Insect herbivory is a critical top-down force structuring plant communities, and quantifying the factors that mediate damage caused by herbivores is fundamental to understanding biodiversity. As herbivory is the result of numerous ecological and evolutionary processes, including complex population dynamics and the evolution of plant defense, it has been difficult to predict variation in herbivory across meaningful spatial scales. In the present work, we characterized patterns of herbivory on plants in a speciose and abundant tropical understory genus (Piper) across forests spanning 44° of latitude in the Neotropics. We modeled the effects of geography, climate, resource availability, species richness and top-down pressure from parasitoids on the mean, dispersion, and skew of generalist and specialist herbivory. By examining these multiple moments of the distribution of herbivory, we were able to determine factors that increase biologically meaningful herbivory at the upper ends of its distribution. The strongest pattern that emerged at a large spatial scale was a roughly two-fold increase in herbivory in humid relative to seasonal forests. Site level variables such as latitude, seasonality and maximum Piper richness explained variation in herbivory at the local scale (plot level) better for communities of Piper congeners than for a single species. Predictors that varied between local communities, such as resource availability and diversity, best explained the distribution of herbivory within sites, dampening any broad patterns across latitude and climate and demonstrating why generalizations about gradients in herbivory have been elusive. The estimated population means, skew, and dispersion of herbivory respond differently to abiotic and biotic factors, demonstrating the need for careful studies to explore the distributions of herbivory and their effects on forest diversity.

One of the current priorities of the new Common Agriculture Policy (CAP) is to overcome the serious environmental prob- lems raised by intensive agriculture. Despite the steps for- ward guaranteed by new technologies and innovations (e.g., IoT, precision agriculture), the availability of real operational tools, helping the member states to fulfill the high require- ments and expectations of the new CAP, is still lacking. To fill this gap, in the H2020 LandSupport project, the web- based best practice tool was developed to identify, on-the- fly, optimized agronomic solutions. The core of the tool is the ARMOSA process-based model, which dynamically sim- ulates several combinations of cropping systems, crops, ni- trogen fertilization rates, tillage solutions and crop residues managements for a specific region of interest. To identify the optimized solutions, it provides a synthetic “Best Practice in- dex”, which combines the production, nitrate leaching and SOC_change, according to the end-user dynamic requests. The tool was implemented for three case studies: March- feld Region in Austria, Zala County in Hungary, Campania Region in Italy, which are representative of a variety of dif- ferent pedoclimatic conditions. In the present work, three possible uses are shown to i) maximize the crop production; ii) evaluate the use of different crops and related practices; iii) evaluate the best practices in the nitrate vulnerable zones. The tool offers a close representation of actual and optimized cropping systems, with the possibility of further applications in other regional case studies, and in tailored scenarios, in which users enter their own input data.

The land problem is the key to the implementation of the Rural Revitalization Strategy, and the land suitability evaluation is the basis for the renovation and classification of the rural idle residential. Taking Yuzhong County in the Loess Hilly region of Longzhong, China as the research area, this study integrated multi-source data, such as rural residential ownership confirmation data, survey data of land use, high-resolution remote sensing images, and field research to construct an idle residential identification matrix. According to the evaluation results of ecological protection suitability, agricultural production suitability, and construction and development suitability, we followed the principle of “ecology first, agriculture second, after construction and setting,” and realize renovation zoning of rural residents through the advantage type identification method. The results show that the waste in rural residential is serious, and there are significant phenomena of “one household with two houses” and “one household with multiple houses.” The renovation potential of 1700 idle rural residentials patches is 117.52 hm 2. In addition, there are significant spatial differences in the suitability of rural residents in Yuzhong County. The rational guidance and planning layout of rural residential renovation can be realized by identifying the type of renovation by the spatial combination of different land uses in terms of ecological protection, agricultural production, and construction and development suitability. This can provide an important decision-making basis for the rational utilization of rural idle residential and national land-space planning. Finally, the rural residential renovation should be guided by the national land space planning. The government should do a good job in the rural residential renovation planning, formulate a scientific plan for the renovation, relocation, and reuse of rural “hollow houses.” Adapting to local conditions, the government should gradually adjust and optimize the layout of rural residential land, improve the comprehensive utilization efficiency of rural land, stimulate the vitality of rural land resources, and promote the rural revitalization and the improvement of rural living environment.

Environmental factors interact with biological and genetic factors influencing the development and well-being of an organism. The interest to better understand the role of environment on behavior and physiology led to the development of animal models of environmental manipulations. Environmental Enrichment (EE), an environmental condition that allows cognitive and sensory stimulation as well as social interaction, improves cognitive function, reduces anxiety and depressive-like behavior, and promotes neuroplasticity. In addition, it exerts protection against neurodegenerative disorders, cognitive aging and deficits aggravated by stressful experiences. Given the beneficial effects of EE on brain and behavior, preclinical studies focus on its protective role as an alternative, non-invasive manipulation, to help an organism to cope better with stress. A valid, reliable and effective animal model of chronic stress that enhances anxiety and depression-like behavior is the Chronic Unpredictable Mild Stress (CUMS). The variety of stressors and the unpredictability in the time and sequence of exposure to prevent habituation, render CUMS an ethologically relevant model. CUMS has been associated with dysregulation of the Hypothalamic-Pituitary-Adrenal axis, elevation in the basal levels of stress hormones, reduction in brain volume, dendritic atrophy and alterations in markers of synaptic plasticity. Although numerous studies have underlined the compensatory role of EE against the negative effects of various chronic stress regimens (e.g., restraint, social isolation), research concerning the interaction between EE and CUMS is sparse. The purpose of the current systematic review is to present up-to-date research findings regarding the protective role of EE against the negative effects of CUMS.

Spatial Modeling of land suitability helps in right deployment of a crop to its suitable locations. The present study was aimed at developing a GIS and MCDA (multi criteria decision analysis) integrated spatial model to assess land suitability for oil palm cultivation under rainfed conditions of India. The most critical parameters (factors) influencing oil palm cultivation under rainfed conditions were identifiedand weights were assigned through rank sum method. Spatial data for these parameters has been collected at district level from standard sources. Thematic rasters developed in GIS with defined sub-classes. Through MCDA, digital suitability map developed and suitable areas (three classes) were delineated, in ArcGIS 10.3.Accordingly, 10.478 million ha (Mha) area was identified as suitable for rainfed cultivation of oil palm in the country.Further, to facilitate expansion of oil palm cultivation to sustainable locations alone, the identified suitable area was restricted to existing eight land use land cover (LULC) classes only. After restricting this suitable area to only selected LULC classes, 4.237 Mha area was identified as suitable in total (0.95 Mha- highly suitable, 1.08 Mha- moderately suitable and 2.21 Mha- marginally suitable). Most of the highly suitable areas were found in Kerala and Andaman & Nicobar Islands. This information acts as a decision tool for policy makers in planning oil palm expansion in the country and presently it is being followed by Indian government to allocate oil palm crop to most suitable areas for achieving sustainable production of the crop in the country.

On 19 September 2021, a new monogenetic volcano (Tajogaite) erupted on the island of La Palma (Canary Islands, Spain). After 86 days of strombolian eruption, with emissions of volcanic material, a pyroclastic cone 200 m high and 800 m in diameter was formed. Successive lava flows descended the western slopes and reached the sea on 29 September. On descending the coastal cliffs and entering the sea, the lava flows formed two lava deltas of 75 and 5 ha, on the submarine island shelf, backed by fossilized coastal cliffs. This work presents an approach, using comparative and numerical methods, to estimate the geoheritage value and support the conservation of a new volcanic landscape in an island territory with high anthropic pressure on land uses. In a first phase, a cartographic inventory was made of all the volcanic formations similar to the new volcano in the geological domain of the Canary Islands. In a second phase, their representativeness (A), rarity (R), diversity (D), integrity (I) and observability (O) was quantitatively measured by means of dimensional estimators. The results obtained show that the new volcano presents a geological value of the first order in the context of the Canary Islands, which is one of the most prominent hot-spot archipelago worldwide. Its value is based above all on its high conservation state with respect to the similar volcanoes in the Canary Islands. The high mismatch found between the intrinsic geological value and the environmental protection of this area, justifies the development and application of urgent basic guidelines for its protection, as well as the promotion of geotourism as opposed to alternative land uses.

We present a framework to model and provide numerical evidence for compartmentalization in the yeast endoplasmic reticulum. Measurement data is collected and an optimal control problem is formulated as a regularized inverse problem. To our knowledge, this is the first attempt in the literature to introduce a PDE-constrained optimization formulation to study the kinetics of fluorescently labeled molecules in budding yeast. Optimality conditions are derived and a gradient descent algorithm allows accurate estimation of unknown key parameters in different cellular compartments. For the first time, the numerical results support the barrier index theory suggesting the presence of a physical diffusion barrier that compartmentalizes the endoplasmic reticulum by limiting protein exchange between the mother and its growing bud. We report several numerical experiments on real data and geometry, with the aim of illustrating the accuracy and efficiency of the method. Furthermore, a relationship between the size ratio of mother and bud compartments and the barrier index ratio is provided.

Diquat (DQ), an effective herbicide, has begun to threaten human health with the surge in the number of poisonings every year. Here, we present a powerful signature to improve the prognostic discrimination for patients with DQ poisoning. In this study, a total of 26 patients with acute DQ poisoning were enrolled. The median survival time in the death group was 43 hours. Undoubtedly, plasma concentration (PC), the blood cells (WBC), neutrophils (NE), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and serum creatinine (Scr) in the death group were significantly higher and negatively correlated with survival time. And COX regression analysis suggested that PC, WBC, NE, ALT and Scr were the risk factors for poisoning death of DQ poisoning. Furthermore, risk factors were further developed as a robust signature (PC&Scr) to predict the prognosis of DQ poisoning. Survival analysis as well as time-dependent ROC analysis showed powerful predictive ability of prognostic signature in patients with DQ poisoning. A nomogram containing risk factors and signature could accurately predict the 2-day survival probability of individual DQ poisoning. The study shows that this signature with a powerful ability to predict DQ poisoning outcomes deserves popularizing in clinical practice.

Objectives: To investigate the prevalence and risks factors associated with electrode migration in cochlear implant (CI) recipients. Design: Retrospective cohort study of all CIs performed between 1 January 2018-1 August 2021 in a single tertiary adult and paediatric cochlear implant centre in the UK. Main outcome measures: The primary aim is to determine the prevalence of electrode migration, based on comparing intraoperative surgeon report and results of a routine plain X-ray performed 2 weeks after surgery. Electrode migration is defined as the detection of movement of 2 or more electrodes out of the cochlea from time of surgery. Multivariate analysis was performed to investigate risk factors including preoperative factors and intraoperative factors that might predispose to migration. Results: 465 patients, having 516 distinct surgery sessions, with 628 implants were analyzed. Electrode migration occurred in 11.5% of all implants. Pre-existing cochlear abnormality was an independent associated risk factor for electrode migration (OR:3.40<1.20-9.62> p=0.021). Demographics, surgical technique, usage of a precurved electrode, CSF leak, surgeon seniority and intraoperative telemetry did not influence risk of migration. There were 5 implants which migrated later than 2 weeks, median: 263days, for which head injury was a common precipitating factor. There was some difference between different lateral wall electrodes Conclusion: Electrode migration in the early postoperative period is a common occurrence and is more likely in implant recipients with obstructed or malformed cochleae. Keywords : Cochlear implants, Electrode migration, Risk factors, Cochlear abnormalities, Postoperative X-ray

The study of the eukaryotic fraction of the microbiota using a metabarcoding approach is usually hindered by the high host to eukaryotic microbiota DNA ratio in samples. Indeed, the 18S rRNA gene is very similar for both the host and its eukaryotic communities, leading to a preferential amplification of the predominant host DNA when using universal primers. Multiple approaches have been developed to reduce host DNA amplification. One method is based on elongation arrest blocking primers, oligonucleotides modified with a C3 Spacer that stops the advancement of the DNA polymerase at non-conserved regions of a target gene. In this paper, we successfully developed and tested species-specific elongation arrest blocking primers to block the Flag cichlid, Mesonauta festivus, 18S rRNA SSU. Our elongation arrest blocking primers significantly reduced the amount of host DNA amplicons by 66 %. In addition to reducing the amount of sequencing wasted, the blocking primers increased the detectability of potentially dangerous parasitic taxa in fish gut, highlighting the potential of the method for parasitic screening. For instance, we discovered a case of infection by the parasitic ciliate Nyctotherus sp. and detected the presence of a parasitic Trematode and an Amoebae. While our data support the possibility of achieving a complete inhibition of host DNA amplification using elongation arrest blocking primers, more research is still required. Still, there is a need for the development and additional testing of protocols to study the eukaryotic diversity present in fish gut, a slow-growing field of study in comparison to its prokaryotic counterpart.

A document by Danny Croghan. Click on the document to view its contents.

In an intelligent IoT environment, an edge server needs to retrieve data from end devices to train the deep neural network deployed at edge. In order to achieve the higher training performance with limited resource, we propose a Bandit-based in-network training data retrieval scheme(Bandit-TDRetrieval). Specifically, we formulate data retrieval from end devices with a multi-armed bandit (MAB) model. A sequence of lever pulls of the arms indicate the options to retrieve date from different end devices, and follows a binomial distribution. To identify the relation between this binomial distribution and the rewards through continuous data retrieval from the corresponding devices, Thompson sampling is used. According to this relation, we design a training data retrieval paradigm in IoT to maximum the rewards to retrieve training data for learning at edge. Finally, the evaluation is carried out on the simulation platform, which can effectively improve the training efficiency of the deep neural networks at edge.

Drug treatment in elderly patients is a challenge for healthcare systems. This challenge is exacerbated by age-related changes in pharmacokinetics and pharmacodynamics, multimorbidity, frailty and cognitive impairment. Moreover, old patients are commonly exposed to polypharmacy, leading to increased risk of drug interactions, adverse drug reactions, and higher costs for the healthcare systems. Thus, the complex task of prescribing medications to older polymedicated patients encourages the use of Clinical Decision Support Systems (CDSS). This paper evaluates the CDSS miniQ for identifying potentially inappropriate prescribing in older adults with polypharmacy and to assesses the usability and acceptability of miniQ in health care professionals, patients, and caregivers. It describes how useful is CDSS miniQ system for Primary Care physicians, as well as for patients and their caregivers to know their medications. The discussion emphasizes how this system is useful to improve the prescribing process and reduce errors.

Aim: To evaluate the properties of the measurement of the Global Evaluation of Medication Adherence Instrument (GEMA) among patients with chronic diseases. Methods: A methodological study was conducted in public hospital of the state of São Paulo, Brazil. The adherence to anticoagulants as well as the International Normalized Ratio (INR) was assessed on 127 patients. Besides GEMA, two other instruments were used to assess adherence: the Morisky Medication Adherence Scale–8 (MMAS-8) and the Measurement of Adhesion to Treatments (MAT). Results: The GEMA presented a satisfactory level of specificity (0.76) to identify adherents among those with a stable INR, low sensitivity (0.43) for the identification of non-adherents among those with an unstable INR, and a Positive Predictive Value of 0.70. Positive and weak to moderate correlations were observed between the proportion of doses assessed with GEMA and the scores on the MMAS-8 (r=0.26 and r=0.22, respectively) and the MAT (r=0.22 and r=0.30, respectively). Conclusion: The GEMA presented good practicality, acceptability, and evidence of specificity regarding the stability of the INR. The validity of the construct was partially supported by the relationship with self - reported measures of adherence.

Over six million individuals have died as a result of the infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that causes Covid-19. The first COVID-19 vaccines were introduced to the public in 2020 through emergency authorizations. This study aims to uncover the fears and misconceptions behind the hesitation or refusal of taking the COVID-19 vaccine in Syria. Methods: Through a nationwide cross-sectional study, a convenience sample of 10006 participants who were at least 18 years old and living in Syria participated in a validated questionnaire during the period between January and May 2022 Results: The majority of recruited individuals were female (n= 6048; 60.4%) from the (18-24) age group (n= 5908; 59%). We recorded 5811 (58%) participants who still have fears and anxieties about the COVID-19 vaccine. The main concerns about vaccines were the rapid development of vaccines (41.4%), fears of blood clots (37.9%), the fears of common side effects (35.2%), and allergic reactions (26.5%). Conclusion: The COVID-19 vaccine is considered the most promising measure for controlling the spread of infection. The success of this policy will depend on the rate of global acceptance of the vaccine. High variability in vaccine acceptance and high vaccine hesitancy can affect the efforts to terminate the COVID-19 pandemic. Addressing the barriers associated with the acceptance of COVID-19 vaccination will be the cornerstone to achieving maximum vaccination coverage. The most common reasons behind refusing the vaccine in Syria were fear of side effects, followed by fears, general concerns, manufacturing-related reasons, and conspiracy belief

Sensorimotor atypicalities are common in Autism Spectrum Disorder (ASD) and are often evident prior to classical ASD symptoms. Despite evidence of differences in neural processing during imitation in ASD, research on integrity of basic sensorimotor processing is surprisingly sparce. To address this gap in the literature, here we examined basic sensorimotor processing in autism by analyzing EEG data recorded from a large sample of children and adolescents while they performed an audio-visual speeded reaction time task. Using response-locked signal averaging, we investigated the neural processes associated with execution of a cued movement in a large sample of children and adolescents with ASD (n=84) and without ASD (n=84). Analyses focused on motor related brain responses that are well-characterized in adults: the late berichtsheft potential, the motor potential, and the reafferent potential. Group differences were examined in data parsed by age (6-9 years, 9-12 years, 12-15 years), sensory cue preceding the response (auditory, visual, bi-sensory audio-visual), and reaction time quartile. Overall, the data revealed robust sensorimotor neural responses in ASD. Nevertheless, subtle sensorimotor atypicalities were present in autistic children across all parcellations, and these differences were most prominent in the youngest group of children (age 6-9). Future studies focused on younger children are needed to understand if differences in basic sensorimotor processing are more prominent earlier in development in autism.

Understanding large-scale patterns of biodiversity and their drivers remains significant in biogeography. Cherries species (Prunus subgenus Cerasus, Rosaceae) are economically and ecologically important in ecosystems and human agricultural activities. However, the mechanisms underlying patterns of species richness-environment relationship in Cerasus remain poorly understood. We collected and filtered worldwide specimen data to map the species richness of Cerasus at the global scale. The map of Cerasus species richness was created using 21043 reliable recorded specimens. The center of Cerasus diversity was determined using spatial cluster analysis. Stepwise regression analysis was carried out using five groups of 21 environmental variables and an integrated model was included to assess the impact of the overall environment. We calibrated each of the four integrated models and used them to predict the global Cerasus species richness and that of the other continents. Our results revealed that Cerasus species have two centers of diversity (the southwest of China and Honshu Island in Japan) with differing environmental variables influencing the distribution patterns of these two centers. In the southwest of China, hydrothermal conditions are the main driving factor while in Japan, habitat heterogeneity is the main driving factor. The relationship between the abundance of the Cerasus and the various groups of factors generally supported both the productivity and the habitat heterogeneity hypothesis. However, these hypotheses did not fully explain the Cerasus species richness pattern, indicating that other factors such as historical environment, topography, and human activities likely played a role in pattern formation. The high level of habitat heterogeneity and better hydrothermal conditions may have played an important role in the establishment of its globally consistent richness-climate relationship. Our results can provide valuable information for the classification, and conservation of Cerasus natural resources, as well as contribute to furthering our understanding of biogeography at a global scale.

Aim: Crested Ibis is an endangered animal with extremely high ecological, humanistic and scientific value. However, there is still a survival predicament due to increasingly shrinking foraging grounds, serious interference by human behavior, and increased habitat requirements. The geographical environment is significant for Crested Ibis behavior patterns analysis and habitat protection. The spatial and temporal trajectory contains the habitat location and period information, a vital record of the Crested Ibis’ habits, and the basis of all research. Nevertheless, there are only a handful of studies on the missing trajectory data and fusing multiple sources of environmental data research methods. Location: Henan Province, Shaanxi Province, China Methods: The LSTM model was adopted to supplement the missing trajectory data, and cluster mining was performed. Using Spatial and temporal trajectory and geographic data, we developed a Random Forest model to predict the habitat of the Crested Ibis and assessed the habitat suitability in Luoshan Country. Results: Based on trajectory, we identified that the Crested Ibis distribution pattern is characterized by high altitude and proximity to woodland and rivers. And the habitat dependence on the village implicates human agricultural activities positively impacting its reproduction. The Random Forest model with high fitting accuracy (R2 = 84.9%)is superior, and the influence factors were gained, finding that 68% of the area is suitable in Luoshan County. Main conclusions: The trajectory complement model and the habitat prediction model are developed to obtain the Crested Ibis’ behavioral patterns and habitat distribution. This paper provides a complete method for analyzing Crested Ibis’ spatial and temporal trajectory by fusing multi-source data, which is crucial for protecting the survival and reproduction of Crested Ibis.

It was suggested that processing subject relative clauses (SRCs) are universally easier than processing object relative clauses (ORCs) based on the studies carried out in head-initial languages such as English, and German. However, studies carried out in head-final languages such as Chinese and Basque refuted this claim. Turkish is also a head-final language. Existing relative clause processing literature in Turkish is based solely on behavioural metrics. Even though an ORC processing disadvantage was suggested for Turkish, the results were not conclusive. Therefore, we aimed to investigate the neural dynamics of relative clause processing in Turkish. We asked 14 native Turkish speakers to answer Yes/No questions about 24 sentences each containing either SRC or ORC while their prefrontal hemodynamic activity was recorded with fNIRS. Our findings revealed hemodynamic activity in the lateral portions of the left prefrontal cortex in both conditions. However, hemodynamic activity was more widespread in prefrontal regions for ORC than SRC. Even though the behavioural metrics failed to produce a significant difference between SRC and ORC conditions, direct ORC>SRC contrast revealed significant activity in left and right DLPFC, which are known to be involved in language processing and conflict monitoring related processes, respectively. Our findings indicate that processing ORCs are more difficult and require further prefrontal resources than processing SRCs in Turkish, thus refuting the head-directionality based explanations of relative clause processing asymmetries.

There are more and more studies on the detection method of 3-chloro-1,2-propanediol fatty acid esters (3-MCPD esters) at present. By comparing these methods for the determination of 3-MCPD esters. Indirect methods, which determine total amount of 3-MCPD after hydrolysis of the esters, have an advantage over direct methods. The existing indirect methods, however, may yield unreliable results or require long hours of alkaline methanolysis. In contrast, the Indirect enzymatic hydrolysis method has mild conditions and more accurate results. In this study, we developed a reliable and rapid indirect method for determinations of 3-MCPD esters. 3-MCPD esters was enzymatized to 3-MCPD by indirect enzymatic hydrolysis method, and the conditions of enzymatic hydrolysis were optimized, the content of 3-MCPD after enzymatic hydrolysis was detected by gas chromatography-mass spectrometry (GC-MS) and the yield was calculated. Finally, the optimum conditions for enzymatic hydrolysis of 3-MCPD esters were determined. According to the optimal enzymatic hydrolysis condition, the contents of 3-MCPD esters in four food oils were determined. The method is simple and sensitive, and can meet the requirement of 3-MCPD esters detection in general oils.

Handwritten recognition (HR) remains a challenging process in various real-world applications. Tamil handwritten text recognition involves the recognition of text in scanned images. Recognition of handwritten Tamil characters is a tedious process because of the differences in sizes, style and orientation angle. Prior studies concentrated on character-level segmentation and each character was subsequently classified. Segmentation is then used, first at the word level and subsequently at the line level. The recently developed machine learning (ML) and deep learning (DL) approaches can be utilized for Tamil HCR. With this motivation, this paper presents an end-to-end deep learning-enabled Tamil handwritten document recognition (ETEDL-THDR) model. The ETEDL-THDR paragraph text recognition can be accomplished by the use of two modules such as line segmentation and line recognition. Initially, the ETEDL-THDR model enables the improvement of the quality of the input images by the use of the median filtering (MF) technique. To create meaningful regions, further line and character segmentation activities are performed. Additionally, a deep convolutional neural network-based MobileNet approach was applied to derive feature vectors. At last, the water strider optimization (WSO) algorithm with a bidirectional gated recurrent unit (BiGRU) model is applied to recognize Tamil characters. An extensive experimental analysis of the ETEDL-THDR model is carried out and the results showed that the ETEDL-THDR model performed better than more recent methodologies with maximum accuracy of 98.48%, precision of 98.38%, a sensitivity of 97.98%, specificity of 98.27%, and F-measure of 98.35%.

The deformation characteristics of fractured rock masses and the acoustic emission (AE) (microseismic) characteristics of internal crack propagation are important research topics to help evaluate and predict the stability of rock masses. In this study, rock-like models of the same scale but with different degrees of hardness were prepared by changing the ratio of rock-like materials, and in each model, a fracture of the same scale was prefabricated at the same position. Uniaxial compressive deformation and AE tests were conducted on these rock-like models. Based on the stress–strain relationship during the compressive deformation of the models, the compressive deformation process could be divided into four stages: stage I is the medium compaction stage; stage II is the elastic deformation stage; stage III is the crack propagation stage; stage IV is the model failure stage. The deformation test results showed that the variation trends in the maximum principal strain with time at measuring points on both sides of the prefabricated fractures were the same. The maximum principal strain peaks at these measuring points showed an opposite variation trend with the model hardness. The deflection angle range of the local principal strain at the passive loading end increased with the increase in the degree of hardness, while that at the active loading end did not change significantly. The relative displacement rate changed significantly mainly in the medium compaction stage; the harder the rock-like model, the lower the peak relative displacement rate. Based on the observation results of the AE test of the rock-like models, the ring-down count vs time curve could be divided into three stages: initial, growth and stable stages. The initial stage corresponded to deformation stages I and II. In this stage, the ring-down count of the hard rock-like model showed little variation, and the cumulative ring-down counts increased gradually. The growth stage corresponded to deformation stage III, where the ring-down count increased sharply, and the harder the rock-like model, the higher the growth rate of the cumulative ring-down counts. The stable stage corresponded to deformation stage IV, where the distribution of the ring-down count of the rock-like model with a relatively higher hardness was sparse, and the cumulative ring-down counts were either stable or increased steadily. Corresponding to the medium compaction stage (stage I) and the crack propagation stage (stage III) of the rock-like model, with the increase in the hardness of the rock-like model, the frequency bandwidth of the peak frequency distribution of the AE signals of the models tended to narrow. Corresponding to the elastic deformation stage (stage II), with the change in the hardness, the frequency bandwidth of the peak frequency distribution did not change significantly. The above test results provide an experimental basis for studying the influence of rock-like model hardness and prefabricated fractures on the deformation process of model medium and fracture development.

Background: In the first-line treatment of BTCs, XELOX has shown comparable clinical efficacy and safety to GEMOX, with fewer visits and better treatment management. Our study aims to investigate the cost-effectiveness of XELOX and GEMOX as the first-line therapy for BTCs from the perspective of the United States healthcare systems and provides valuable suggestions for clinical drug treatment decisions. Methods: A Markov model was developed using the Phase 3 randomized clinical trial (ClinicalTrials.gov number, NCT01470443) to evaluate the cost-effectiveness of XELOX and GEMOX. Quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were used as the primary outcomes of the model. Using univariate and probabilistic sensitivity analyses to assess the uncertainty. Results: The QALYs for the XELOX and GEMOX groups were 0.66 and 0.54, respectively. The additional cost of XELOX treatment was US$493.30 in the United States and ICER was US $4333.28/QALY, which was far below the threshold of willingness to pay (US$50,000 /QALY). The XELOX therapy was confirmed as a stable economic advantage by sensitivity analysis in the United States. Conclusions: XELOX, compared with GEMOX, is a more cost-effective treatment as the first-line treatment for advanced BTCs from the perspective of the United States health service system.

Josephson junction circuits, such as superconducting quantum interference devices (SQUIDs) and single-flux-quantum (SFQ) circuits, have been successfully applied in both analog and digital electronic domains. Their variables of macroscopic quantum phases are distinct from that of the normal resistor-inductor-capacitor (RLC) circuits; their flux-quantization law (FQL) involving magnetic flux couplings are not well supported by the conventional circuit diagrams. This article presents a general network equation to unify the analyses of both normal RLC circuits and superconducting Josephson junction circuits. This network equation uses the flux contributions of noninductive components as variables to unify the definitions of Josephson junctions and normal RLC elements, and unify the closed-loop law for both superconducting and non-superconducting loops. It simplifies the analysis of the electric circuits with various magnetic flux inputs, and is easily understood by electronic engineers who are trained with the conventional circuit theories.