additional traveling behavioral features are defined to identify the group members. Finally, with Hainan province as an example, we provide a number of interesting insights of travel behaviors of group tours as well as individual tours, which will be helpful for tourism planning and management.

Gait abnormalities are one of the distinguishing symptoms of patients with Parkinson's disease (PD) that contribute to fall risk. Our study compares the gait parameters of people with PD when they walk through a predefined course without assistance, with a conventional walker, and with a motorized walker under different speed cues. Six PD subjects were recruited at the New York Institute of Technology College of Osteopathic Medicine to participate in this study. Spatial posture and gait data of the test subjects were collected via a VICON motion capture system. We developed a framework to process and extract gait features and applied statistical analysis on these features to examine the significance of the findings. The results showed that motorized walkers with haptic cues significantly improved gait symmetry of PD subjects. Specifically, the asymmetry index of the gait cycle time was reduced from 6.7% when walking without assistance to 0.56% and below when using a walker. Furthermore, the double support time of a gait cycle was reduced by 4.88% compared to walking without assistance.

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represents an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity are typically not reflecting other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definition based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis.

The Inverted F Antenna (IFA) with the parasitic element on a finite conducting plane is proposed in the range frequency of 0.1 to 5.5 GHz and its characteristics are analyzed numerically. In this research, the parasitic element and the main IFA are investigated to obtain the resonance frequency for multiband operation purposes. The parasitic element is placed beneath adjusted to the main IFA to derive more frequency bands. The distance between the parasitic element and main horizontal element extremely affects the performance of the IFA. It is found that when the parasitic element is located closer to the conducting plane, this element is coupled by the current on the conducting plane. Consequently, the return loss bandwidth becomes narrower. Therefore, the gain of the proposed IFA becomes a bit higher. The antenna gain is about 8.21 dB at band #3 (λ_1.747), 7.43 dB at band #5 (λ_2.967) and 8.82 dB at band #6 (λ_4.023). This occurs when the calculation condition is antenna height h1 = 23 mm, h2 = 21 mm, horizontal antenna elements L = 173.2 mm, L1 = 140.9 mm and Lp = 152 mm, shorted element Ls = 30.7 mm, the distance between parasitic element and shorted element pyl = 5 mm. While the size of conducting plane is considered pxp+pxm by pyp+pym as 57.5+57.5 mm by 200+50 mm. In the numerical analysis, the electromagnetic simulator WIPL-D based on Method of Moment is used. The results show that the proposed IFA has UHF and SHF channel receiver which are suitable for advanced wireless service (band #3), mobile phones, Bluetooth, maritime service, radiolocation service (band #5) and radars, mobile phones, commercial wireless LAN (band #6).

The geographical environment, food culture, and dietary habits are substantially different between the southern and northern regions in China. We investigated the associations with dietary patterns and metabolic syndrome between Chinese adult from the southern and northern regions (North: 1249; South: 1849) using data from the Chinese Health and Nutrition 2009 survey. Respectively, four dietary patterns were identified by factor analysis in the two regions. Each dietary pattern of factor score was calculated for three groups by tertile (T1<T2<T3). In the northern region, the association between the Alcohol and Western pattern and the risk of abdominal obesity (OR: 1.31; 95%:1.01, 1.68), hypertriglyceridemia (OR: 1.35; 95%:1.05, 1.74), high fasting blood glucose (OR: 1.37; 95%: 1.05, 1.80), and hypertension (OR: 1.55; 95%: 1.45, 1.99) was increased. In the southern region, the Convenience Food pattern was positively associated with hypertriglyceridemia (OR: 1.53; 95%: 1.03, 2.26), low HDL-cholesterol (OR: 1.96; 95%: 1.12, 3.43), and metabolic syndrome (OR: 1.79; 95%: 1.03, 3.11). The Alcohol dietary pattern was positively associated with high fasting blood glucose (OR: 1.83, 95%: 1.13, 2.97). There are some dietary pattern differences in the two regions. It is necessary to consider the factors of food culture and food intake habits in order to provide nutrition education to Chinese individuals from different regions in the future.

The loose and porous structure and abundant pores of biochar provide conditions for being a suitable fertilizer carrier. Biochar loaded with beneficial microorganisms will greatly promote plant growth and soil improvement. In this work, an environmentally friendly Paenibacillus mucilaginosus loaded biochar-based fertilizer (B@PM) with high nutrient content, good slow-release effect and increased biological activity was prepared. The released mechanism of P-K-Ca from B@PM and the synergistic effect on the soil nutrients and plant growth were also analyzed. The experimental results showed that the release behavior of P, K and Ca from B@PM was diffusive and dissolved, which conforms to the Power function and Parabolic diffusion models, respectively. The potting experiment showed that the root length (30.77%), leaf width (71.67%), and plant height (81.08%) of Chinese cabbage were enhanced after the application of B@PM, and the organic matter, available phosphorus, available potassium, and total calcium in the soil were also substantially enhanced. In addition, the abundance of the Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes in the in the rhizosphere soil was increased, as well as the activities of catalase (82.84%) and alkaline phosphatase (39.64%). The results of RDA analyses showed that B@PM increased the content of the environmental factors, such as OM, URE, EC, TCa, AK, CAT, AP and ALP, thus improving soil quality and plant length.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Bacteriophages (phages) are potential alternatives to chemical antimicrobials against pathogens of public health significance. Understanding the diversity and host specificity of phages is important for developing effective phage biocontrol approaches. Here, we assessed the host range, morphology, and genetic diversity of eight Salmonella enterica phages isolated from a wastewater treatment plant. The host range analysis revealed that six out of eight phages lysed more than 81% of the 43 Salmonella enterica isolates tested. The genomic sequences of all phages were determined. Whole genome sequencing data (WGS) data revealed that phage genome sizes ranged from 41 to 114 kb with GC contents be-tween 39.9 and 50.0 %. Two of the phages SB13 and SB28 represent new species Epsep-timavirus SB13 and genera Macdonaldcampvirus, respectively as designated by the In-ternational Committee for the Taxonomy of Viruses (ICTV) as per genome based taxonomic classification. One phage (SB18) belonged to the Myoviridae morphotype while the re-maining phages belonged to the Siphoviridae morphotype. The gene content analyses showed that none of the phages possessed virulence, toxin, antibiotic resistance, type I-VI toxin-antitoxin modules or lysogeny genes. Three (SB3, SB15 and SB18) out of the eight phages possessed tailspike proteins. Whole genome-based phylogeny of the eight phages with their 113 homologs revealed three clusters A, B, C and seven subclusters (A1, A2, A3, B1, B2, C1 and C2). While cluster C1 phages were predominantly isolated from animal sources, cluster B contained phages from both wastewater and animal sources. The broad host range of these phages highlights their potential use to control the presence of S. enterica in foods.

This study analyzes tree diversity and its ecological importance value in silvopastoral systems in the Sumaco Biosphere Reserve (SBR), Ecuador, along an altitudinal gradient of 400-2000 masl. Twenty-six plots distributed in low (400-700 masl), medium (701-1600 masl) and high (1601-2000 masl) zones were used. The Shannon index and the Importance Value Index (IVI), based on abundance, dominance and relative frequency, were estimated. The results show variations in the diameter structure of the trees, influenced by factors such as settlement history and pasture management. The lower and middle zones showed higher tree density and diversity, linked to regeneration and the presence of nearby forests. Species of high commercial value, such as Cedrela odorata and Jacaranda copaia, were common, reflecting knowledge of the local timber market. In the lower and middle zones, the 10 most important species accounted for more than 70% of the trees, and up to 96% in the upper zone, indicating the need for further research on abundance factors and promotion of diversification in pastures. A total of 51 tree species were identified, mostly native, 64.7% are classified by the IUCN as "Least Concern", 31.4% as "Not Evaluated", and 3.9% as "Vulnerable", specifically highlighting Cedrela odorata and Cedrela Montana. The study concludes with policy recommendations related to the importance of trees in silvopastoral systems for the conservation of species and the livelihoods of local communities, highlighting the need for responsible management of Amazonian pasturelands.

Tandemly organized rRNA genes are the typical example of a multigene family, where individual members evolve coordinately within but independently between species due to gene conversion and unequal crossing over. More frequently, in eukaryotic species with an inter-species hybrid origin, expression of unhomogenized rRNA genes from one progenitor is epigenetically silenced because of nucleolus dominance, and distinct rRNA genes may lose functionality and evolve faster. Interestingly, we obtained unusual ribosomal gene sequences from Oryza species that showed great diversity and did not appear in the present rice genomic sequence. The diversity of rDNA sequences indicated that the homogenization in rice is incomplete and explains the introgression of distinct rRNA gene families into ancestral rice genome before speciation and continent separation. The divergent large subunit (LSU) ribosomal genes are expressed, some of them differentially, depending on the N-fertilization of plants. Detection of differential transcripts of the rRNA genes suggested that rRNA gene families are not functionally equivalent. Phylogenetic analysis assigned Oryza species branching order to monocots, and monocot lineages probably have the same ecological origin by molecular clock calculation. Therefore, our results suggested that the geographical distances of continents separation cause barriers to the gene flow and homogenization among Oryza species which requires further explanation,

The purpose of this investigation was to study the impact of different rates of bio fertilizer on agronomic characteristics and the relations among herbaceous plant diversity and soil properties of Aloysia citrodora in central Greece. For this aim a two – year Completely Randomized Design (CRD) field experiment was carried out in central Greece. The experiments included four biological fertilizer levels, BF0: 0 kg ha-1, BF50: 50 kg ha-1, BF100: 100 kg ha-1 and BF150: 150 kg ha-1 with 3 replication. Plant height, dry stem, dry leaves, dry total yield and Leaf Area Ιndex (LAI) were measured during the two growing years. The results showed that in the 1st studied the maximum plant height was observed in BF150 treatment while the 2nd year the BF150 level provoked a raise of 16.08% and 1.09% compared to BF50 and BF100, respectively. The 1st year the values of total dry yield were better in BF150 application. The 2nd year the total yield increased by 50.27% in BF100 and 50.09% BF150 treatments. Moreover, LAI was ameliorated by applied the BF100 and BF150 treatments both in two studied years. A key finding in this study is that Aloysia citrodora ecosystem favors herbaceous plant species richness. Also, soil factors (soil organic matter, P and K) promote positive herbaceous plant diversity within the Aloysia citrodora ecosystem. Finally, Aloysia citrodora can be a promising medicinal plant, cultivated under the Mediterranean climatic conditions.

The South of France is a biodiversity hotspot within Europe. Here, we present a comprehensive review of surveys conducted in the Cent Fonts aquifer, an overlooked subterranean biodiversity hotspot embedded in a region rich in stygobiotic species and threatened by climate change and water abstraction projects. Key studies, spanning from 1950 to 2006, show a progression in survey methods and results, although troglobiotic species remain poorly documented. With 43 stygobiotic species recorded, the Cent Fonts is the second richest stygobiont hotspot in Europe. Most species are regional endemics, a quarter of which are considered vulnerable by the IUCN. The Cent Fonts also hosts several relict species and is the type locality of four species. Such a high biological value clearly deserves to be preserved. Our analysis warns of a possible decline in biodiversity, as 8 of the species recorded in the 20th century were absent from the 2006 survey, suggesting potential threats of unknown origin. The capture of the Cent Font springs for water abstraction is discussed as a potential threat to this ecosystem and its unique biodiversity. Three new species of stygobiotic molluscs are described, one of which was collected in the Cent Fonts.

Studies on the domestication, genetic differentiation, and crop evolution of foxtail millet are re-viewed. Several genetic studies were carried out to elucidate the genetic relationships among foxtail millet accessions originating mainly from Eurasia, based on intraspecific hybrid pollen semi-sterility, isozymes, DNA markers, and single-nucleotide polymorphisms. Most studies suggest that China is the center of diversity of foxtail millet, and landraces were categorized into geographical groups. Furthermore, the evolution of genes was reviewed (i.e., the Waxy gene conferring amylose content in the endosperm, the Si7PPO gene controlling polyphenol oxidase, the HD1 and SiPRR37 genes controlling heading time, the Sh1 and SvLes1 genes involved in grain shattering, and the C gene controlling leaf sheath pigmentation), and the variation and distribu-tion of these genes suggested complex patterns of evolution under human and/or natural selec-tion.

Woody and non-woody plant species conservation is one of the ecosystem services provided by agroforestry (AF) systems across the agricultural landscapes. Little attention has been paid in as-sessing the plant diversity conservation of AF systems. The study was, thus, aimed to investigate plant species diversity, structure, and composition of three AF systems in Gedeo zone of south eastern Rift–valley Agricultural landscape of Ethiopia. The study was conducted in three agroforestry systems, namely, enset based, coffee–enset based (C-E based AF) and coffee-fruit trees–enset based (C-Ft-E based AF) agroforestry systems. Twenty farms representative of each AF system were randomly selected and inventory of the floristic diversity was employed in a 10×10 meter sample plot per farm. A total of 52 perennial woody and non–woody plant species belonging to 30 families were recorded. Of all species identified 33 (63.5%) were native, of which two species were registered as endemic. The highest proportion of native species was recorded in enset based AF (93.3%) and the least were in C–Ft–E based AF (59%). According to IUCN Red List and local criteria, 13 species were recorded as of interest for conservation in all AF systems. The woody species Prunus africana was identified as both vulnerable by IUCN Red List and rare for 25% of species that least occurred. The Shannon diversity index and richness showed that C–Ft–E based AF systems were significantly different from the two remaining AF systems. However, the species abundance and evenness did not show significant differences between the three AF systems. In general, retaining such number of woody and non–woody perennial plant species richness under AF systems of the present study underlines their potential for biodiversity conservation.

Guava (Psidium guajava L.) is a species is widely distributed in Córdoba, despite this, there are few studies that have been carried out to understand its genetic diversity. For this reason, the objective of this research was to evaluate the genetic diversity and variability of guava (Psidium guajava L) using microsatellite markers in Montería, Córdoba-Colombia. Forty-five accessions were evaluated. For DNA extraction, the CTAB 2x extraction protocol was used with modifications. The extracted DNA was amplified by the PCR technique using seven microsatellite markers. A total of 46 alleles were found with an average of 6.5 alleles per locus. A total of 28 private alleles were identified in the populations, possibly fixed by different evolutionary forces. The evaluated population presented an average expected heterozygosity of 0.572 and the observed heterozygosity was lower (0.058). The fixation index presented a total average of 0.906, indicating that in Montería there is an excess of homozygotes. The PIC values allowed us to determine that the markers mPgCIR9, mPgCIR11, mPgCIR13, mPgCIR16, mPgCIR19 and mPgCIR22 are highly informative, while mPgCIR23 is moderately informative. The guava population in Montería presented a low genetic diversity within the subpopulations, which could be related to inbreeding events such as self-pollination..

Desert ecosystem occupies an important position in the composition of global biodiversity. The Tarim Basin locates in south Xinjiang of China and has the world 's second largest mobile desert, the Taklamakan Desert. As an endemic species in this region, Phrynocephalus forsythii has been demonstrated with potential high extinction risk to climate change. In order to understand the overall genetic status and provide accordant conservation strategies of the species, we investi-gated the genetic diversity and population structure of P. forsythii from 15 sites in the Tarim Basin using 21 highly polymorphic microsatellite markers. We found significant genetic structure across the study region. We also revealed generally low levels of gene flow between the 25 sites, sug-gesting individual dispersal and migration may be restricted within populations. In addition, geographical distance and ambient temperature might be important factors in explaining the observed genetic structure. Our results will provide scientific basis for the future protection of P. forsythii in this area, as well as an important reference for the conservation and management of biodiversity in desert ecosystems.

The Cosmonaut Sea is an under-studied area and a “blank canvas” for macrobenthos research. Here, we report on the species diversity and community structure of macrobenthos collected using the tringle trawl on the 38th Chinese National Antarctic Research Expedition (CHINARE) in the Cosmonaut Sea, East Antarctica. A total of 11 tringle trawls were deployed at different depths across the shelf, slope and seamount of the Cosmonaut Sea. A total of 275 macrobenthic species were found from 207-1994 m. The species richness per station varied from 23 to 89. Echinoderms (100 species), arthropods (48 species) and mollusks (36 species) were the most dominant groups. Echinoderms and arthropods dominated in abundance at seamount stations, and echinoderms, arthropods and polychaetes dominated in abundance at slope stations, while bryozoans, corals, ascidians and sponges were abundant on the Cosmonaut Sea Shelf. Depth was the major driving force influencing the distribution of macrobenthos. The main components were two core communities. One was dominated by sessile suspension feeders and associated fauna. Variants of this community include sponges and bryozoans. The other core community was dominated by mobile deposit feeders, infauna and grazers–epifauna, which included arthropods and echinoderms. The results showed that the slope (40-50° E, 65-67° S) of the Cosmonaut Sea may be an important area with complex ecological processes. The results of this study contribute to the knowledge of species diversity and communities of macrobenthos in the Cosmonaut Sea and provide monitoring data for future ecosystem health assessments and better protection.

This review resumes published data on fungal diversity in and within monuments (e.g., religious and secular monuments, museums, and statues), covering a multidisciplinary investigation into the complex interactions between fungi and cultural heritage structures. Fungi represent remarkable adversaries to monuments, potentially compromising their structural integrity and aesthetic value. Based on a bibliographic search of manuscripts published, the knowledge of fungal communities colonizing monuments was comprehensively assessed. This work first describes the diverse fungal species implicated in the degradation of monument materials (e.g., stone, metal, and glass). It elucidates the factors governing fungal colonization and proliferation in and within these structures (e.g., environmental conditions, construction materials, and human interventions). Finally, the efficacy of preservation and restoration techniques to mitigate fungal threats and safeguard our cultural heritage is also discussed. This synthesis highlights the pivotal role of mycological research in heritage conservation, and a platform for future studies to address critical knowledge gaps is provided. Understanding fungal diversity in and within monuments is critical to preserving these invaluable cultural treasures, as it informs targeted conservation strategies and ensures their longevity in the face of fungal challenges.

Lily database online genomic resource composed of Korean Lily Germplasm Collection, Transcriptome Sequences, molecular markers, transcription factors (TF) and DEGs data. A total of ~0.23 gb of RNA-sequences data were mined for gene identification, marker development and gene expression analysis. As a result, 47,863 SSR, 20,929 SNP and 1213 COS-marker were developed. A total of 1327 TF genes were identified and characterized. This is the first unique, user-friendly, genomic resource database for Lilium species. It is a relational database based on a ‘three-tier architecture’ that catalogs all the information in MySQL table and a user-friendly query interface and data visualization page developed using JavaScript, PHP and HTML code. The search parameters are highly flexible, user can be retrieved data by using either single or multiple search parameters. Data present in this database can be used for germplasm characterization, gene discovery, population structure analysis, QTL mapping and accelerating the lily variety improvements. This database can be accessed through this link: http://www.genomicsres.org/lilidb/.

Proso millet is an important allotetraploid cereal crop, however, it is the least studied species of the Poaceae family as it is an under-utilized crop. Genomic resources of proso millet are very limited compared to the major crops. Understanding of genetic relationships among germplasm resources is important for future breeding endeavors. In the present study, the SSR markers were employed to assess the polymorphism and genetic diversity of 100 millet accessions from different countries, which were tested in the dry steppe zone conditions of the Akmola region from 2020 to 2022. The use of 20 SSR markers detected a total of 47 alleles with an average allele number of 2.35 per locus among these proso accessions. Nine of them were polymorphic among genotypes, which suggests that these SSR markers can be used for genetic studies. The results showed a moderate level of polymorphism information content (PIC) averaged at 0.424, ranging from 0.125 to 0.795. The markers SSR 67, SSR-82, SSR-85 and SSR-109 showed high PIC values, 0.536, 0.756, 0.795 and 0.758 respectively. Markers SSR 85 and SSR 86 significantly correlated to agronomic traits, such as productive tillering (PT) and grain yield (GY). The genetic structure, UPGMA cluster and PCoA assay indicated that the accessions originated from Central Asia had higher genetic diversity. Based on Structure (K=3), all the accessions were divided into three groups, whereas the gene pool originated from Central Asia were detected in all the three clusters. Based on principal component analysis (PCA), the accessions of Central Asian origin were genetically closer to the North Asian group.

The goal of this narrative review was to identify, synthesize and summarize research providing both institutional and personal recommendations for female leaders who aspire to hold leadership roles in academia. Existing evidence regarding factors that influence females acquiring leadership positions was first gathered and examined, noting recurring issues that have been identified as inimical to women assuming leadership roles. Recent research studies and statistical trends were then investigated, tracking and reporting on the increase in female leadership in academia that has occurred over recent years. Quantitative and qualitative literature focusing on successful strategies to support females aspiring to academic leadership positions were then elaborated upon, with specific factors identified in order to deepen understanding of shifts that may help to account for the rise of females in academic leadership roles. The recommendations resulting from the findings of this narrative review could be used to scaffold female success in the pursuit of academic leadership roles and offer insights for university executives and administrators on methods of more effectively supporting an increase in female leaders in academia.

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 came after found in only seven individuals, 14 PFAs occurred once (7 PFAs twice), implying high frequency of rare PFAs. Interestingly, more than half of the (15) PFAs were specific to clade I, only one and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sextual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The way of allele sharing and FST values between three clades were to some extent in agreement with pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed cross-species polymorphisms. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

Macroalgae and macroalgae-associated bacteria together constitute the most efficient metabolic cycling system in the ocean. Their interactions, especially the responses of macroalgae-associated bacteria communities to algae in different geographical locations, is mostly unknown. In this study, metagenomics was used to analyze the microbial diversity and associated algal polysaccharide-degrading enzymes on the surface of red algae among three remote regions. There were significant differences in the macroalgae-associated bacteria community composition and diversity among the different regions. At the phylum level, Proteobacteria, Bacteroidetes, and Actinobacteria had a significantly high relative abundance among the regions. From the perspective of species diversity, samples from China had the highest macroalgae-associated bacteria diversity, followed by those from Antarctica and Indonesia. In addition, in the functional prediction of the bacterial community, genes associated with amino acid metabolism, carbohydrate metabolism, energy metabolism, metabolism of cofactors and vitamins, and membrane transport had a high relative abundance. Canonical correspondence analysis and redundancy analysis of environmental factors showed that, without considering algae species and composition, pH and temperature were the main environmental factors affecting bacterial community structure. Furthermore, there were significant differences in algal polysaccharide-degrading enzymes among the regions. Samples from China and Antarctica had high abundances of algal polysaccharide-degrading enzymes, while those from Indonesia had extremely low abundances. The environmental differences between these three regions may impose a strong geographic differentiation regarding the biodiversity of algal microbiomes and their expressed enzyme genes. This work expands our knowledge of algal microbial ecology, and contributes to an in-depth study of their metabolic characteristics, ecological functions, and applications.

In order to understand the genetic diversity of germplasm resources of kumquat in Guangxi, 14 kumquat germplasm resources in Guangxi and 12 accessions from other provinces were analyzed by using SRAP markers. In total, 19 primer pairs with high stability, good reproducibility, and high polymorphism were chosen for analysis of all the 26 kumquat genotypes. Among the 101 amplified bands, 87 (86.14%) were polymorphic. SRAP markers were analyzed by employing Principal Coordinate Analysis, Population Structure Analysis and Hierarchical Cluster Analysis (UPGMA). The classification results showed that 26 kumquat germplasm could be divided into 5 groups, including cultivated kumquat, intergeneric hybrid, wild kumquat from other provinces, wild kumquat from Guangxi and hybrid kumquat from Guangxi. Guangxi kumquat germplasm occurred high genetic diversity, which were clearly divided into 3 groups like cultivated kumquat, wild kumquat and kumquat hybrid. And the 8 cultivated kumquat varieties in Guangxi were further divided into two subgroups. Wild kumquat in Guangxi and wild kumquat in other provinces belong to different groups, meanwhile the hybrids of Guangxi kumquat form independent groups, thus indicated that Guangxi wild kumquat and kumquat hybrid possessed certain specificity, or they maybe belonged to different species. Among the tested 26 kumquat accessions, 23 unique genotype-specific SRAP markers were detected for 14 kumquat genotypes, which made it possible to surely identify them. For the remaining 12 accessions without genotype-specific markers, they were distinguished by various combinations of markers. These results may have certain importance for kumquat genetic research and cultivar selection.

: Urinary schistosomiasis caused by the parasite Schistosoma haematobium is the most common form of schistosomiasis. This parasite has a high potential for genetic exchange within parasite populations giving rise to the genetic diversity that is important for its survival. Genetic differ-ences may lead to some parasite strains being more immunogenic which may have a negative impact on management and control of schistosomiasis. Therefore, understanding these genetic differences in the parasite may lead to better management of the disease. A literature search was done on PubMed, African Journals online and Google scholar using predefined search terms such as urinary schistosomiasis, S. haematobium, genetic diversity in sub-Saharan Africa in com-bination with Boolean operators (AND, OR). The search included studies published from 2000-2020 that emphasised on genetic diversity of Schistosoma haematobium in sub-Saharan Africa. Sixteen studies from 18 sub-Saharan African countries that met the inclusion criteria were se-lected. Most studies conducted in these countries showed a high genetic diversity of Schistosoma haematobium studies with microsatellite markers being the most commonly used method for ge-netic diversity determination. Fisher’s exact test showed that the distribution of genetic diversity in sub-Saharan African regions was not statistically significant (p=0.768). The highest number of studies on genetic diversity of Schistosoma haematobium were conducted in West Africa with Ni-geria and Zimbabwe in Southern Africa conducting the most studies, 4/36 (11%) each. Results obtained show the need for continued monitoring of genetic variations in Schistosoma haemato-bium in sub- Saharan Africa. This will aid in understanding the epidemiology of disease, ad-vancing novel treatment and vaccine strategies.

Capirona (Calycophyllum spruceanum Benth) is a tree species of commercial importance widely distributed in South American forests and is traditionally used for its medicinal properties and wood quality. Studies on this tree species have been focused mainly on wood properties, propagation and growth. Genetic studies on capirona are very limited to date. Today it is possible to explore genetic diversity and population structure in a fast and reliable manner by using molecular markers. We here used 10 Random Amplified Polymorphic DNAs (RAPDs) markers to analyze genetic diversity and population structure of 59 samples of capirona that were sampled from four provinces located in the eastern region of the Peruvian amazon. A total of 186 bands were manually scored, generating a 59 x 186 presence/absence matrix. We used R software to calculate genetic distances based on provesti coefficient. A dendrogram was generated using the UPGMA clustering algorithm and showed four groups that correspond to the geographic origin of the capirona samples. Similarly, a discriminant analysis of principal components (DAPC) confirmed that capirona is grouped into four clusters. However, we also noticed few accessions are intermingled. Genetic diversity estimation was conducted considering the four groups (populations) identified by adegenet package in R. Nei's genetic diversity estimate varied from 0.26 to 0.39 and Shannon index ranged from 2.48 to 2.83. AMOVA analysis revealed the greatest variation exist within populations (69.7%) and indicated that variability among populations is 31.5%. To our best knowledge, this is the first investigation employing molecular markers in capirona in Peru considering their natural distribution, and sheds light towards its modern genetic improvement and for the sustainable management of forests in Peru.

Rhodes grass (Chloris gayana Kunth) is one of the most important forage grasses used throughout the tropical and subtropical regions of the world. Enhancing the conservation and use of genetic resources requires the development of knowledge and understanding about the existing global diversity of the species. In this study, 104 Rhodes grass accessions, held in trust in the ILRI forage genebank, were characterized using DArTSeq markers to evaluate the genetic diversity and population structure, and to develop representative subsets, of the collection. The genotyping produced 193,988 SNP and 142,522 SilicoDArT markers with an average polymorphic information content of 0.18 and 0.26, respectively. Hierarchical clustering using selected informative markers showed the presence of two and three main clusters using SNP and SilicoDArT markers, respectively, with a cophenetic correction coefficient of 82 %. Bayesian population structure analysis also showed the presence of two main subpopulations using both marker types indicating the existence of significant genetic variation in the collection. A representative subset, containing 21 accessions from diverse origins, was developed using the SNP markers. In general, the results revealed substantial genetic diversity in the Rhodes grass collection and the generated molecular information, together with the developed subset, should help enhance the management, use and improvement of Rhodes grass germplasm in the future.

Success and impact metrics in science are based on a system that perpetuates sexist and racist ‘rewards’ through prioritizing citations and impact factors. These metrics are flawed and biased against already marginalized groups and fail to accurately capture the breadth of individuals’ meaningful scientific impacts. We advocate shifting this outdated value system to advance science through principles of justice, equity, diversity, and inclusion. We outline pathways for a paradigm shift in academic values based on multidimensional mentorship and promoting mentee wellbeing. These actions will require collective efforts supported by academic leaders and administrators to drive essential systemic change.

Energy and institutional quality are two factors that determine economic output, but these two factors are often neglected in the search for economic output. Therefore, this study examines the relative importance of energy use and its interaction with institutional quality for economic output. We employ a robust econometric estimation technique on a panel sample of 21 African countries between 2002-2019. Our results show that energy use is significant and negatively related to economic output while moderating terms of institutional quality are significantly associated with economic output, but the direction of the association depends on the specific quality. We find the moderating term control of corruption and government effectiveness to be negative and significantly associated with economic output, whilst political stability, regulatory quality, rule of laws, voice, and accountability positively impact. Our results imply that improved economic output is possible when there are specific institutional strategies.

Melon (Cucumis melo L.) a member of family Cucurbitaceae is extensively cultivated for its fleshy fruits. Based on the specific agro-climatic zones of cultivation as well as concerning the regional preferences, melon displays significant variability phenotypic and biochemical attributes. Below, an effort is put forth to considerably evaluate the scope of achievements while in the growth as well as the enactment of melon breeding programs by employing the newest solutions. Melon breeding has achieved critical milestones throughout the previous century, and we hope this trend will go on to persist down the road. However, studies have to determine new genetic information for genes associated with the challenges imposed by climate change. The identification of valuable hereditary and also metabolic variability in the form of landraces and melon wild relatives will be useful for harvest diversification and also for the broadening of the cultivated melon genetic base. Whereas, considerable information on genomics, and melon metabolomics, is beneficial for dissecting the basis of the inheritance of important traits and their impact on the former characteristics. Overall, we hope the manuscript is going to serve as a crucial resource for the melon breeders.

Diversity as well as temporal and spatial changes of the proportional abundances of different antibiotics (cycling, mixing or combinations thereof) have been hypothesised to be an effective administrative control strategy in hospitals to reduce the prevalence of antibiotic-resistant pathogens in nosocomial or community-acquired infections. However, a rigorous assessment of the efficacy of these control strategies is lacking. The main purpose here is to present a mathematical framework for the assessment of control stategies from a processual stance. To this end, we adopt diverse measures of heterogeneity and diversity of proportional abundances based on the concept of entropy from other fields and adapt them to the needs in assessing the impact of variations in antibiotic consumption on antibiotic resistance. Thereby, we derive a family of diversity measures whose members exhibit different degrees of complexity. Most important, we extent these measures such that they account for the assessment of temporal changes in heterogeneity including otherwise undetected diversity-invariant permutations of antibiotics consumption and prevalence of resistant pathogens. We apply a correlation analysis for the assessment of associations between changes of heterogeneities on the antibiotics and on the pathogen side. As a showcase, which serves as a proof-of-principle, we apply the derived methods to records of antibiotic consumption and prevalence of antibiotic-resistant germs from University Hospital Dresden. Besides the quantification of heterogeneities of antibiotics consumption and antibiotic resistance, we show that a reduction of prevalence of antibiotic-resistant germs correlates with a temporal change of similarity with respect to the first observation of antibiotics consumption, although heterogeneity remains approximately constant. Although an interventional study is pending, our mathematical framework turns out to be a viable concept for the assessment and optimisation of control strategies intended to reduce antibiotic resistance.

Live streaming conferences increase the participation of a diverse audience, help defray travel costs and overcome problems related to travel restrictions. In this article, we lay out tips for implementing live-streaming in scientific meetings. We also cover legal, ethical, and technical aspects implicated with live-streaming scientific talks. To write this article, we leveraged knowledge from our experience in organizing the symposium “Deciphering the Denisovans,” presented at the 88th Annual Meeting of the American Association of Physical Anthropology (AAPA) in Cleveland, OH, in 2019, as well as literature on the topic.

Background: Wheat root rot disease due to soil-borne fungal pathogens leads to tremendous yield losses worth billions of dollars worldwide every year. It is very important to study the relationship between rhizosphere fungal diversity and wheat roots to understand the occurrence and development of wheat root rot disease. Results: A significant difference in fungal diversity was observed between the diseased and healthy groups in the heading stage, but the trend was the opposite in the filling stage. The abundance of most genera with high richness decreased significantly from the heading to the filling stage in the diseased groups; the richness of approximately one-third of all genera remained unchanged, and only a few low-richness genera, such as Fusarium and Ceratobasidium, had a very significant increase from the heading to the filling stage. In the healthy groups, the abundance of most genera increased significantly from the heading to the filling stage; the abundance of some genera did not change markedly, or the abundance of very few genera increased significantly. Physical and chemical soil indicators showed that low soil pH and density, increases in ammonium nitrogen, nitrate nitrogen and total nitrogen contributed to the occurrence of wheat root rot disease. Conclusions: Our results revealed that in the early stages of disease, highly diverse rhizosphere fungi and a complex community structure can easily cause wheat root rot disease. The existence of pathogenic fungi is a necessary condition for wheat root rot disease, but the richness of pathogenic fungi is not necessarily important. The increases in ammonium nitrogen, nitrate nitrogen and total nitrogen contributed to the occurrence of wheat root rot disease. Low soil pH and soil density are beneficial to the occurrence of wheat root rot disease.

The latest methods based on deep learning have achieved amazing results regarding the complex work of inpainting large missing areas in an image. This type of method generally attempts to generate one single "optimal" inpainting result, ignoring many other plausible results. However, considering the uncertainty of the inpainting task, one sole result can hardly be regarded as a desired regeneration of the missing area. In view of this weakness, which is related to the design of the previous algorithms, we propose a novel deep generative model equipped with a brand new style extractor which can extract the style noise (a latent vector) from the ground truth image. Once obtained, the extracted style noise and the ground truth image are both input into the generator. We also craft a consistency loss that guides the generated image to approximate the ground truth. Meanwhile, the same extractor captures the style noise from the generated image, which is forced to approach the input noise according to the consistency loss. After iterations, our generator is able to learn the styles corresponding to multiple sets of noise. The proposed model can generate a (sufficiently large) number of inpainting results consistent with the context semantics of the image. Moreover, we check the effectiveness of our model on three databases, i.e., CelebA, Agricultural Disease, and MauFlex. Compared to state-of-the-art inpainting methods, this model is able to offer desirable inpainting results with both a better quality and higher diversity. The code and model will be made available on https://github.com/vivitsai/SEGAN.

Pig genetic resources in Africa originate from different regions. Genetic analysis has shown a strong phylogeographic pattern with the pigs on the eastern parts showing a high frequency of alleles from the Far East while the ones on the western parts show a strong European influence. This highlights the influence of trade routes on the genetic legacy of African pigs. They have, however, since adapted to the local environments to produce unique populations with unique attributes. Most of the pigs are now reared in resource-constrained smallholdings under free-range conditions. They are largely owned by women who spread ownership of the resource through kinship networks. Very little work has been done to characterize, conserve and sustainably utilize pig genetic resources in Southern Africa. The risk status of the breeds together with population numbers, distribution and other attributes are largely unknown. This paper proposes several strategies for the sustainable utilization of the pig genetic resources: a market-driven in situ conservation program and two complementary ex situ strategies. In addition, the possibility of community-based breed improvement programs is discussed.

Rocas Atoll is a unique environment in the Equatorial Atlantic Ocean, hosting a large number of endemic species and studies on the chemical diversity emerging from this biota are rather scarce. Therefore, the present work aims to assess the metabolomic diversity and pharmacological potential of the microbiota from Rocas Atoll. A total of 76 bacteria were isolated and cultured in liquid culture media to obtain crude extracts. About one third (34%) of these extracts were considered cytotoxic against human colon adenocarcinoma HCT-116 cell line. 16S rRNA gene sequencing analysis revealed that the bacteria producing cytotoxic extracts are mainly from the Actinobacteria phylum, including Streptomyces, Salinispora, Nocardiopsis and Brevibacterium genera, and in a smaller proportion from Firmicutes phylum (Bacillus). The search in the GNPS spectral library unveiled a high chemodiversity being produced by these bacteria, including rifamycins, antimycins, desferrioxamines, ferrioxamines, surfactins, surugamides, staurosporine and saliniketals, along with several unidentified compounds. Using an original approach, molecular network successfully highlighted groups of compounds responsible for the cytotoxicity of crude extracts. DEREPLICATOR+, a recently developed in silico tool (GNPS), allowed the identification of derivatives of the macrolide novonestimycin, as the cytotoxic compounds into the extracts produced by Streptomyces BRB-298 and BRB-302. Overall, these results highlighted the pharmacological potential of bacteria from this singular Atoll.

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximise the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

Food intake plays a pivotal role of human growth, which necessarily contributes 45% of global economy and wellbeing in general. Consumption of balanced food is elementary for overall good health while a shift of equilibrium can lead to malnutrition, prenatal death, obesity, osteoporosis and bone fractures, coronary heart diseases (CHD), idiopathic hypercalciuria, diabetes and many more. Though CHD, osteoporosis, malnutrition, obesity are being classified thoroughly in the literature, there are fragmented findings in the regime of kidney stone diseases (KSD) and the correlation with food intake therein. KSD associated with hematuria and renal failure poses an increasing threat to the healthcare and global economy while its emergence of Indian populations is being affected with multi-factorial urological disorder resulting from several factors. In this realm, epidemiological, biochemical, macroeconomic situations been portrayed when food intake is also a paramount importance which rarely been forecasted. Hence, in this article we will be reviewing the corollary connotation with diverse food consumption and the efficacy it plays in KSD extrapolating in Indian context.

Viruses are the most abundant biological entities in aquatic ecosystems and harbor an enormous genetic diversity. While their great influence on the marine ecosystems is widely acknowledged, current information about their diversity remains scarce. A viral metagenomic analysis of three water samples was conducted from sites on the South Scotia Ridge (SSR) near the Antarctic Peninsula, during the austral summer 2016. The taxonomic composition and diversity of the viral communities were investigated and a functional assessment of the sequences was determined. Phylotypic analysis showed that most viruses belonging to the order Caudovirales, especially the family Podoviridae (41.92-48.7%), similar to the viromes from the Pacific Ocean. Functional analysis revealed a relatively high frequency of phage-associated and metabolism genes. Phylogenetic analyses of phage TerL and Capsid_NCLDV (nucleocytoplasmic large DNA viruses) marker genes indicated that many sequences associated with Caudovirales and NCLDV were novel and distinct from known phage genomes. High Phaeocystis globosa virus virophage (Pgvv) signatures were found in SSR area and complete and partial Pgvv-like were obtained which may have an influence on host-virus interactions. Our study expands the existing knowledge of viral communities and their diversities from the Antarctic region and provides basic data for further exploring polar microbiomes.

Acid lime [Citrus aurantifolia (Christm.) Swingle] is a fruit crop, enriched with high commercial value and is cultivated in 60 out of 75 districts representing all geographical landscapes of Nepal. Lack of high yielding cultivars is probably one of the main reason for its extremely reduced productivity which warrants a deep understanding of genetic diversity in existing germplasm. Hereby, we aim to access the genetic diversity of acid lime germplasm cultivated at 3-different ecological gradients of eastern Nepal employing PCR-based Inter-Simple Sequence Repeats markers (ISSR). Altogether, 21 polymorphic ISSR markers were used to assess the genetic diversity in 60 acid lime cultivars sampled from different geographical locations. Analysis of binary data matrix was performed on the basis of bands obtained, scoring of the data was done accordingly, and principal coordinate analysis and phenogram were constructed using different computer algorithms. ISSR profiling yielded 234 amplicons, of which 87.18% were found to be polymorphic. The number of amplified fragments ranged from 7-18 with amplicon size ranging from 250-3200 bp. The NTSYS based Cluster analysis using UPGMA algorithm taking Dice Similarity coefficient separated 60 accessions into 2-major and 3-minor clusters. The genetic diversity analysis revealed the highest for Terai and the lowest for High-hill zone. Cluster I comprised of accessions from High-hill and Mid-hill regions revealing the close genetic relationship, whereas cluster II comprised of accessions from all three agro-ecological zones and the exotic varieties. Furthermore, our results revealed the accessions harvested from different geographical gradients were not genetically distinct, but highest diversity was observed in Terai accessions in comparison to the regions belonging to the High and Mid-hills. Thus, our data indicate that the ISSR provides a better option for evaluating the genetic diversity of Nepalese Acid Lime cultivars and furnished significant information, assisting parental selection in current and future breeding programs and germplasm conservation which ultimately may help to provide a technological breakthrough for the farmers of the developing country like Nepal.

Moonmilk are cave carbonate deposits that host a rich microbiome including antibiotic-producing Actinobacteria making these speleothems appealing for bioprospecting. Here we investigated the taxonomic profile of the actinobacterial community of three moonmilk deposits of the cave “Grotte des Collemboles” via high-throughput sequencing of 16S rRNA amplicons. Actinobacteria was the most common phylum after Proteobacteria, ranging from 9 to 23% of the total bacterial population. Next to actinobacterial OTUs attributed to uncultured organisms at the genus level (~44%), we identified 47 actinobacterial genera with Rhodoccocus (4 OTUs, 17%) and Pseudonocardia (9 OTUs, ~16%) as the most abundant in terms of absolute number of sequences. Streptomycetes presented the highest diversity (19 OTUs, 3%), with most of OTUs unlinked to the culturable Streptomyces strains previously isolated from the same deposits. 43% of OTUs were shared between the three studied collection points while 34% were exclusive to one deposit indicating that distinct speleothems host their own population despite their nearby localization. This important spatial diversity suggests that prospecting within different moonmilk deposits should result in the isolation of unique and novel Actinobacteria. These speleothems also host a wide range of non-streptomycetes antibiotic-producing genera, and should therefore be subjected to methodologies for isolating rare Actinobacteria.

Medical datasets may be imbalanced and contain errors due to subjective test results and clinical variability. The poor quality of original data affects classification accuracy and reliability. Hence, detecting abnormal samples in the dataset can help clinicians make better decisions. In this study, we propose an unsupervised error detection method using patterns discovered by the Pattern Discovery and Disentanglement (PDD) model, developed in our earlier work. Applied to the large data, the eICU Collaborative Research Database for sepsis risk assessment, the proposed algorithm can effectively discover statistically significant association patterns, generate an interpretable knowledge base for interpretability, cluster samples in an unsupervised learning manner, and detect abnormal samples from the dataset. As shown in the experimental result, our method outperformed K-Means by 38% on the full dataset and 47% on the reduced dataset for unsupervised clustering. Multiple supervised classifiers improve accuracy by an average of 4% after removing abnormal samples by the proposed error detection approach. Therefore, the proposed algorithm provides a robust and practical solution for unsupervised clustering and error detection in healthcare data.

Pedestrian Dead Reckoning (PDR) is a promising algorithm for indoor positioning. However, the accuracy of PDR degrades due to the accumulated error, especially in multi-floor buildings. This paper introduces a three-dimensional (3D) positioning method based on terrain feature matching to reduce the influence of accumulated error in multi-floor scene. The proposed method involves two steps: motion pattern recognition and position matching calibration. The motion pattern recognition aims to detect different motion states, i.e., taking the stairs or horizontal walking, from the streaming data. Then, stair entrances and corridor corners are matched with transition points of motion states and pedestrian turning points, respectively. After matching, calibration is performed to eliminate the accumulated errors. By carrying out experiments on a two-floor closed-loop path with a walking distance about 145 m, it is shown that this method can effectively reduce the accumulated error of PDR , achieving accurate 3D positioning . The average error is reduced from 6.60 m to 1.83 m.

In general sound waves propagate radially outwards from a point source. These waves will continue in the same direction, decreasing in intensity, unless a boundary condition is met. To arrive at a universal understanding of the relation between frequency and wave propagation within spatial boundaries, an analysis and comparison is made between the results of Chladni plate experiments and Chladni plate simulations. We consider a finite range of frequencies and plate geometries and present a model that has been shown to successfully recreate the nodal line patterns to a first approximation. We discuss the benefits of such a model and the future work necessary to develop the model to its full predictive capacity.

The field of nephrology has recently directed a considerable amount of attention towards the stimulator of interferon genes (STING) molecule since it appears to be a potent driver of chronic kidney disease (CKD). STING and its activator, the cyclic GMP-AMP synthase (cGAS) are among the most relevant inducers that promote the expression of type I interferons (IFN-Is). These cytokines have been long recognized as part of the mechanism used by the innate immune system to battle viral infections; however, their involvement in sterile inflammation remains unclear. Mounting evidence pointing to the involvement of the IFN-I pathway in sterile kidney inflammation provides potential insights into the complex interplay between the innate immune system and damage to the most sensitive segment of the nephron, the glomerulus. The STING pathway is often cited as the cause of renal disease originating from non-infection related caused by the induction of IFN-I expression. However, other receptors have been implicated in this process, mainly by recognizing host-derived nucleic acids. This review explores the main endogenous inducers of IFN-I in glomerular cells, discusses what exposure to the main autocrine and paracrine cytokines has on these cells, and identifies the pathways that are implicated in the development of glomerular damage.

Forest-grass intercropping patterns of protected cultivation has been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry (L. barbarum) intercropping and it is cultivated mostly by clean tillage. This paper takes 10 kinds of wolfberry-forage intercropping patterns, compares the effects of different planting modes on the growth, yield, photosynthetic characteristics, nutritional quality, and the degree of occurrence of diseases and pests, which aims to make clear the effects of wolfberry-forage intercropping patterns on wolfberry. The results showed that different intercropping combinations had different effects on wolfberry. The overall effect of Wolfberry-forage intercropping patterns on the growth of wolfberry were promote the photosynthetic characteristics. Ryegrass could increase the branch number, Lvyuan 5 and mangel increase branch length; Mangel, clover, sweet sorghum, ryegrass and stipas could reduce the damage of powdery mildew by 69%, and alfalfa, stipa and ryegrass could reduce the occurrence of aphids by 67% (P<0.05). Intercropping could increase carotenoids, flavonoids and ascorbic acid contents to improve wolfberry quality by 21%, 53% and 127%, respectively (P<0.05). Among all the performances, wolfberry-mangel intercropping has absolute advantages in promoting wolfberry yield and quality increase. Therefore the best patterns of wolfberry-mangel, wolfberry-ryegrass, wolfberry-alfalfa and wolfberry-clover were chosen.

This work introduces an innovative approach that unites a PIDND2N2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND2N2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system's response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing impressive performance. These important results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

Sensors and actuators are fundamental units in Cyber-Physical and Internet of Things systems. Because they are included in a variety of systems, using many technologies, it is very useful to characterize their functions abstractly by describing them as Abstract Entity Patterns (AEPs), that are patterns that describe abstract conceptual entities. For concreteness, we study them here in the context of autonomous cars. An autonomous car is a complex system because, in ad-dition to its own complex design, it interacts with other vehicles and with the surrounding in-frastructure. To handle these functions, it must incorporate various technologies from different sources. An autonomous car is an example of a Cyber-Physical System, where some of its func-tions are performed by Internet of Things units. Sensors are extensively used in autonomous cars to measure physical quantities; actuators are commanded by controllers to perform appro-priate physical actions. From AEPs we can derive concrete patterns, a structure combining re-lated AEPs is an Entity Solution Frame (ESF). Both sensors and actuators are susceptible to mali-cious attacks due to the large attack surface of the system where they are used. Our work is in-tended to make autonomous cars more secure, which also increases their safety. Our final objec-tive is to build a Security Solution Frame for sensors and actuators of autonomous cars that will facilitate their secure design. A Security Solution Frame is a solution structure that groups to-gether and organizes related security patterns. This article is the first stage of a secure unit that can be used to design not only secure autonomous cars but also any system where sensors and actuators are used. This paper concentrates on AEPs and ESFs for sensors and actuators; that is, on the functional aspects of these devices.

In every agricultural setting, weed seeds can be found in every cubic centimeter of soil. Weed seeds, as a valuable trait underlying the fate of weed populations, exhibit differing levels of seed dormancy, ensuring their survival under uncertain conditions. Seed dormancy is considered as an innate mechanism that constrains germination under suitable conditions that would otherwise stimulate germination of non-dormant seeds. This work provides new insight into changes in germination patterns along the dormant to nondormancy continuum in seeds with physiological dormancy. Notable findings are: (1) germination synchrony can act as a new parameter that quantitatively describes dormancy patterns and subsequently weed population dynamics, (2) germination synchrony is dynamic, suggesting that the more dormancy decreases, the more synchrony is obtainable, (3) after-ripening and stratification can function as a synchronizing agent that regulates germination behavior. Brassica napus showed the most synchronous germination with the value of 3.14, while lower level of germination asynchrony was for Sinapis arvensis, with the asynchrony value of 2.25. After-ripening and stratification can act as a synchronizing factor through decreasing asynchrony level and increasing synchrony. Weed establish a firm relationship between dormancy cycling and germination synchrony patterns, ensuring their survival and reproductive strategies. By germinating in synchrony, which is accompanied by cycling mechanisms, weeds have more opportunities to persist. The synchrony model used in the present study predicts germination behavior and synchrony along the dormant to nondormancy continuum in weed seeds with physiological dormancy, suggesting a useful method for quantification of germination strategies and weed population dynamics.

This short paper demonstrates that the galactic spiral equations developed from ROTASE model can be used to morphologically simulate the phyllotactic spiral-ring patterns of plants. It is also noticed during this project that although the numbers in the Fibonacci sequence dominate the phyllotactic numbers, there are still significant phyllotactic numbers are not in the Fibonacci sequence, however, most of those numbers are well fit into a Fibonacci sibling sequence starting with numbers 0 and 2. Many plants show the phyllotactic number pairs of 10-16, 16-26 and 26-42 from the Fibonacci sibling sequence, which is the second dominated sequence in the phyllotaxis.

Machine learning (ML) is a subdivision of artificial intelligence in which the machine learns from machine-readable data and information. It uses data, learns the pattern and predicts the new outcomes. Its popularity is growing because it helps to understand the trend and provides a solution that can be either a model or a product. Applications of ML algorithms have increased drastically in G.I.S. and remote sensing in recent years. It has a broad range of applications, from developing energy-based models to assessing soil liquefaction to creating a relation between air quality and mortality. Here, in this paper, we discuss the most popular supervised ML models (classification and regression) in G.I.S. and remote sensing. The motivation for writing this paper is that ML models produce higher accuracy than traditional parametric classifiers, especially for complex data with many predictor variables. This paper provides a general overview of some popular supervised non-parametric ML models that can be used in most of the G.I.S. and remote sensing-based projects. We discuss classification (Naïve Bayes (NB), Support Vector Machine (SVM), Random Forest (RF), Decision Trees (DT)) and regression models (Random Forest (RF), Support Vector Machine (SVM), Linear and Non-Linear) here. Therefore, the article can be a guide to those interested in using ML models in their G.I.S. and remote sensing-based projects

B chromosomes (Bs) or supernumerary chromosomes are extra chromosomes in the species karyotype that can vary in their copy number. Bs are widespread. Usually, the Bs of specimens collected from natural populations are involved in studies. We applied another approach analyzing the Bs in animals of laboratory cultures. In this study, three species of the Macrostomum genus that underwent a recent whole-genome duplication (WGD) were involved. In laboratory lines of M. lignano and M. janickei, the frequency of Bs was less than 1%, while in the laboratory culture of M. mirumnovem, it was nearer 30%. Their number in specimens of the culture varied from 1 to 14. Mosaicism on Bs was discovered in parts of these animals. We analyzed the distribution of Bs among the worms of the laboratory cultures during long-term cultivation, the transmission rates of Bs in the progeny obtained from crosses of worms with different numbers of Bs, and from self-fertilized isolated worms. The DNA content of the Bs in M. mirumnovem was analyzed with the chromosomal in situ suppression (CISS) hybridization of microdissected DNA probes derived from A chromosomes (As). Bs mainly consisted of repetitive DNA. The cytogenetic analysis also revealed the divergence and high variation in large metacentric chromosomes (LMs) containing numerous regions enriched for repeats. The possible mechanisms of the appearance and evolution of Bs and LMs in species of the Macrostomum genus were also discussed.

Heart attacks and strokes are one of the leading causes of death in the world today, and heart attacks caused by clogged arteries that carry blood to the heart muscle are a significant part of these strokes. These are caused by the accumulation of fat particles in the walls of the arteries and the reduction of blood flow through it over a long process. The process of fat penetration in the underlying layers of the Artery wall has been the focus of many researchers, and various researches and Simulations have been done on it, in each of them, the effect of specific parameters has been considered. In the present study, the effect of blood flow rate on the flow pattern in a bifurcate artery with two ducts has been investigated using FLUENT software with Computation fluid dynamic Method. The effect of the angle between the two ducts of the Artery on the flow pattern has been investigated.

Over the years, there has been a significant rise in the world's scientific knowledge. However, most of it lacks structure and is often termed as Dark Data. Both humans and expert systems have continually faced difficulty in analyzing and comprehending such overwhelming amounts of information which is crucial in solving several real-world problems. Information and data visualization techniques proffer a promising solution to explore such data by allowing quick comprehension of information, the discovery of emerging trends, identification of relationships and patterns, etc. In this tutorial, we utilize the rich corpus of PubMed comprising of more than 30 million citations from biomedical literature to visually explore and understand the underlying key-insights using various information visualization techniques. With this study, we aim to diminish the limitation of human cognition and perception in handling and examining such large volumes of data by speeding up the process of decision making and pattern recognition and enabling decision-makers to fully understand data insights and make informed decisions.

Many clustering approaches succeed in pattern segmentation in many applications. This unsupervised segmentation should be effective to reduce an expert labelling time: i.e, they must be able to detect the number of patterns and identify them in a sequence or map with the right cuts. Several direct and hierarchical clustering approaches are compared for this task. A divisive spectral clustering architecture with a no-cut criteria is also proposed. This new algorithm achieves promise segmentation of spatial UCI databases and marine time series compared to other approaches.

In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.

Pressure drop and flow pattern of oil-water flows were investigated in a 19 mm ID clear polyvinyl chloride pipe consisting of U-bend with radius of curvature of 100 mm. The range for oil and water superficial velocities tested were and respectively. Measurements were carried out under different flow conditions in a test section that consisted of four different parts: upstream of the bend, at the bend and at two redeveloping flow locations after the bend. The result indicated that the bend had limited influence on downstream flow patterns. However, the shear forces imposed by the bend caused some shift flow pattern transition and bubble characteristics in the redeveloping flow section after the bend relative to develop flow before the bend. Generally, pressure gradient at all the test sections increased with both oil fraction and water superficial velocity and there was a sharp change of pressure gradient profile during phase inversion. The transition point where phase inversion occurred was always within the range of . Pressure losses differed at the various test sections and the difference was strongly linked to the superficial velocity of the phases and the flow pattern. At high mixture velocity, pressure losses at the redeveloping section after the bend were higher than that at the bend and that for fully developed flows. At low mixture velocity, pressure losses at the bend are higher than in the straight sections. Pressure drop generally decreased with level of flow development downstream of the bend.

Resource Description Framework(RDF) is a data representation format of the Semantic Web, and its data volume is growing rapidly. Cloud-based systems provide a rich platform for managing RDF data. However, the distributed environment has performance challenges when it is processing with RDF queries that contain multiple join operations, such as network reshuffle, memory overhead. To get over these challenges, this paper proposed a spark-based RDF query architecture, which is based on Semantic Connection Set (SCS). First of all, this spark-based query architecture adopts the mechanism of re-partitioning class data based on vertical partitioning, which can reduce memory overhead and fast index data. Secondly, a method for generating query plans based on semantic connection sets is proposed in this paper. In addition, statistics and broadcast variable optimization strategies are used to reduce shuffling and data communication costs. The experiment of this paper is based on the latest SPARQLGX on the spark platform RDF system, two synthetic benchmarks are used to evaluate the query. The experiment result illustrates that the proposed approach in this paper is more efficient in data search than SPARQLGX.

Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local Binary Pattern (CLBP). We first divide the image into blocks and then re-divide the blocks into cells. For each cell, we compute CLBP and then concatenate them to describe the texture of the corresponding block. We then train a multi-class Support Vector Machine (SVM) classifier, which classifies each block of image into one of four categories, i.e. Very Low, Low, Medium, and High. We evaluate our technique on the PETS 2009 dataset, and from the experiments, we show to achieve 95% accuracy for the proposed descriptor. We also compare other state-of-the-art texture descriptors and from the experimental results, we show that our proposed method outperforms other state-of-the-art methods.

In this paper, PEN3 electronic nose was used to detect and recognize fresh and moldy apples (inoculated with Penicillium expansum and Aspergillusniger) taken Golden Delicious apples as model subject. Firstly, the apples were divided into two groups: apples only inoculated with different molds (Group A) and mixed apples of inoculated apples with fresh apples (Group B). Then the characteristic gas sensors of the PEN3 electronic nose that were most closely correlated with the flavor information of the moldy apples were optimized and determined, which can simplify the analysis process and improve the accuracy of results. Four pattern recognition methods, including linear discriminant analysis (LDA), backpropagation neural network (BPNN), support vector machines (SVM) and radial basis function neural network (RBFNN), were then applied to analyze the data obtained from the characteristic sensors, respectively, aiming at establishing the prediction model of flavor information and fresh/moldy apples. The results showed that only the gas sensors of W1S, W2S, W5S, W1W and W2W in the PEN3 electronic nose exhibited strong signal response to the flavor information, indicating were most closely correlated with the characteristic flavor of apples and thus the data obtained from these characteristic sensors was used for modeling. The results of the four pattern recognition methods showed that BPNN presented the best prediction performance for the training and validation sets for both the Group A and Group B, with prediction accuracies of 96.29% and 90.00% (Group A), 77.70% and 72.00% (Group B), respectively. Therefore, it first demonstrated that PEN3 electronic nose can not only effectively detect and recognize the fresh and moldy apples, but also can distinguish apples inoculated with different molds.

Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.

Recent advances in recording and real-time analysis of surface electromyographic signals (sEMG) have fostered the use of sEMG human-machine interfaces for controlling personal computers, prostheses of upper limbs, and exoskeletons among others. Despite a relatively high mean performance, sEMG-interfaces still exhibit strong variance in the fidelity of gesture recognition among different users. Here we systematically study the latent factors determining the performance of sEMG-interfaces in synthetic tests and in an arcade game. We show that the degree of muscle cooperation and the amount of the body fatty tissue are the decisive factors in synthetic tests. Our data suggest that these factors can only be adjusted by a long-term training, which promotes fine-tuning of low-level neural circuits driving the muscles. A short-term training has no effect on synthetic tests, but significantly increases the game scoring. This implies that it works at a higher decision-making level, not relevant for synthetic gestures. We propose a procedure that enables quantification of the gestures’ fidelity in a dynamic gaming environment. For each individual subject the approach allows identifying “problematic” gestures that decrease gaming performance. This information can be used for optimizing the training strategy and for adapting the signal processing algorithms to individual users, which could be a way for a qualitative leap in the development of future sEMG-interfaces.

Fisheries and bottom seawater data were collected in July in 2022 and 2023 from 15 sampling stations in the Huanghe River Estuary and adjacent seas in China. The patterns of functional alpha- and beta-diversity of fish communities in this area and their relationship with environmental factors were studied using trait-based analysis. Five functional classifications, which included 16 functional traits, four functional alpha-diversity indices (functional richness, functional evenness, functional divergence, and community-weighted mean), three functional beta-diversity indices (functional beta-diversity and its turnover and nestedness components), and 14 bottom environmental factors were considered. The dominant traits of fish communities were: benthivorous feeding habits, small and front-facing mouths, high trophic level, demersal, anguilliform, low growth coefficient, medium resilience, low vulnerability, and adapted to warm temperate conditions. The dominant migration traits and types of fish eggs varied by year, and fish abundance was the main factor affecting the dominant traits of the communities. The results of multiple regression on distance matrices and variance partitioning analysis indicated that ammonia nitrogen content, total phosphorus content, and pH were the main environmental factors that affected fish functional diversity. The N/P ratio had an upward control effect on fish functional diversity. Our findings also revealed that high pH gradients and distant geographical distances can inhibit trait turnover in fish communities.

As part of the Fabaceae project of northeastern Mexico, today we present the compendium of legumes of the subfamilies Caesalpinioideae, Cercidoideae and Detarioideae from this region. As in our previous work on the Mimosoideae Clade, new nomenclatural changes and retypification of genera of the subfamily Caesalpinioideae are included. Also, based on new scientific information published, the taxonomic changes in new genera, recently segregated from the genus Caesalpinia (Conzattia, Coulteria, Denisophytum, Erythrostemon, Guilandina, Hoffmannseggia, and Pomaria) are included. Based on field work, collection of botanical samples over the past 37 years, and reviewing botanical materials in national and international herbaria, the diversity of legumes of the subfamilies Caesalpinioideae, Cercidoideae, and Detarioideae in northeastern Mexico has been recorded. The subfamily Caesalpinioideae includes two tribes, the tribe Caesalpinieae with 12 genera (Caesalpinia, Ceratonia, Coulteria, Delonix, Denisophytum, Erythrostemon, Gleditsia, Guilandina, Hoffmannseggia, Haematoxylum, Parkinsonia, and Pomaria), and 26 species and the tribe Cassieae, which includes three genera (Cassia, Chamaecrita, and Senna) and 28 species. The subfamily Cercidoideae include two genera (Bauhinia and Cercis), and eight species and the subfamily Detarioideae, includes only one genus and one species (Tamarindus indicus). The total flora of these three subfamilies comprize 18 genera and 63 species, it includes 56 native species and seven exotic ones: Bauhinia variegata, Cassia fistula, Ceratonia siliqua, Delonix regia, Erythrostemon gilliesii, Senna alata, and, Tamarindus indicus. The endemism of both subfamilies includes a total of 20 species and 10 infraspecific categories.

Bactrocera dorsalis Hendel is a highly invasive horticultural pest of major economic importance worldwide. In Burkina Faso, it is one of the main insect pests constraining the mango production and export. Understanding the biology and the genetic dynamics of this insect pest provide cru-cial information for the development of effective control measures. The aim of this study was to understand the distribution, diversity and genetic structure of B. dorsalis in Burkina Faso. Male flies were collected transversally in Burkina Faso and analyzed by PCR using 10 microsatellite markers. The results showed an abundance of B. dorsalis varying from 87 to 2986 flies per trap per day in the different sampling sites. Genetic diversity was high in all sites with an average Shan-non's Information Index (I) of 0.72 per site. Gene flow was high between study populations and ranged from 10.62 to 27.53 number of migrants. Bayesian admixture analysis showed no evi-dence of structure while Discriminant Analysis of Principal Components identified three weakly separated clusters in the population of B. dorsalis in Burkina Faso. The results of this study could be used to optimize the effectiveness of current control interventions and to guide the imple-mentation of new, innovative and sustainable strategies.

A compositional data vector is a special type of multivariate observation in which the elements of the vector are non-negative and sum to a constant, usually taken to be unity. A compositional data does not have zero and only retains relative information. Furthermore, comparisons can only be made between compositional data of the same component. The relevant sample space is the standard simplex. A simplex space is a space that is a generalized form of a triangle. For compositional data, many of the operations defined in Euclidean space are meaningless. Microbiome analyzes have become popular in recent years. Operational Taxonomic Units (OTU) and Amplicon Sequence Variants (ASVs) used in microbiome analysis are one type of compositional data. The microbiome data are counts of different species within a sample and it is compositional. Although there is an order of bacterial abundance within a sample, there is no order of bacterial abundance between samples. Firmicutes and Bacteroidetes, the major phyla in the colon, have been observed in humans worldwide. Gut microbiome analyses often use the Firmicutes/Bacteroidetes ratio and principal coordinates analysis (PCoA). Alpha and beta diversities are used as indicators of bacterial flora diversity. However, misinformation is pervasive in the human microbiome literature and analysis. There is a lot of misunderstanding regarding compositional data and its analysis. An attempt was made to demonstrate how to analyze using the “National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN JMD) (Public Data).” The results showed that PCoA did not work, and principal component analysis (PCA) was useful for analyzing the gut microbiome relative diversity.

This comprehensive article explores the intricate responsibilities of executives leading AI projects within the framework of Federal Directives, specifically Executive Order 14110 and Executive Order 14091. The executive role is dissected, covering aspects such as defining leadership in the AI context, historical perspectives, current trends, and challenges in AI project leadership. The article delves into the significance of Federal Directives, particularly Executive Order 14110, which emphasizes safe, secure, and trustworthy AI development, and Executive Order 14091, focusing on racial equity and support for underserved communities. Key provisions of these orders are outlined, including safe AI development, secure AI implementation, trustworthy AI use, and commitments to racial equity. The article also highlights steps that should guide documenting case studies that align with successful AI projects, showcasing compliance with Executive Orders and positive impacts on communities and organizations. The future outlook focuses on anticipating regulatory changes, adapting to evolving ethical standards, and promoting a culture of continuous improvement within AI projects. The conclusion summarizes executive responsibilities, emphasizing the call to action for ethical and inclusive AI leadership, contributing to the positive evolution of AI technologies for societal well-being.

Parkland contributes economic, social, and ecological benefits worldwide. However, parklands degradation is an encounter to biodiversity loss needs generating information on woody species. This study was aimed to investigate woody species composition, diversity, structure, and management of parklands along Agroecology, and farmers’ wealth status. Multistage sampling technique was employed. Highland Bede Kebele, and midland Durgi Kebele were randomly selected. A total of 60 quadrats with size of 100m x 50m were used for inventory. A total of 276 respondents were used. Species richness, Shannon, Simpson, and evenness diversity indices were subjected to one-way ANOVA, and independent t-test for comparison STATA V. 17.0. Of 31 woody species, (16 families in 26 genera) observed, 26 woody species belonging to 13 families in 22 genera from midland while 18 woody species belonging to 12 families in 16 genera from highland parklands were observed. Species richness 6.8, 3.7; Shannon 1.82, 1.68; Simpson 0.85, 0.73; evenness 0.83, 0.7 were observed in midland, and highland parklands, respectively. Poorly regenerated stands were observed along Agroecology. Pruning, pollarding, coppicing, lopping, cutting, fertilizing, watering were common management practices. In conclusion, woody species diversity, and structure were affected by Agroecology, and socioeconomic factors needing intervention to enhancing woody species conservation.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

We investigated the potential genetic variants using whole exome sequencing (WES) and evalu-ated the disease course using T cell receptor (TCR) repertoire analysis in rheumatoid arthritis (RA). Fourteen patients with RA and five healthy controls (HCs) were enrolled. For patients with RA, only naïve patients were recruited before treatment, and data were collected at baseline and 6 and 12 months after the initiation of disease-modifying antirheumatic drug (DMARD) treatment. Laboratory data and disease parameters were also collected. Genetic variants were detected using WES, and the diversity of the TCR repertoire was assessed using Shannon-Weiner diversity. Some variants were detected by WES, but their clinical significance should be confirmed by further studies. The diversity of the TCR repertoire in patients with RA was lower than that in HCs; however, after DMARD treatment, it increased significantly. The diversity was negatively cor-related with laboratory findings and disease measures with statistical significance. Variants with a potential for RA pathogenesis were identified and the clinical significance of TCR repertoire was evaluated in Korean patients with RA. Further studies are required to confirm the findings of the present study.

Circadian rhythm disruption is increasingly considered an environmental risk factor for the development and exacerbation of inflammatory bowel disease. We have reported in a previous study that nychthemeral dysregulation is associated with an increase in intestinal barrier permeability and inflammation in mice with dextran sulfate sodium (DSS)-induced colitis. To investigate the effect of circadian rhythm disruption on the composition and diversity of the gut microbiota (GM). Sixty male C57BL/6J mice were divided initially to two groups, the shifted group (n=30) exposed to circadian shifts for three months and the non-shifted group (n=30) under a normal light-dark cycle. The mice of the shifted group were cyclically housed for five days under the normal 12:12 hour light-dark cycle followed by another five days under reversed light-dark cycle. At the end of the three months a colitis was induced by 2 % DSS given in the drinking water of 30 mice. Animals were then divided into four groups (n=15 per group), sham group non-shifted (Sham-NS), sham group shifted (Sham-S) and DSS non-shifted (DSS-NS) and DSS shifted (DSS-S). Fecal samples were collected from rectal content to investigate changes in GM composition by DNA extraction followed by high-throughput sequencing of the bacterial 16S rRNA gene. The mouse GM was dominated by three phyla: Firmicutes, Bacteroidetes and Actinobacteria. The Firmicutes/Bacteroidetes ratio decreased in mice with induced colitis. The richness and diversity of the GM were reduced in the colitis group, especially in the group with inverted circadian rhythm. Moreover, GM composition was also modified in the inverted circadian rhythm group, with an increase in Alloprevotella, Turicibacter, Bacteroides and Streptococcus genera. Circadian rhythm inversion exacerbates GM dysbiosis to a less rich and diversified extent in a DSS-induced colitis model. These findings shows a possible interplay between circadian rhythm disruption, GM dynamics, and colitis pathogenesis.

Genetic diversity is the foundation of evolutionary resilience, adaptive potential, and the flourishing vitality of living organisms, serving as the cornerstone for robust ecosystems and the continuous evolution of life on Earth. The landscape of directed evolution, a powerful biotechnological tool inspired by natural evolutionary processes, has undergone a transformative shift propelled by innovative strategies for generating genetic diversity. This shift is fuelled by several factors, encompassing the utilization of advanced toolkits like CRISPR-Cas and base editors, enhanced comprehension of biological mechanisms, cost-effective custom oligo pool synthesis, and the seamless integration of artificial intelligence and automation. This comprehensive review looks into the myriad methodologies employed for constructing gene libraries, both in vitro and in vivo, categorized into three major classes: random mutagenesis, focused mutagenesis, and DNA recombination. The objectives of this review are threefold: firstly, to present a panoramic overview of recent advances in genetic diversity creation, secondly, to inspire novel ideas for further innovation in the genetic diversity generation, and thirdly, to provide a valuable resource for individuals entering the field of directed evolution.

Tigrai region is one of the potential beekeeping areas in Ethiopia, which is endowed with diversified honeybee plant species. However, its honeybee plants are deforested and degraded due to natural and anthropogenic pressures. Area exclosures (AEs) has been practicing for the last three decades restore degraded habitats of the plant species in Ethiopia. Empirical data on the effectiveness of AE is still limited for restoration of honey bee plant species; this study was conducted to assess the roles of AE for species composition, density, and diversity and regeneration status of honeybee floras. Sixty quadrats were installed, 36 in AE and 24 in CGL (communal grazing lands) using a systematic sampling method. The study showed that a total of 42 honey bee plant species belonging to 23 families in AE and 33 species belonging to 17 families in CGL were recorded. The study also indicated a significant increase in the abundance, diversity, regeneration and the structure of the honey bee plant species was found in the AEs. The list presented herein provides a guide to stakeholders in establishing of AE for the foraging resource of honeybee in order to enhance the abundance, diversity and regeneration and structure. Thus, AE has made a significant contribution to solving the shortage of honeybee forages in the beekeeping industry. Therefore, the development of beekeeping is integrated with conservation of natural resources.

Despite advancements in antiretroviral therapy (ART) that reduces the viral load to undetectable levels, viral eradication has not been achieved due to HIV-1 persistence in resting CD4+ T-cells. We, therefore, characterized the tat gene, which is essential for HIV-1 replication, from 20 viro-logically controlled HIV-infected (HIV+) older patients on long-term ART with improved CD4+ T-cell counts. PBMC genomic DNA from HIV+ patients were used to amplify tat gene by PCR fol-lowed by nucleotide sequencing and analysis. Phylogenetic analysis showed that each patient’s tat sequences were confined to their own subtrees and well discriminated from other patients’ sequences. Moreover, there was a low degree of viral heterogeneity and lower estimates of genetic diversity within these patients’ tat sequences. Most patients’ Tat deduced amino acid sequences showed intact open reading frames and maintained the important functional domains for Tat functions, including transactivation, TAR binding and nuclear localization. Furthermore, Tat deduced amino acid sequences showed variation in previously characterized cytotoxic T lym-phocytes (CTL) epitopes, suggesting escape mutants. In conclusion, a low degree of genetic varia-bility and conservation of functional domains and variations in CTL epitopes were the features of tat sequences from 20 HIV+ older patients with undetectable viral load on long-term ART.

Carnivorous waterbirds have been reported to enhance wetlands diversities, control pests, bio-indicators of ecological conditions, and act as indicators of potential disease outbreaks. They also provide important ecosystem services to indigenous communities residing along wetlands. Regardless of their importance, global waterbirds populations are declining. Despite their ecological contribution to wetlands functions and ecosystem services, piscivore waterbirds have been re-ported to compete with piscivorous fish and fishermen. The aim of this study was to compare piscivorous waterbirds species and functional diversity between fish protected areas (FPA) and non-fish protected area (NFPA) in two tributaries of Zambezi River in Namibia. We also measured the degree to which patterns of guild structure between piscivore waterbirds and fish were similar between FPA and non-FPA. Species diversities were determined by calculating the Shannon Diversity Index. We calculated taxonomic diversity, functional diversity and community-based trait diversity indices for each tributary. Generally, species diversities were not significantly different between FPA and NFPA (P > 0.05). However, all functional diversities indices calculated were significantly different between FPA an NFPA (P < 0.05 for all comparisons). This was partly due to food item, weight and movement type that were associated with each site.

In order to explore the genetic diversity of the extremely small population wild plant Habenaria dentata and protect and optimize its wild resources. The genetic diversity of 133 samples from 6 wild populations of H.dentata was analyzed by ISSR molecular marker technique to provide a scientific basis for the screening of improved germplasm resources. The results show that the average number of alleles (Na) was 1.765, the average number of effective alleles (Ne) was 1.424, the average Nei 's gene diversity index (He) was 0.252, the average Shannon information diversity index (I) was 0.381, and the average percentage of polymorphic loci (PPL) was 76.499%. The variation within populations was 77.34%, and the variation between populations was 22.66%. Gene flow (Nm) was 1.705 8, greater than 1. The results of cluster analysis showed that the six populations were mainly divided into four branches and not classified according to geographical location. There was no significant correlation between geographical location and genetic distance between populations (r=0.557, P>0.05). The genetic diversity of H.dentata is high. Among the six wild populations, the genetic diversity of Mulun population is the highest and this population can be used as a key protection unit.

As most prominent plant-associated disease, photosensitization in large herbivores provides a substantial data base to evaluate the conditions under which animals are concerned. The purpose of this meta study was to investigate whether the level of feed plant diversity and feed choice influence the incidence of photosensitization. Case reports from 1900 to 2022 served as database. 113 publications described 178 cases of altogether 12 animal species, most of them being farm animals. 73.6% of the cases originated from three continents: South America, Australia and North-America. Of the 40 phototoxic agents, herbs represented the majority (63.6%). Brachiaria, Froelichia and other four genus were associated in almost 50% of the cases. Usually, animals received feed both of normal quality and in fresh state. Secondary photosensitization was most frequent only when associated with poor feed quality. If the animals had had access to high-diversity feed instead of low-diversity feed, the incidence was 27.5% smaller. If the animals had the choice between various kind of feed, the incidence was even reduced by 56.1%. Horses could select the least, however, suffered mainly from primary photosensitization. We conclude that farmers may prevent photosensitization in husbandry animals by allowing both more feed choice and feed diversity.

We explored the trends and the diversity of the mortality and risk factors of age-standardized cardiovascular diseases (CVD) and cerebrovascular disease (CBD) from 2000 to 2020 in five advanced Asian countries, including China, Japan, Singapore, South Korea, and Taiwan. Data were obtained from the Global Burden of Disease (GBD) report. Overall, the CVD mortality rates decreased gradually in all five Asian countries. Singapore had the highest rates before 2011, but Taiwan replaced Singapore as the nation of the highest mortality rates after 2012. Additionally, South Korea had the highest CBD mortality rates before 2016, while Taiwan experienced a peak in 2011 and remained high thereafter. The absolute difference (AD) and relative difference (RD) for CVD mortality rates showed clear declining trends in all five countries, with South Korea and China displaying the highest reductions, respectively. It is noteworthy that overweight and obesity exhibited an increasing trend in all these five Asian countries, with China demonstrating the highest AD and RD. Except for Taiwan, where a negative association of r=-0.732 was observed, CVD mortality was positively associated with CBD, hypertension, and DM mortality in all other four countries, therefore, further investigation into these relationships are needed.

Phytoseiidae inhabit a wide range of herbs, shrubs and trees. Aesculus hippocastanum is an important ornamental tree in Europe and is likely reservoir of these mites. We therefore assessed the species composition and the spatial and seasonal variability in the abundance of Phytoseiidae in city parks in South Bohemia, Czech Republic. Leaf samples were randomly collected from horse chestnut tree branches at eight sites, five times during the vegetation season in 2013. The mites were collected by washing technique and mounted on slides for identification. In total, 13,903 specimens of phytoseiid mites were found, and eight species were identified: Amblyseius andersoni, Euseius finlandicus, Kampimodromus aberrans, Neoseiulella tiliarum, Phytoseilus macropilis, Paraseiulus talbii, Paraseiulus triporus and Typhlodromus (Typhlodromus) pyri. Paraseiulus talbii and P. macropilis were recorded on the leaves of horse chestnut trees for the first time in the Czech Republic in this study. The predominant species was E. finlandicus (96.25%). The number of mites per compound leaf was, on average, 2.53, 10.40, 23.54, 11.59 and 9.27 on the sampling dates in each month between May and September, respectively. The mite density was significantly affected by the sampling site and date.

The mitochondrial marker, cytochrome oxidase subunits II gene (mtDNA-COII) was employed to assess the genetic structure and diversity of Anopheles funestus, a very important malaria vector in Africa, that adapt and colonize different ecological niches in western Kenya. Mosquitoes were collected using mechanical aspirators in four sites (Bungoma, Port Victoria, Kombewa and Migori) in western Kenya. Following morphological identification, PCR was used to confirm species. The mtDNA-COII gene was amplified, sequenced and analyzed to determine genetic diversity and population structure. A total of 126 (Port Victoria-38, Migori-38, Bungoma-22 and Kombewa-28) sequences of mtDNA-COII were used for population genetic analysis. Anopheles funestus had high haplotype diversity (Hd= 0.97 to 0.98) but low nucleotide diversity (π =0.004 to 0.005). The neutrality test revealed significant (p<0.05) negative Tajima’s D and Fs values indicating population expansion with an excess of low-frequency variation due to evolutionary forces across all sites. No genetic differentiation or structure was observed across the sites (Fst = -0.01) and a high level of gene flow (Gamma St, Nm = 17.99 to 35.22) was observed among the populations. Population expansion suggests the high adaptability of this species to various ecological requirements hence sustaining its vectorial capacity and malaria transmission.

The emergence of multi-drug resistant E. coli is an important matter of increasing considerable concern to global public health. The aim of this study was to investigate the incidence, antibiotic resistance pattern, phylogroups and genetic variation of E. coli isolates from raw milk, vegetable salad and ground meat samples. Methods: Culture-based techniques, Kirby-Bauer disk diffusion susceptibility testing, PCR and RAPD assays were used to determine the incidence rate, antimicrobial resistance pattern, phylogenetic groups and genetic diversity of the E. coli isolates. Results: E. coli isolates were highly resistant to amoxicillin (79.16%), trime-thoprim-sulfamethoxazole (70.83%), amoxicillin-clavulanic acid (62.50%), tetracycline (54.16%), chloramphenicol (54.16%), nitrofurantoin (54.16%), ampicillin (45.83%), streptomycin (45.83%), and kanamycin (33.33%); and completely susceptible to norfloxacin and azithromycin. 70.83% of the isolates were multi-drug resistant. Most E. coli isolates (46%) belonged to phylogroup A. RAPD with UBC245 primer categorized the isolates into 11 clusters. A high level of genetic di-versity was found among the isolates; however, 33.3% of the isolates were grouped in a major cluster (R5). Conclusions: Antibiotic resistance patterns are randomly distributed among the ge-netic clusters. Novel, practical, efficient food safety control and surveillance systems of multi-drug resistant foodborne pathogens are required to control the foodborne pathogen contamina-tion.

The dramatic increased rates of uncontrolled urbanization in various parts of the World have resulted in loss of native species and overall threats to biodiversity. Over the last few decades Saudi Arabia has witnessed a remarkably rapid population growth and unparalleled levels of urbanization, leading to threats to biodiversity. Ants were pitfall-trapped across an urban-rural gradient to evaluate ant assemblage responses to urbanization in Wadi Hanifa, Riyadh, Central Saudi Arabia. Fifteen sampling sites were selected along three different urbanization gradients, each traversing urban, suburban and rural zones. Within each site 10 traps were distributed and operated for 7 consecutive days, at 3-monthly intervals throughout one year. Vegetation, ground cover, and chemical and physical soil variables at sampling sites were analyzed concurrently. Ant abundance, species richness, evenness, and diversity indices of Shannon and Simpson were calculated for each site using PC-ORD to demonstrate diversity patterns along the urbanization gradients. Ant assemblages were assessed by detrended corresponding analysis (DCA), canonical correspondence analysis (CCA), and analysis of similarity (ANOSIM) using PC-ORD. Indicator species analysis was conducted to define representative species along the urbanization gradient. A total of 42 ant species were identified. The diversity parameters were consistent across the urbanization gradient. However, significant differences were observed in the ant assemblages between rural and urban, suburban and urban, but only marginal between rural and suburban. Eleven ant species were identified as indicator species (IV values between 50.7-80.7%). The ant assemblages were influenced by flora, ground cover, and soil variables.

Optical remote sensing can contribute to biodiversity monitoring and species composition mapping in tropical forests. Inferring ecological information from canopy reflectance is complex and data availability suitable to such a task is limiting, which makes simulation tools particularly important in this context. We explored the capability of the 3D radiative transfer model DART to simulate top of canopy reflectance acquired with airborne imaging spectroscopy in complex tropical forest, and to reproduce spectral dissimilarity within and among species, as well as species discrimination based on spectral information. We focused on two factors contributing to these canopy reflectance properties: the horizontal variability in leaf optical properties (LOP) and the fraction of non-photosynthetic vegetation (NPVf). The variability in LOP was induced by changes in leaf pigment content, and defined for each pixel based on a hybrid approach combining radiative transfer modeling and spectral indices. The influence of LOP variability on simulated reflectance was tested by considering variability at species, individual tree crown and pixel level. We incorporated NPVf into simulations following two approaches, either considering NPVf as a part of wood area density in each voxel or using leaf brown pigments. We validated the different scenarios by comparing simulated scenes with experimental airborne imaging spectroscopy using statistical metrics, spectral dissimilarity (within crowns, within species, and among species dissimilarity) and supervised classification for species discrimination. The simulation of NPVf based on leaf brown pigments resulted in the closest match between measured and simulated canopy reflectance. The definition of LOP at pixel level resulted in conservation of the spectral dissimilarity and expected performances for species discrimination. Our simulation framework could contribute to better understand performances for species discrimination and relationship between spectral variations and taxonomic and functional dimensions of biodiversity.

During the 1970s, Tunisian durum wheat landraces were replaced progressively by modern cultivars. These landraces are nowadays maintained by smallholder farmers in some ecological niches and are threatened gradually by extinction resulting on the narrowing of the genetic diversity. This study aims to investigate patterns of phenotypic variability using twelve quantitative traits in a panel of 189 durum wheat landraces and seven checks, based on farmer’s population name attribution and genetic structure. Our results showed high phenotypic variability among and within landraces and checks for the majority of the studied traits. The principal components analysis showed similar grouping using farmers name attribution and genetic structure using K = 6, which confirmed the identification of a new gene pool in the oases of Tunisia, represented by the sub-population Jenah Zarzoura and the robustness and high relationships between phenotypic and genome-wide genetic structure using DArTseq method. These findings will enhance the conservation efforts of these landraces and their use in breeding efforts at national and international levels to adapt to dry conditions.

Whereas bait and pitfall trappings are two of the most commonly used techniques for sampling ant assemblages, they have not been properly compared in temperate open habitats. In this study, taking advantage of a large-scale project of heathland restoration (3 sites along the French Atlantic Coast forming a north-south gradient), we evaluated the relative efficiency of these two methods for assessing both taxonomic and functional diversities of ants while accounting for a north south diversity gradient. Ants were collected and identified to species level, and 6 traits related to morphology, behavior (including diet, dispersal and maximum foraging distance) and social life (colony size and dominance type) were attributed to all 23 species. Both observed and estimated species were significantly higher in pitfalls compared to spatially pair-matched bait traps. Functional diversity followed the same pattern, with consistent results for both community weighted mean (CWM) and Rao’s quadratic entropy. Taxonomic and functional diversities from pitfall assemblages increased from North to South locations, following a frequently reported pattern at larger spatial scales. Bait traps can hardly be considered a complementary method to pitfall traps for sampling ants in open temperate habitats, as it appears basically redundant with pitfall traps at least on maritime cliff-tops of the East-Atlantic coast.