Head Tail Research Articles

KBPT: knowledge-based prompt tuning for zero-shot relation triplet extraction

Knowledge representation is increasingly recognized as an effective method for information extraction. Nevertheless, numerous studies have disregarded its potential applications in the zero-shot setting. In this article, a novel framework, called knowledge-based prompt tuning for zero-shot relation triplet extraction (KBPT), was developed, founded on external ontology knowledge. This framework serves as a catalyst for exploring relation triplet extraction (RTE) methods within low-resource scenarios, warranting further scrutiny. Zero-shot setting RTE aims to extract multiple triplets that consist of head entities, tail entities, and relation labels from an input sentence, where the extracted relation labels are those that do not exist in the training set. To address the data scarcity problem in zero-shot RTE, a technique was introduced to synthesize training samples by prompting language models to generate structured texts. Specifically, this involves integrating language model prompts with structured text methodologies to create a structured prompt template. This template draws upon relation labels and ontology knowledge to generate synthetic training examples. The incorporation of external ontological knowledge enriches the semantic representation within the prompt template, enhancing its effectiveness. Further, a multiple triplets decoding (MTD) algorithm was developed to overcome the challenge of extracting multiple relation triplets from a sentence. To bridge the gap between knowledge and text, a collective training method was established to jointly optimize embedding representations. The proposed model is model-agnostic and can be applied to various PLMs. Exhaustive experiments on four public datasets with zero-shot settings were conducted to demonstrate the effectiveness of the proposed method. Compared to the baseline models, KBPT demonstrated enhancements of up to 14.65% and 24.19% in F1 score on the Wiki-ZSL and TACRED-Revisit datasets, respectively. Moreover, the proposed model achieved better performance compared with the current state-of-the-art (SOTA) model in terms of F1 score, precision-recall (P–R) curves and AUC. The code is available at https://Github.com/Phevos75/KBPT.

Isolation and Biological Characteristics of a Novel Phage and Its Application to Control Vibrio Parahaemolyticus in Shellfish Meat.

Vibrio parahaemolyticus is a common foodborne pathogenic bacterium. With the overuse of antibiotics, an increasing proportion of drug-resistant strains are emerging, which puts enormous pressure on public health. In this study, a V. parahaemolyticus-specific phage, VP41s3, was isolated. The head length, width, and tail length of the phage were 77.7 nm, 72.2 nm, and 17.5 nm, respectively. It remained active in the temperature range of 30-50°C and pH range of 4-11. The lytic curve of phage VP41s3 showed that the host bacteria did not grow until 11 h under phage treatment at MOI of 1000, indicating that the phage had good bacteriostatic ability. When it was added to shellfish contaminated with V. parahaemolyticus (15°C, 48 h), the number of bacteria in the experimental group was 2.11 log10 CFU/mL lower than that in the control group at 24 h. Furthermore, genomic characterization and phylogenetic analysis indicated that phage VP41s3 was a new member of the Podoviridae family. The genome contained 50 open reading frames (ORFs), in which the ORF19 (thymidine kinase) was an enzyme involved in the pyrimidine salvage pathway, which might lead to the accelerated DNA synthesis efficiency after phage entered into host cells. This study not only contributed to the improvement of phage database and the development of beneficial phage resources but also revealed the potential application of phage VP41s3 in food hygiene and safety.

Comparison of the genotoxicity of propofol and desflurane using the comet assay in the lymphocytes of patients who underwent lumbar discectomy: A randomized trial.

To compare the genotoxic effects of desflurane and propofol using comet assay in patients undergoing elective discectomy surgery. This was a randomized controlled study. Patients who underwent elective lumbar discectomy under general anesthesia with propofol or desflurane were included in the study. Venous blood samples were obtained at 4 different time points: 5 minutes before anesthesia induction (T1), 2 hours after the start of anesthesia (T2), the first day after surgery (T3), and the fifth day following surgery (T4). Deoxyribonucleic acid damage in lymphocytes was assessed via the comet assay. A total of 30 patients, 15 in each group, were included in the analysis. The groups were similar in terms of age and gender distribution. There were no significant differences in demographics, duration of surgery, total remifentanil consumption, and total rocuronium bromide consumption. The comet assay revealed that head length, head intensity, tail intensity, tail moment at T1 were similar in the desflurane and propofol groups. Head length, tail length and tail moment measured in the desflurane group at T4 were significantly higher compared to the propofol group. Tail lengths of the desflurane group at T1, T2 and T3 were significantly higher than the corresponding values in the propofol group. Propofol and desflurane do not appear to induce DNA damage in lymphocytes. However, when the quantitative data were compared, it was determined that propofol had relatively lower genotoxic potential than desflurane.ClinicalTrials.gov Reg. No.: NCT05185167.

Protocolo de adquisición de imágenes y medición de la elasticidad pancreática mediante elastografía por onda de cizallamiento bidimensional (2D-SWE) transabdominal

IntroductionTransabdominal ultrasound (TU) pancreatic 2D-SWE elastography is a developing technique that needs to be protocolized. ObjectivesEstablish a protocol for image acquisition and measurement of TU pancreatic - 2D-SWE elastography and estimate the minimum number of measurements to be performed. Materials and methodsTen measurements of pancreatic elasticity were taken in healthy volunteers using TU-2D-SWE, following a strict protocol for image acquisition and measurement. ResultsThe 70% of the participants were women, with an average age, weight, and BMI of 49.5±15.7 years, 65.9±11.9kg, and 24.5±4.2kg/m2, respectively. Measurements were taken from the body (70%), tail (16.7%), and pancreatic head (13.3%). The median mean velocity and elasticity were 1.46±0.25cm/sec and 6.46±2.87KPa, respectively. The ROI depth was 4.12±1cm and the SP-ROI distance was 5.2mm on average. There were no statistically significant differences between the 10 measurements. The reliability analysis of the measurements showed high internal consistency and repeatability. Taking 5-6 measurements ensured high concordance with the ten reference measurements. The measurements were significantly lower when the SP-ROI values were intermediate (0.3-0.6cm). The measurement accuracy was higher when performed at a depth less than 4.8cm. ConclusionTo measure pancreatic elasticity using TU-2D-SWE, we propose a strict protocol for image acquisition and measurement, taking a minimum of 5 measurements in the best visualized and accessible pancreatic portion, and preferably at a depth of less than 4.8cm.

Mitigating biases in long-tailed recognition via semantic-guided feature transfer

Dealing with significant class imbalance poses a significant challenge in various real-world applications, particularly when the accurate classification and generalization of minority classes are of crucial. One key factor that results in model biases is the inadequate representation of intra-class diversity in samples from tail classes. To tackle this challenge, transfer learning strategies have emerged as a viable approach to promote the data distribution of tail classes by transferring feature learned from head classes. However, existing methods often assume that transferability exists between any head class and tail class, and randomly transfer information during training, which can be problematic when the head and tail classes have uncorrelated semantics. To tackle this problem, we propose a novel feature transfer strategy to promote the learning of discriminative representations for tail classes. Firstly, we compute the semantic similarity in a hybrid manner by combining local visual features and global semantic features. Secondly, we utilize the Gaussian mixture model to represent each class with multiple and anisotropic prototypes, which helps us fit the actual distribution accurately. We then carry out distribution-aware head-to-tail feature transfer, leveraging an optimization objective that can derive a computationally efficient closed-form upper bound. This procedure mitigates representation biases in the feature space and achieves state-of-the-art results on CIFAR100-LT, ImageNet-LT, and iNaturalist long-tailed benchmarks.

REACT: Relation Extraction Method Based on Entity Attention Network and Cascade Binary Tagging Framework

With the development of the Internet, vast amounts of text information are being generated constantly. Methods for extracting the valuable parts from this information have become an important research field. Relation extraction aims to identify entities and the relations between them from text, helping computers better understand textual information. Currently, the field of relation extraction faces various challenges, particularly in addressing the relation overlapping problem. The main difficulties are as follows: (1) Traditional methods of relation extraction have limitations and lack the ability to handle the relation overlapping problem, requiring a redesign. (2) Relation extraction models are easily disturbed by noise from words with weak relevance to the relation extraction task, leading to difficulties in correctly identifying entities and their relations. In this paper, we propose the Relation extraction method based on the Entity Attention network and Cascade binary Tagging framework (REACT). We decompose the relation extraction task into two subtasks: head entity identification and tail entity and relation identification. REACT first identifies the head entity and then identifies all possible tail entities that can be paired with the head entity, as well as all possible relations. With this architecture, the model can handle the relation overlapping problem. In order to reduce the interference of words in the text that are not related to the head entity or relation extraction task and improve the accuracy of identifying the tail entities and relations, we designed an entity attention network. To demonstrate the effectiveness of REACT, we construct a high-quality Chinese dataset and conduct a large number of experiments on this dataset. The experimental results fully confirm the effectiveness of REACT, showing its significant advantages in handling the relation overlapping problem compared to current other methods.

A DQN-based memetic algorithm for energy-efficient job shop scheduling problem with integrated limited AGVs

AGVs have gained significant popularity in various industries. However, the existing literature rarely considers the integrated scheduling of production and logistics on the workshop due to the NP-hard property of both machine scheduling and AGV scheduling. The energy-efficient job shop scheduling problem with limited AGVs is investigated in this paper. A multi-objective memetic algorithm with deep Q-network (DQNMMA) is proposed to minimize the makespan and total energy consumption. In DQNMMA, ten features are selected to describe the current state of the population. This enables the DQN to dynamically adjust the crossover probability according to the population evolution. Formulas for calculating the head length and tail length of each node in the disjunctive graph model are presented for the first time to enable fast and accurate access to the critical paths. Building upon the analysis of critical paths, four problem properties are developed as the foundation for designing six neighborhood operators. Then, a property-based variable neighborhood search strategy is proposed to enhance the exploration capability of the algorithm. Numerous experimental results demonstrate that the proposed approaches can effectively enhance the performance of the algorithm, especially in solving large-scale problems. The comparative analysis with three other state-of-the-art multi-objective algorithms confirms the superiority and effectiveness of the proposed DQNMMA.

Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation

In partial label learning (PLL), each instance is associated with a set of candidate labels, among which only one is correct. The traditional PLL almost all implicitly assume that the distribution of the classes is balanced. However, in real-world applications, the distribution of the classes is imbalanced or long-tailed, leading to the long-tailed partial label learning problem. The previous methods solve this problem mainly by ameliorating the ability to learn in the tail classes, which will sacrifice the performance of the head classes. While keeping the performance of the head classes may degrade the performance of the tail classes. Therefore, in this paper, we construct two classifiers, i.e., a head classifier for keeping the performance of dominant classes and a tail classifier for improving the performance of the tail classes. Then, we propose a classifier weight estimation module to automatically estimate the shot belongingness (head class or tail class) of the samples and allocate the weights for the head classifier and tail classifier when making prediction. This cooperation improves the prediction ability for both the head classes and the tail classes. The experiments on the benchmarks demonstrate the proposed approach improves the accuracy of the SOTA methods by a substantial margin. Code and data are available at: https://github.com/pruirui/HTC-LTPLL.

Statistical tool for the estimation of body weight of lactating cows from 2D photographs

Estimating the body weights of animals is an arduous task in livestock management. However, it is a vital tool in developing suitable breeding programmes,calculating the nutritional requirements, determining pharmaceutical doses of drugs and assessing feed conversion efficiency and carcass quality. In this study, we made an attempt to predict the bodyweights of lactating cows using images from various angles. Seventeen lactating cows from the University Livestock Farm and Fodder Research Station, Mannuthy, were selected randomly. Different body measurements of the animals were obtained manually and photographs of the lateral, rear, and dorsal views were taken using the demo version of the CAD-KAS measure-pictures 1.0 software. The surface area was estimated using the body length along the back on the midline from the withers to the croup and the maximum stomach width from the dorsal view photographs. A stepwise multiple linear regression model was used to predict the body weight of the animals. A regression equation fitted using the surface area and perpendicular length between the Tail Head above and the plane in level with the ventral line of the abdomen below yielded an R2 of 90.5 percent. This study suggests that models built using measurements retrieved from digital image analysis techniques can be used as a promising tool for predicting the body weight of animals. Keywords: Cattle, body weight, digital image analysis, multiple linear regression

Heart Rate and Acceleration Dynamics during Swim-Fitness and Stress Challenge Tests in Yellowtail Kingfish (Seriola lalandi).

The yellowtail kingfish is a highly active and fast-growing marine fish with promising potential for aquaculture. In this study, essential insights were gained into the energy economy of this species by heart rate and acceleration logging during a swim-fitness test and a subsequent stress challenge test. Oxygen consumption values of the 600-800 g fish, when swimming in the range of 0.2 up to 1 m·s-1, were high-between 550 and 800 mg·kg-1·h-1-and the heart rate values-up to 228 bpm-were even among the highest ever measured for fishes. When swimming at these increasing speeds, their heart rate increased from 126 up to 162 bpm, and acceleration increased from 11 up to 26 milli-g. When exposed to four sequential steps of increasing stress load, the decreasing peaks of acceleration (baseline values of 12 to peaks of 26, 19 and 15 milli-g) indicated anticipatory behavior, but the heart rate increases (110 up to 138-144 bpm) remained similar. During the fourth step, when fish were also chased, peaking values of 186 bpm and 44 milli-g were measured. Oxygen consumption and heart rate increased with swimming speed and was well reflected by increases in tail beat and head width frequencies. Only when swimming steadily near the optimal swimming speed were these parameters strongly correlated.

Characterization of ES10 lytic bacteriophage isolated from hospital waste against multidrug-resistant uropathogenic E. coli.

Escherichia coli is the major causative agent of urinary tract infections worldwide and the emergence of multi-drug resistant determinants among clinical isolates necessitates the development of novel therapeutic agents. Lytic bacteriophages efficiently kill specific bacteria and seems promising approach in controlling infections caused by multi-drug resistant pathogens. This study aimed the isolation and detailed characterization of lytic bacteriophage designated as ES10 capable of lysing multidrug-resistant uropathogenic E. coli. ES10 had icosahedral head and non-contractile tail and genome size was 48,315 base pairs long encoding 74 proteins. Antibiotics resistance, virulence and lysogenic cycle associated genes were not found in ES10 phage genome. Morphological and whole genome analysis of ES10 phage showed that ES10 is the member of Drexlerviridae. Latent time of ES10 was 30 min, burst size was 90, and optimal multiplicity of infection was 1. ES10 was stable in human blood and subsequently caused 99.34% reduction of host bacteria. Calcium chloride shortened the adsorption time and latency period of ES10 and significantly inhibited biofilm formation of host bacteria. ES10 caused 99.84% reduction of host bacteria from contaminated fomites. ES10 phage possesses potential to be utilized in standard phage therapy.

Lack of CCDC146, a ubiquitous centriole and microtubule-associated protein, leads to non-syndromic male infertility in human and mouse

From a cohort of 167 infertile patients suffering from multiple morphological abnormalities of the flagellum (MMAF), pathogenic bi-allelic mutations were identified in the CCDC146 gene. In somatic cells, CCDC146 is located at the centrosome and at multiple microtubule-related organelles during mitotic division, suggesting that it is a microtubule-associated protein (MAP). To decipher the molecular pathogenesis of infertility associated with CCDC146 mutations, a Ccdc146 knock-out (KO) mouse line was created. KO male mice were infertile, and sperm exhibited a phenotype identical to CCDC146 mutated patients. CCDC146 expression starts during late spermiogenesis. In the spermatozoon, the protein is conserved but is not localized to centrioles, unlike in somatic cells, rather it is present in the axoneme at the level of microtubule doublets. Expansion microscopy associated with the use of the detergent sarkosyl to solubilize microtubule doublets suggests that the protein may be a microtubule inner protein (MIP). At the subcellular level, the absence of CCDC146 impacted all microtubule-based organelles such as the manchette, the head–tail coupling apparatus (HTCA), and the axoneme. Through this study, a new genetic cause of infertility and a new factor in the formation and/or structure of the sperm axoneme were characterized.

Asymmetric Learning for Graph Neural Network based Link Prediction

Link prediction is a fundamental problem in many graph-based applications, such as protein-protein interaction prediction. Recently, graph neural network (GNN) has been widely used for link prediction. However, existing GNN-based link prediction (GNN-LP) methods suffer from scalability problem during training for large-scale graphs, which has received little attention from researchers. In this paper, we first analyze the computation complexity of existing GNN-LP methods, revealing that one reason for the scalability problem stems from their symmetric learning strategy in applying the same class of GNN models to learn representation for both head nodes and tail nodes. We then propose a novel method, called a sym m etric l earning (AML), for GNN-LP. More specifically, AML applies a GNN model to learn head node representation while applying a multi-layer perceptron (MLP) model to learn tail node representation. To the best of our knowledge, AML is the first GNN-LP method to adopt an asymmetric learning strategy for node representation learning. Furthermore, we design a novel model architecture and apply a row-wise mini-batch sampling strategy to ensure promising model accuracy and training efficiency for AML. Experiments on three real large-scale datasets show that AML is 1.7×∼7.3× faster in training than baselines with a symmetric learning strategy while having almost no accuracy loss.

Enhancing Heterogeneous Knowledge Graph Completion with a Novel GAT-based Approach

Knowledge graphs (KGs) play a vital role in enhancing search results and recommendation systems. With the rapid increase in the size of KGs, they are becoming inaccurate and incomplete. This problem can be solved by the KG completion methods, of which graph attention network (GAT)-based methods stand out because of their superior performance. However, existing GAT-based KG completion methods often suffer from overfitting issues when dealing with heterogeneous KGs, primarily due to the unbalanced number of samples. Additionally, these methods demonstrate poor performance in predicting the tail (head) entity that shares the same relation and head (tail) entity with others. To solve these problems, we propose GATH, a novel GAT -based method designed for H eterogeneous KGs. GATH incorporates two separate attention network modules that work synergistically to predict the missing entities. We also introduce novel encoding and feature transformation approaches, enabling the robust performance of GATH in scenarios with imbalanced samples. Comprehensive experiments are conducted to evaluate GATH’s performance. Compared with the existing state-of-the-art GAT-based model on Hits@10 and MRR metrics, our model improves performance by 5.2% and 5.2% on the FB15K-237 dataset and by 4.5% and 14.6% on the WN18RR dataset, respectively.

Fine-tuning activation specificity of G-protein-coupled receptors via automated path searching

Physics-based simulation methods can grant atomistic insights into the molecular origin of the function of biomolecules. However, the potential of such approaches has been hindered by their low efficiency, including in the design of selective agonists where simulations of myriad protein-ligand combinations are necessary. Here, we describe an automated input-free path searching protocol that offers (within 14 d using Graphics Processing Unit servers) a minimum free energy path (MFEP) defined in high-dimension configurational space for activating sphingosine-1-phosphate receptors (S1PRs) by arbitrary ligands. The free energy distributions along the MFEP for four distinct ligands and three S1PRs reached a remarkable agreement with Bioluminescence Resonance Energy Transfer (BRET) measurements of G-protein dissociation. In particular, the revealed transition state structures pointed out toward two S1PR3 residues F263/I284, that dictate the preference of existing agonists CBP307 and BAF312 on S1PR1/5. Swapping these residues between S1PR1 and S1PR3 reversed their response to the two agonists in BRET assays. These results inspired us to design improved agonists with both strong polar head and bulky hydrophobic tail for higher selectivity on S1PR1. Through merely three in silico iterations, our tool predicted a unique compound scaffold. BRET assays confirmed that both chiral forms activate S1PR1 at nanomolar concentration, 1 to 2 orders of magnitude less than those for S1PR3/5. Collectively, these results signify the promise of our approach in fine agonist design for G-protein-coupled receptors.

Characterization of a new Pseudomonas aeruginosa Queuovirinae bacteriophage.

The ESKAPEE pathogen Pseudomonas aeruginosa is a common cause of chronic wound and cystic fibrosis lung infections, as well as acute burn and nosocomial infections. Many of these infections are recalcitrant to conventional antibiotic therapies due to both traditional antibiotic resistance mechanisms and antimicrobial tolerance. Recent successes with bacteriophage (phage) therapy to treat chronic human P. aeruginosa infections have led to a renewed interest in isolating and characterizing new P. aeruginosa phages. Here, we isolated and characterized a new lytic phage (termed PIP, pili-infecting phage) capable of infecting P. aeruginosa PA14. PIP is a tailed phage with an icosahedral head and flexible tail containing a genome that is 57,462 bp in length. Phylogenetic analysis reveals that PIP belongs to the subfamily Queuovirinae and genus Nipunavirus but is highly divergent in gene content from known Nipunaviruses. By isolating and characterizing a P. aeruginosa strain that spontaneously evolved resistance to PIP, we show that the receptor for PIP is Type IV pili. In summary, we isolated a new P. aeruginosa phage species with a unique genome, thus increasing the diversity of phages known to infect this important human pathogen.IMPORTANCEThe opportunistic pathogen Pseudomonas aeruginosa causes both acute and chronic human infections. These infections are notoriously difficult to treat due to both antibiotic resistance and antibiotic tolerance. The increasing frequency of antibiotic failure in P. aeruginosa infections has led scientists to explore other treatment options, including bacteriophage (phage) therapy. To this end, there has been a significant effort to identify new Pseudomonas phages. Here, we isolated and characterized a bacteriophage (termed PIP, pili-infecting phage) that infects P. aeruginosa PA14. Examination of the PIP genome revealed that this phage represents a new species in the subclass Queuovirinae. The isolation and characterization of spontaneous PA14 mutants that are resistant to PIP infection revealed Type IV pili as the PIP receptor. Ultimately, this study characterizes a new species of Pseudomonas phage, thus enhancing the known diversity of phages that infect this important pathogen.

Surfactant‐Templated Synthesis of High‐Performance Noble Metal Electrocatalysts: A Case of Dioctadecyldimethylammonium Chloride

Mesoscopic structures of noble metal (NM) nanomaterials are important parameters that remarkably affect physicochemical properties and electrocatalytic performances. To date, various synthesis strategies have been proposed to prepare NM nanomaterials with well‐defined mesoscopic structures. Specifically, amphiphilic surfactants that chemically composed of hydrophobic tail(s) and hydrophilic head(s) have been utilized as functional templates to precisely engineer mesoscopic structures of NM nanomaterials and further optimize their electrochemical performance. Compared with traditional surfactants, dioctadecyldimethylammonium chloride (DODAC) is a functional amphiphilic surfactant that can assemble into vesical and cylinder micelles and thus template precise synthesis of NM nanomaterials with various advanced structures. In this review, recent developments in DODAC‐templated synthesis of high‐performance NM electrocatalysts with a specific focus on the findings in the group are presented. Three kinds of advanced NM mesoscopic structures, including one‐dimensional (1D) nanowires, three‐dimensional (3D) mesoporous nanospheres (MSs), and sophisticated hollow/asymmetric MSs, are described in detail. Meanwhile, the applications in various electrocatalytic reactions are presented to highlight high activity, selectivity, and stability of NM electrocatalysts. This review provides some insights into both synthesis and application exploration of high‐performance NM electrocatalysts by templated synthesis of amphiphilic surfactants.

Ameliorative Activities of Morus and Jamun against Cr Induced Andro-Hepatic Anomalies

Chromium (Cr) is a vital micronutrient for sugar metabolism while its unauthorized use may agonize health fatalities. This study was conducted about the novelty about exposure of hexavalent chromium (Cr+6) histopatholgical potentials along with Mulberry Fruit Extract and Jamun Fruit Extract to define the ameliorative aptitude. The histological finding in Cr exposure specify; cessation of testicular seminiferous tubules (ST), annihilation of smooth muscles in basement membrane, Leydig’s cell and spermatids. The ST have halted spermatogenesis, with irregular boundary and dead spermatogonia and Leydig’s cells are disorganized. The sperm head cross sectional area (CSA), tail length and middle piece diameter (p ≤ 0.001) significantly reduced while there is significant elevation of hepatocytes nuclei size, central vein CSA and mean width of Sinusoidal Spaces as compared to control. The protuberant marks of steatosis, fibrosis, dehydration and atrophy were nullified by designated fruit extracts and their possible bio-chelating effects was obvious due to the presence of anthocyanin, β-sitosterol and phytochemicals. The given results specify that hexavalent Cr induce andro-hepatic anomalies when it is freely used without scientific authentication. Cr+6 as food additives in coloring rice and local sweets should be prohibited while bio-products of Morus and Jamun can be recommended and sponsored for traditional medicines.

Sexual dimorphism and ecomorphology of the Berthold’s bush anole (Polychrus gutturosus) in Costa Rica

Abstract Morphological variation present within a species is the result of sexual or natural selection and determines the ecological relationships (i.e., ecomorphology) and the degree of sexual dimorphism. For most lizard species, either males or females are the larger sex, suggesting that selection operates differently on each sex. Thus, differences in morphology can determine the habitat use made by males and females. Here we use the Berthold’s bush anole (Polychrus gutturosus), a rare arboreal, diurnal lizard, to examine whether morphological and ecological measures differ among sexes and whether such potential differences emerge as a result of resource partitioning. We measured the morphology of wild individuals from one population and from preserved specimens collected in Costa Rica. We collected data on nine morphological measurements, nocturnal body and air temperatures, and sleeping perch height. We measured 45 wild individuals (22 males and 23 females) and 17 preserved specimens (6 males and 11 females). We found a female-biased body size, and male-biased tail length, head dimensions, and limb lengths. We also observed differences between males and females in body color and the size and shape of femoral pores, although these differences require quantification. We did not find sex differences in sleeping perch height or nocturnal body temperature. Our results demonstrate that resource partitioning does not explain differences among sexes, and that female-biased body size in P. gutturosus might reflect selection operating on increased fecundity.

Amphiphilic Azo-Functionalized Polyhedral Oligomeric Silsesquioxane; Synthesis and Photo-Switched Efficient Phase Transfer via Host-Guest Encapsulation.

A new amphiphilic azo-functionalized polyhedral oligomeric silsesquioxane (POSS) derivative was synthesized by functionalizing octa(3-aminopropyl)silsesquioxane (OAS-POSS) with 4-((4-(dodecyloxy)phenyl)diazenyl)benzoic acid, affording a hydrophilic amino POSS head and hydrophobic dodecyl tail with a diphenyl-azo connector. Prepared amphiphilic azo-functionalized POSS (azo-POSS) exhibited high ability for encapsulation and transferring cationic dyes into the organic phase by vigorously mixing with aqueous solutions of each dye. The photo-controlled encapsulating properties of the synthesized phase transfer reagent was studied using cationic dyes, such as methylene blue (MB), crystal violet (CV) and thymol blue in acidic conditions. Results showed more than 95 % encapsulation of MB. However, no considerable encapsulation was shown in the case of anionic dyes such as eriochrome black T (EBT) and thymol blue in alkaline solutions. By trans/cis isomerization of the azo moiety of the phase transfer reagent by UV irradiation (365 nm), the amount of dye encapsulation was decreased, which could be attributed to the formation of cis isomer that led to the folding of the dodecyl alkyl tail on the POSS moiety, and therefore prevent to lay the 3-aminopropyl moieties of POSS head to the water/DCM interface to adsorb and encapsulate MB molecules.