Sensation seeking (SS) is a psychobiological personality trait characterized by an individual’s propensity to engage in various forms of risk-taking behavior. The Brief Sensation Seeking Scale (BSSS-8) is a widely used instrument for assessing SS that has been translated into several languages. However, only outdated and non-validated questionnaires have been used to measure SS in the Slovenian population. The aim of this study was to translate and psychometrically validate the Slovenian version of the BSSS-8. A total of 363 participants aged between 14 and 65 years completed the translated BSSS-8 and the questionnaire on drug abuse. The scale demonstrated good reliability (Cronbach’s α=0.81) and a unidimensional factorial structure, as revealed by confirmatory factor analysis (CFA). The multigroup CFA showed gender-specific measurement invariance. In the nomological network, SS was positively associated with drug-related variables. The Slovenian version of the BSSS-8 scale is a short and simple instrument to assess SS for research and epidemiological purposes.

The work presents a mathematical model of a thermogravimetric curve for the growth and simultaneous sublimation of scale on a metal or alloy surface. Reduction of the reaction area as a result of the formation of oxides of alloying elements (for obtaining the basic oxide) is considered for the alloy. For metals, the case where this area is increased as a result of powder metal crushing is also considered. The equations that were obtained are employed to explain the kinetic curves of the mass change of the samples.

The Principle of Indifference (“PI”: the simplest non-informative prior in Bayesian probability) has been shown to lead to paradoxes since Bertrand (1889). Von Mises (1928) introduced the “Wine/Water Paradox” as a resonant example of a “Bertrand paradox”, and which has been presented as demonstrating that the PI must be rejected. We now resolve these paradoxes by a Maximum Entropy (MaxEnt) treatment of the PI that also includes information provided by Benford’s “Law of Anomalous Numbers” (1938). We show that the PI should be understood to represent a family of informationally-identical MaxEnt solutions; each solution being identified with its own explicitly justified boundary condition. In particular, our solution of the Wine/Water Paradox exploits Benford’s Law to construct a non-uniform distribution representing the universal constraint of scale invariance, which is a physical consequence of the Second Law of Thermodynamics.

BACKGROUND. The aims of this study was to compare differences in daytime sleepiness between genders and qualification levels in a cohort university Chinese soccer player under 0 Covid policy restrictions in the urban area of Shanghai. METHODS. 491 questionnaires of Epworth Sleepiness Scales (ESS) were compiled online by males and females Soccer Students (SS), Semi-professional players (SP) and professional players (PP) during the ongoing measures of Shanghai lockdown. ANOVA was performed for players levels and gender. RESULTS. Significant differences were found between the 3 levels and between males and females. PP showed a very low score in the ESS (5,97) well below the threshold of 8, while SS and SP showed an ESS score above the threshold. Female showed higher scores than males. CONCLUSIONS. This study present the first data on sleepiness in Chinese soccer players of different level of qualification in a lockdown condition. Professional players has been less affected by lockdown measures than SS and SP. We can hypothesize the reasons resides in the more ordered lifestyle of PP in comparison to SS and SP, which mitigated the effects of the lockdown. Measures to improve sleep in females’ soccer player should be adopted.

The level of technological development of any civilization can be gaged in large part by the amount of energy they produce for their use, but also encompasses that civilization’s stewardship of their home world. Following the Kardashev definition, a Type I civilization is able to store and use all the energy available on its planet. In this study, we develop a model based on Carl Sagan’s K formula and use this model to analyze the consumption and energy supply of the three most important energy sources: fossil fuels (e.g., coal, oil, natural gas, crude, NGL and feedstocks), nuclear energy and renewable energy. We also consider environmental limitations suggested by United Nations Framework Convention on Climate Change, the International Energy Agency, and those specific to our calculations to predict when humanity will reach the level of a Kardashev scale Type I civilization.

Carton detection is an important technique in the automatic logistics system and can be applied to many applications such as the stacking and unstacking of cartons, the unloading of cartons in the containers. However, there is no public large-scale carton dataset for the research community to train and evaluate the carton detection models up to now, which hinders the development of carton detection. In this paper, we present a large-scale carton dataset named Stacked Carton Dataset (SCD) with the goal of advancing the state-of-the-art in carton detection. Images are collected from the Internet and several warehouses, and objects are labeled using per-instance segmentation for precise localization. There are total of 250,000 instance masks from 16,136 images. Naturelly, a suite of benchmarks are established with several popular detectors. In addition, we design a carton detector based on RetinaNet by embedding our proposed Offset Prediction between Classification and Localization module (OPCL) and Boundary Guided Supervision module (BGS). OPCL alleviates the imbalance problem between classification and localization quality which boosts AP by 3.1%∼4.7% on SCD at the model level while BGS guides the detector to pay more attention to boundary information of cartons and decouple repeated carton textures at the task level. To demonstrate the generalization of OPCL to other datasets, we conduct extensive experiments on MS COCO and PASCAL VOC. The improvements of AP on MS COCO and PASCAL VOC are 1.8%∼2.2% and 3.4%∼4.3% respectively. Source dataset is available here.

In this work, we derive the spectral efficiency, secrecy outage probability, and bit error rate of a communication system assisted by a large intelligent surface (LIS). We consider a single-antenna user and an array of antennas at the transmitter side and the possibility of a direct link between transmitter and receiver. Additionally, there is a single-antenna eavesdropper with a direct link to the transmitter, which is modeled as a Nakagami-m distributed fading coefficient. The channels from transmitter to the LIS and from the LIS to the user may or may not have the line-of-sight (LoS) and are modeled by the Nakagami- m distribution. Moreover, we assume that the LIS elements perform non-ideal phase cancellation leading to a residual phase error that assumes a Von Mises distribution. We show that the resulting channel can be accurately approximated by a Gamma distribution whose parameters are analytically estimated using the moments of the equivalent signal-to-noise ratio. We also provide an upper bound for the error probability for M-QAM modulations. With the derived formulas, we analyze the effect of the strength of the LoS link by varying the Nakagami parameter, m.

There is an increasing trend that Unmanned Combat Air Vehicles (UCAVs) are employed to complete different combat missions in modern wars. This paper investigates a UCAV routing problem, which simultaneously considers the decisions for the configuration of weapons carried by the UCAV subject to its capacity and the allocation of weapons to the targets subject to their destroying requirements. An integer linear programming model is developed to formulate the problem. An adaptive large neighborhood search (ALNS) heuristic is proposed to solve the problem, in which seven neighborhood structures are designed and employed. Randomly generated instances covering the small, medium and large sizes are used to test the proposed ALNS algorithm. CPLEX is also utilized to solve the small-size instances, whose results are compared with that obtained by the ALNS algorithm. And the extensive experimental results confirm the effectiveness and superiority of the proposed ALNS algorithm.

Although the Geriatric Depression Scale (GDS) is a well-established instrument for the assessment of depressive symptoms in older adults, this has not been validated specifically for Portuguese cognitively impaired persons. The objective of this study was to analyze the psychometric properties of two Portuguese versions of the GDS (GDS-27 and GDS-15) in a Portuguese mild-to-moderate cognitively impaired sample. Clinicians assessed for major depressive disorder and cognitive functioning in 117 participants with mild to moderate cognitive decline (76.9% female, Mage = 83.66 years). The internal consistency of GDS-27 and GDS-15 were 0.874 and 0.812, respectively. There was a significant correlation between GDS-27 and GDS-15 with Beck Depression Inventory-II GDS-27: rho = 0.738, p < 0.001; GDS-15: rho = 0.760, p < 0.001), suggesting good validity. A cutoff point of 15/16 in GDS-27 and 8/9 in GDS-15 resulted in identification of persons with depression (GDS-27: sensitivity 100%, specificity 63%; GDS-15: sensitivity 90%, specificity 62%). Overall, the GDS-27 and GDS-15 are reliable and valid instruments for the assessment of depression in Portuguese-speaking cognitively impaired persons.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wavefunction just prior to the entrance of ‘gravitons’ to a small region of space-time prior to a nonsingular start to the universe. We compare this to a solution worked out using Klauder Enhanced quantization, for the same given problem. The solution of the first Cosmological Constant problem relies upon the geometry of the multiverse generalization of CCC cosmology which is explained in this paper. The second solution, used involves Klauder enhanced quantization. We look at energy given by our methods and compare and contrast it with the negative energy of the Rosen model for a mini sub universe and estimate GW frequencies

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

The reagents and raw materials used, as well as the products obtained (bio-oil, reaction condensates, polyols and sugar phases) were characterized by elemental analysis, infrared spectroscopy, thermogravimetry and high performance liquid chromatography with mass spectrometry. The heating value of the bio-oils is higher than that of the original biomass (higher heating value of Eucalyptus sawdust bio-oil 29 MJ/kg versus 19.5 MJ/kg of the original Eucalyptus sawdust). The analyses of the bio-oils allowed to identify the presence of high added-value compounds, such as levulinic acid and furfural. Finally, a study of the accelerated aging of the liquefied biomass showed that the biofuel density increases with the storage time due to the occurrence of repolymerization reactions.

We utilize how Weber in 1961 initiated the process of quantization of early universe fields to the problem of what may be emitted at the mouth of a wormhole. While the wormhole models are well developed, there is as of yet no consensus as to how, say GW or other signals from a wormhole mouth could be quantized, or made to be in adherence to a procedure Weber cribbed from Feynman, in 1961. In addition, we utilize an approximation for the Hubble parameter parameterized from Temperature using Sarkar’s H ~ Temperature relations, as given in the text . Finally after doing this we go to the Energy as E also ~ Temperature, and from there use E (energy) as ~ signal frequency. This gives us an idea of how to estimate frequency generated at the mouth of a wormhole.

Objective: The goal of this study was to analyse the attitudes and perceptions of emergency and mental health nurses through the validation of the SM-GIBED scale in specialised care in Spain on alcoholics and other drug-dependent patients. Design and Setting: This cross-sectional study was developed using the Spanish hospital version of the Seaman-Mannello scale to denominate the SM-GIBED scale. Participants: 170 Emergency and Mental Health Nursing from five Spanish Hospitals. Intervention: Self-administered questionnaire to analiyse the perceptions and attitudes about the drug addict and the alcoholic. Primary and Secondary Outcome Measures: A descriptive and inferential analysis of the study variables was carried out. A psychometric analysis was performed to validate the scale. Results: A total of 170 questionnaires were collected from 257 healthcare workers. Overall, 99.1% of the participants had contact with drug-dependent patients during their professional experience. Nearly 75% had difficulties in treating them. The psychometric analysis of the SM-GIBED scale in the Spanish context obtained values of KMO = 0.655 and Bartlett's test p < 0.000. Cronbach's alpha of 0.738 was obtained from the reliability analysis. A reliability analysis of each of the SM-GIBED questions found no case with an alpha lower than 0.71. In conclusion, positive aspects include an ingratiating attitude and subject-to-subject communication when nurses self-define as empathic and non-paternalistic. Among the negative aspects, there is a lack of communication skills and assertiveness with these patients. This highlights a certain degree of resignation and dissatisfaction when working with drug addicts.

With the rapid growth of large language models (LLMs), there is increasing demand for memory and computation in LLMs. Recent efforts on post-training pruning of LLMs aim to reduce the model size and computation requirements, yet the performance is still sub-optimal. In this paper, we present a plug-and-play solution for post-training pruning of LLMs. The proposed solution has two innovative components: 1) Relative Importance and Activations (RIA), a new pruning metric that jointly considers the weight and activations efficiently on LLMs; and 2) Channel Permutation, a new approach to maximally preserve important weights under N:M sparsity. The two proposed components can be readily combined to further enhance the N:M semi-structured pruning of LLMs. Our empirical experiments show that RIA alone can already surpass all existing post-training pruning methods on prevalent LLMs, e.g., LLaMA ranging from 7B to 65B. Furthermore, N:M semi-structured pruning with channel permutation can even outperform the original LLaMA2-70B on zero-shot tasks, together with practical speed-up on specific hardware. Our code is available at: https://github.com/biomedical-cybernetics/Relative-importance-and-activation-pruning

LLMs are a compressed repository of a vast corpus of valuable information on which they are trained. Therefore, this work hypothesizes that LLMs such as Llama, Orca, Falcon, and Mistral can be used for misinformation detection by making them cross-check new information with the repository on which they are trained. Accordingly, this paper describes the findings from the investigation of the abilities of LLMs in detecting misinformation on multiple datasets. The results are interpreted using explainable AI techniques such as LIME, SHAP, and Integrated Gradients. The LLMs themselves are also asked to explain their classification. These complementary approaches aid in better understanding the inner workings of misinformation detection using LLMs and lead to conclusions about their effectiveness at the task.

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method Let-Net(Large kernel and attention mechanism Network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to broaden the receptive field and incorporates depthwise convolution with residual connections to reduce parameter count. Secondly, Let-Net integrates an attention mechanism to enhance the information flows in channels and spaces for more comprehensive and distinctive FV feature extraction. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications.

Background: Although cerebral aneurysm (CA) is a defining complication of COL4A1/2-related vasculopathy, the specific factors influencing its onset remain uncertain. This study aimed to identify and analyze these factors. Methods: We described a family presenting with a novel variant in the COL4A1 gene complicated with CA. Concurrently, an exhaustive review of previously documented patients with COL4A1/2-related vasculopathy was conducted by sourcing data from PubMed, Web of Science, Google Scholar, and Ichushi databases. We compared the variant types and locations between patients with CA (positive group) and those without CA (negative group). Results: This investigation encompassed 53 COL4A1/2 variants in 76 patients. Except for one start codon variant, all the identified variants in CA were missense variants. Otherwise, CA was not associated with other clinical manifestations, such as small-vessel disease or other large-vessel abnormalities. A higher frequency of missense variants (95.5% vs 58.1%, p = 0.0035) was identified in the CA positive group. Conclusions: CA development appears to necessitate qualitative alterations in COL4A1/2, and the underlying mechanism seems independent of small vessel disease or other large vessel anomalies. Our findings suggest that a meticulous evaluation of CA is necessary when missense variants in COL4A1/2 are identified.

A digital twin is a virtual representation that serves as the real-time digital counterpart of a physical object or system. Recent advancements have extended the concept of digital twins to humans, incorporating complex biological data such as DNA (Predictiv Care, Inc.) and immune system profiles. These sophisticated models go beyond mere pictorial representations, offering a more holistic digital reflection. However, a significant gap remains. The current human digital twin models are not capable of learning one’s preferences. In this pilot study, we introduce Diginality, a chatbot powered by HyperCLOVA X, a Large Language Model (LLM) developed by NAVER, Inc. Diginality, learns one’s preferences with custom training from data collected by interview-style questions on the user’s topic of interest. Our findings demonstrate that Diginality successfully answers one’s preferences, thereby adding a new dimension to the concept of human digital twins. This work represents a pioneering step towards creating a more comprehensive and psychologically nuanced human digital twin.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive and biologically heterogeneous disease. Approximately 40% of patients with DLBCL will experience disease relapse or will be refractory to first line chemoimmunotherapy. In recent years there have been several new therapeutic agents approved for the treatment of relapsed/refractory (R/R) DLBCL. These agents include anti-CD19 chimeric antigen receptor T-cell therapies (CAR T-cells) and monoclonal antibodies as polatuzumab and tafasitamab. Nevertheless, despite the high efficacy of all these new therapies, there are still patients who do not respond or relapse, representing an unmet clinical need. This review describes new promising therapies that are under investigation to treat R/R DLBCL.

Electron-hole recombination and narrow range utilization of sunlight limit the photocatalytic efficiency of TiO2. We synthesized a carbon dots (CDs) modified TiO2 nanoparticles (NPs) with flower-like mesoporous structure, i.e., porous TiO2/CDs nanoflowers. Among such hybrid parti-cles, CDs worked as photosensitizers for the mesoporous TiO2 and enabled the resultant TiO2/CDs nanoflowers with a wide-range light absorption. Rhodamine B (Rh-B) was employed as a model organic pollutant to investigate the photocatalytic activity of the TiO2/CDs nanoflowers. The results demonstrated that the decoration of CDs on both TiO2 nanoflowers and P25 NPs enabled a significant improvement of the photocatalytic degradation efficiency compared with the pristine TiO2. TiO2/CDs nanoflowers with porous structure and larger surface areas than P25 showed a higher efficiency owing to prevent local aggregation of carbon materials. All the results revealed that the introduced CDs and the unique mesoporous structure, large surface areas and loads of pore channels of the prepared TiO2 NPs played important roles in the enhancement of the photocatalytic efficiency of the TiO2/CDs hybrid nanoflowers. Such TiO2/CDs composite NPs also opens a door for photodegradation, photocatalytic water splitting and enhanced solar sun-light as light source.

To date, several different approaches are available to study sediment dynamics at reach or watershed scale, based on very different hypothesis. One of such assumptions, the so-called “morphodynamic equilibrium hypothesis” is becoming little unpopular for its embedded simplifications. The aim of this work is to demonstrate how this approach proves yet effective in modelling landscape morphodynamics at the watershed scale, for what concerns the longitudinal profile of a river and the sedimentary aspects. The application of a 1-D model based on the equilibrium hypothesis has been implemented for several large rivers worldwide. Geomorphological parameters have been analysed, which describe the evolution of longitudinal profile (concavity) and sediments characteristics (aggrading and fining), and the results show a reasonably good correspondence with qualitative estimation of the same parameters. At the scale of analysis and for the chosen systems, which show high inertia to geomorphological changes likely owing to their longitudinal extension, the model can detect where the present conditions reflect a big disturbance to the “natural equilibrium” thus allowing water managers to identify present issues to be addressed.

Knowledge about ecological conditions and processes in centers of endemism (CoEs) is still limited with respect to various systematic groups of organisms, ecosystem types, ecological conditions and ecosystem functions. Endemics and CoEs play a prominent role in nature conservation monitoring and management, and in the organization of zoos, aquaria and botanical gardens. We review the meaning of different groups of organisms and indicators for the characterization of endemic-rich regions, the importance of heterogeneity in space, continuity in time, isolation and ex-situ management for the survival of endemic and threatened species. Currently, conversion of land cover and land use change are the most important causes of biodiversity decline and extinction risk of endemic and endangered species concentrated in CoEs. These are followed by climate change, including severe weather, and then natural processes such as volcanism, landslides or tsunamis. For conservation purposes the management of zoos, aquaria, botanical gardens, of regional land use, and social aspects of the diversity of endemics and CoEs have to be taken into account as well. We need better answers to questions about the relationship between ecoregions, CoEs and regional awareness of biodiversity, which is linked with human culture including the management of zoos, aquaria and botanical gardens, aesthetics, wellbeing, health and trade.

Diffuse large B-cell lymphoma (DLBCL) is the most common haematological malignancy in humans and dogs. Several studies disclosed some similarities between the two species, including the constitutive activation of NF- κB pathway as a fundamental underlying pathogenetic mecha-nism. In humans, downregulation of IL-1R8 is implicated in DLBCL development, but its role in dogs has not been explored so far. To gain insight into the pathogenesis of this tumor in dogs, we evaluated the mRNA and protein expression of IL-1R8 in 12 hyperplastic lymph nodes ob-tained from dogs not bearing tumors and from 50 dogs with DLBCL. Moreover, we analysed through qRT-PCR the expression of TLR7, TLR9, MYC, and p52 genes that are known to be in-volved in the IL-1R8 regulatory network. IL-1R8 and p52 were downregulated in DLBCLs com-pared to control lymph nodes (p<0.001), while a higher expression of TLR7, TLR9 and MYC was observed in tumors (p<0.01). Immunohistochemistry confirmed gene expression results, reveal-ing a significantly lower IL-1R8 staining score in DLBCLs compared to control lymph nodes (p<0.0001). Taken together, these results suggest that IL-1R8 downregulation may represent one of the mechanisms driving DLBCL pathogenesis in dogs, mainly through dysregulation of the Toll-like/Interleukin receptors signalling cascade and the aberrant activation of classical NF-κB pathway.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, a commercial FD reservoir simulator (ECLIPSE) and an academic FD colloid transport code (MNMs). For a 1D homogeneous case, the effluent breakthrough curves (BTC) produced by the in-house simulator are in good agreement with the analytical solution and MNMs, respectively. For a two-dimensional (2D) heterogeneous case, the BTC and concentration pattern of the in-house simulator all match well with the solution produced by commercial simulator. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, given zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wave just prior to specifying the creation of ‘gravitons’, while using Karen Freeze’s criteria as to the breakup of primordial black holes to give radiation era contributions to GW generation. The GW generation will be when there is sufficient early universe density so as to break apart Relic Black holes of the order of Planck mass (10^15 grams) which isabout when the mass of relic black holes is created, 10^-27 or so seconds after expansion starts. Need to state a key result will be in the initial potential V calculated, in terms of other input variables

Mindfulness interventions have been implemented in many countries. This study aimed to examine the psychometric properties of English and Thai-version of the 15-item mindfulness attention awareness scale (MAAS) across five samples. A descriptive correlation research was conducted in the Philippines and Thailand, and five data sets were generated using self-reported and online questionnaires. Exploratory factor analyses were used to explore the factorial structure of the MAAS. Confirmatory factor analyses were performed to test measurement invariance across samples. Concurrent validity was tested by examining relationships between the MAAS and psychological well-being (PWB). A unidimensional structure of the MAAS was documented across the five samples. The MAAS demonstrated measurement invariance across samples for both English and Thai versions. Concurrent validity was displayed through significant correlations with PWB. This study produced evidence to support the construct validity, concurrent validity, and reliability of the English and Thai versions of MAAS. This study was not registered.

Phylogenetic tree analysis is commonly used to understand the evolutionary distance between different species or strains of the same species. This work originally aimed to gain an understanding and visual depiction of the evolutionary distance in 23S rRNA gene of different Helicobacter pylori strains. Using an in-house MATLAB multiple sequence alignment and phylogenetic tree analysis software, the phylogenetic tree constructed for 23S rRNA gene reveals two major lineages with further subdivisions in each cluster. This suggests two major evolutionary forces driving the evolution of the 23S rRNA gene. In comparison, there is relatively short evolutionary distance in the 16S rRNA gene phylogenetic tree of H. pylori, suggesting lack of major evolutionary forces driving mutational changes of the gene. Overall, the data suggests that the large ribosome subunit which houses the 23S rRNA of H. pylori is undergoing significant conformational changes that may be a response to the frequent use of various antibiotics that target the ribosome of H. pylori.

Calibration of flow devices is important in several areas of pharmaceutical, flow chemistry and microfluidic applications where dosage of process liquids or accurate measurement of the flow rate is important. The process-oriented liquid itself might influence the performance of the flow device and the simultaneous determination of the dynamic viscosity under flow conditions might be a valuable information for the process parameters. To offer the simultaneous calibration of the dynamic viscosity of the process-oriented liquid at the corresponding flowrate, METAS has built a pipe viscometer for the traceable in-line measurement of the dynamic viscosity in the current flow facilities for low flow rates from 1 L/min to 150 mL/min and pressure drops up to 10 bar. The traceability of all the measuring quantities as well as the geometrical dimensions of the micro tube guarantee the traceability of the pipe viscometer to SI units. The most challenging part is the traceable determination of the inner diameter of the micro tube. This can be achieved by measuring the pressure drop as a function of flow rate with the pipe viscometer and applying the law of Hagen-Poiseuille with a traceable dynamic viscosity of a reference liquid (water) or perform the measurements with the micro-CT at METAS, which determines the inner diameter by x-ray diffraction. The validation of the stated measurement uncertainty of the pipe viscometer has been performed by means of calibration of the dynamic viscosity of several reference liquids with traceable density and kinematic viscosity. The setup of the facility, the traceability as well as the uncertainty calculation of the pipe viscometer for the in-line measurement of the dynamic viscosity are discussed in this paper.

The sustainability of agroecological systems, biodiversity protection, animal welfare and consumer demand for higher-quality products from alternative and extensive farming methods, have reinforced interest in local breeds that are well adapted to low-input environments. However, food safety needs to be safeguarded to reinforce consumer confidence. The aim of this study was to conduct a preliminary investigation on the occurrence of Salmonella spp. in eggshells, hen’s cloaca and litter materials from autochthonous Portuguese laying hens raised in a semi-extensive system for small-scale production. A total of 279 samples were obtained, with 63 samples from the “Preta Lusitânica” breed, and 72 samples each from the remaining autochthonous breeds, namely “Branca”, “Amarela” and “Pedrês Portuguesa”. None (0%) of the samples analyzed were positive for Salmonella spp.. To the best of our knowledge, these are the first results of Salmonella evaluation from hen’s cloaca, eggshells, and litter materials in autochthonous Portuguese chickens, suggesting that a semi-extensive production system can contribute to better food security and a lower risk to public health and the environment.

Dolomite is a common type of natural soluble rock. The strength of rock decreases under the action of corrosion, which has a significant impact on the self-stability and long-term safety of the tunnel surrounding the rock. To reveal the microscopic structure evolution and strength-damage law of carbonate rock caused by corrosion, chemical corrosion, rock uniaxial compression, and electron microscope scanning tests are conducted at different pH values on the dolomite of the Doushantuo Formation. The rock dissolution at different pH values exhibits four typical stages: the initial dissolution stage, secondary dissolution acceleration stage, stable dissolution rate stage, and dissolution attenuation stage. During the dissolution process, the initial dissolution rate is 25.91 times that of the stable stage, and the maximum strength attenuation is 76.2% after 21 days of dissolution. For macroscopic failure, the rock is developed from 1 to 2 external fractures to multiple internal and external fractures and penetrated, and the specimen transforms from brittle to flexible. For microstructure, the sample exhibits corrosion characteristics along the joint surface, intensified corrosion at the edge, etc. The porosity increase rate is 0.6%/d; however, the length–width ratio of the pores is maintained at 1.7–1.85, indicating that the development rate of pores in different directions is similar. The results of this study have enriched the study of the dolomite dissolution mechanism and have important reference value for the stability evaluation of tunnel surrounding rock in karst environments.

Hydrogels, soft materials with 3D polymer networks in aqueous solution, have been developed for engineering and bio-related fields. However, these conventional hydrogels are weak and brittle due to lack of energy dissipation mechanisms. Recently, dual-network hydrogels have been proposed, combining rigid and flexible networks and exhibiting high strength, stretchability, and toughness. This paper explores the rheological properties of dual-network hydrogels based on acrylamide and sodium alginate under large deformations. This dual network is a combination of a covalently crosslinked polyacrylamide network and a supramolecular crosslinked sodium alginate network at the presence of divalent calcium cations. Small and large amplitude oscillatory shear methods with Fourier transform rheology, stress decomposition method, and Chebyshev polynomial analysis of large amplitude oscillatory shear (LAOS) data were employed to evaluate non-linearity limit, toughness, and network rigidity. The concentration of calcium ions affects (concentrations 0-80 mg/ml) the nonlinear transition and limit points, and all gel samples exhibit strain hardening, shear thickening, and shear densification.

Mechanical recycling of solid plastic wastes on a small-scale level can be accomplished with the correct approaches. Thermoplastics are mostly considered for mechanical recycling because of their physical properties and ease of reprocessing. This paper reviews the mechanical reprocessing techniques of selected thermoplastics (polyethylene terephthalate and polyolefins) since they constitute a significant proportion of plastics used commercially. Furthermore, necessary considerations for effective operation of small-scale plants, including energy requirements of machinery and optimisation in order to improve efficiency and product quality, are discussed. A clearer understanding and addressing of the process-related challenges will lead to successful establishment and management of small-scale mechanical recycling facilities to benefit communities. Efficient small-scale mechanical reprocessing establishments have become essential in reducing the environmental impacts of solid plastic wastes and for energy conservation.

MCrAlYHf bond coats are employed in jet and aircraft engines, stationary gas turbines, and power plants, which require strong resistance to oxidation at high temperatures. The oxidation behavior of a free-standing CoNiCrAlYHf coating was investigated in this study. Isothermal oxidation tests were performed in air at 1050 °C on the specimens with various levels of surface roughness to investigate the oxidation kinetics. X-ray diffraction, focused ion beam, scanning electron microscopy (SEM), and scanning transmission electron microscopy were used to characterize the surface oxides. The surface roughness was examined using a contact profilometer and SEM. An empirical model was proposed to elucidate the impact of surface roughness on the oxidation behavior based on the correlation between the surface roughness level and oxidation rates.

Photoelectrochemical systems have the potential to contribute to de-carbonation of the energy system because solar energy can be directly converted to hydrogen which can be burnt without the release of greenhouse gases. However, meaningful deployment of photoelectrochemical (PEC) technology in the global energy system, even when highly efficient scaled up devices become available, shall only be a reality when their safe and reliable operation can be guaranteed over serveral years of service life. The first part of the review discusses the importance of hermetic sealing of up scaled PEC device provided by the casing and sealing joints from a reliability and risk perspective. The second part of the review presents a survey of fully functional devices and early demonstrators and uses this to establish the extent to which the state of the art in PEC device design address the issue of hermetic sealing. The survey revealed that current material choices and sealing techniques are still unsuitable for scale –up and commercialization. Accordingly, we examined possible synergies with related photovoltaic and electrochemical devices that have been commericalised and derived therefrom, recommendations for future research routes that could accelerate the development of hermetic sealings of PEC devices.

In previous researches, Job Crafting questionnaire to develop is consists of 3 factors which are Task Crafting, Cognitive Crafting, and Relationship Crafting with 12 to 17 items. The purpose of study is to develop JCQ for leisure sports instructor of Korean. 274 valid samples are used for analysis. Data collecting is purposeful sampling. At result, for Korean Sports Instructor Job Crafting Scale is constructed 3 factors with 12 items is constructed by 3 step procedure. KSIJCQ is confirmed on convergent discriminant validity evidence. In conclusion, KSIJCQ is a valid scale of the measuring and distributes Job Crafting of generalization in sports.

The contemporary landscape of education is witnessing a paradigm shift towards innovative instructional methods, with the flipped learning approach gaining considerable attention. The purpose of this research was to investigate the impact of the flipped learning approach on students' perception and acceptance throughout an entire semester in the 'Introduction to Programming with Java' course, using a research design with a quantitative approach, ultimately aiming to inform educational practice and advance our knowledge of innovative teaching methods in higher education. This study was conducted at a university with 174 students involved, divided into two groups, 87 students in the experimental group and 87 students in the control group. The data collected through the scales were analyzed by using descriptive and inferential statistical analysis techniques in statistical software. At the end of the measurements, the technology acceptance level and self-directed learning perceptions of engineering students who received education with flipped learning were high. The results suggest that educators should consider students' readiness for self-directed learning when implementing the flipped learning approach and focus on creating an environment that supports their autonomy and engagement. This research offers valuable guidance for instructors, curriculum designers, and educational policymakers seeking to enhance the effectiveness of flipped learning in higher education courses.

Background: The novel coronavirus (COVID-19) infection is primarily transmitted through respiratory droplets from an infected person and contact with tainted surfaces or items. Social distancing became the primary measure of preventing the spread of COVID-19, with the principal aim being to reduce the probability of contact with an already infected person. Social distancing can be distressing, as it is against the community's way of life. Saudi Arabia imposed a curfew and suspended all religious, entertainment, sporting, and mass congregations. The daily updates on COVID-19 infection and mortality are upsetting and further, aggravate depression and anxiety. With this background, this study was planned with the following objectives. To determine the sociodemographic profile of the study participants, to find the prevalence of psychological morbidity, and to measure the association between the sociodemographic details, COVID-19 associated factors, and psychological effects among Abha citizens during the COVID-19 pandemic. Methodology: A descriptive cross-sectional community-based study was conducted in the Abha city population from August 2021 to July 22. This study followed snowball sampling, the data was collected using an online Google form the link was shared in WhatsApp groups and through emails to contacts, asking friends to share it with their friends, until reaching the adequate sample size the responses were accepted. Results: A total of 530 participated, and their age ranged from 19 -70 years. Many of the participants (34.5%, n=183) belonged to 36-45 years old. Most of the responders were 69.8% married and Females (69.2%, n=367). Half of the participants had been quarantined (49.6%), and 51.5% were scared from fear of COVID-19. 64.8% of the participants had depression; 14.2%, 20.8%, 13.6%, and 16.2% had mild, moderate, severe, and extremely severe depression, respectively. Around 58.2% of participants suffered from anxiety; 5.8% experienced mild anxiety, 21.7% moderate anxiety, and 30.7% severe anxiety. The proportion of stress among the participants was 45.0%; 10.8% had mild stress, 9.4% had moderate stress, and 24.5% had severe to extremely severe stress. Conclusions: COVID-19 poses mental health problems among individuals and communities. There is a need to find the more susceptible individuals for mental health issues or other psychological disorders. Mental health and psychological problems can be resolved with health education, counseling, and appropriate interventions to curb the negative health impacts of COVID-19.

In the last years, more and more studies highlight the advantages of complementing traditional master classes with additional activities that improve students´ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce intuitively students in the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use an amateur camera, a black background and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.

Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems in which systematic architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope up with current Information and Communication Technologies (ICT). The distributed generation in smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review on architecture for smart grids. An in depth analysis of layered and agent based architectures is presented and compared under various domains.

Large language model (LLM) is a representation of a major advancement in AI, and has been used in multiple natural language processing tasks. Nevertheless, in different business scenarios, LLM requires fine-tuning by engineers to achieve satisfactory performance, and the cost of achieving target performance and fine-tuning may not match. Based on the Baidu STI dataset, we study the upper bound of the performance that classical information retrieval methods can achieve under a specific business, and compare it with the cost and performance of the participating team based on LLM. This paper gives an insight into the potential of classical computational linguistics algorithms, and which can help decision-makers make reasonable choices for LLM and low-cost methods in business R&D.

Besides the Lagrangian and the Eulerian descriptions, the motion of a body can also be expressed relative to the present configuration of the body, known as the relative motion description. It is interesting to consider such a relative motion description in general to formulate the basic system of field equations for solid bodies. In doing so, when the time increment from the present state is small enough, the nonlinear constitutive equations can be linearized relative to the present state so that the resulting system becomes linear. This will be done for thermoelastic materials with a brief comment on the exploitation of entropy principle in general. Relative Lagrangian formulation is based on the well-known ``small-on-large'' idea, and can be implemented for solving problems with large deformation in successive incremental manner. Some applications of such a formulation in numerical simulations are briefly reviewed.

New or in-service truss bridges, with or without upper bracing systems, may display instability phenomena such as general lateral torsional buckling of the upper chord. The buckling of structural elements, particularly in the case of steel bridges, can be associated with the risk of collapse or temporary/permanent withdrawal from service. Buckling poses a significant danger as it often occurs at lower load values compared to those considered during the design phase. Additionally, this phenomenon can manifest suddenly, without prior warning, rendering intervention for its prevention impossible or futile. In contemporary times, most research and design calculation software offer the capability to establish preliminary values for buckling loads, even for highly intricate structures. This is typically achieved through linear eigenvalue buckling analyses, often followed by significantly more complex large displacement nonlinear analyses. However, interpreting the results for complex bridge structures can be challenging, and their accuracy is difficult to ascertain. Consequently, the objective of this paper is to introduce an original method for a more straightforward estimation of the buckling load of the upper chord in steel truss bridges. The method utilizes the theory of beams on an elastic foundation. The buckling load of the upper chord was determined using both the finite element method and the proposed methodology, yielding highly consistent results.

Vulnerabilities in smart contracts may trigger serious security events, and the detection of smart contract vulnerabilities has become a significant problem. In this paper, by using the multi-scale cascade encoder architecture as the backbone, we propose a novel Multi-scale Encoder Vulnerability Detection (MEVD) approach to detect well-known high-risk vulnerabilities in smart contracts. Firstly, we use the gating mechanism to design a unique Surface Feature Encoder (SFE) to enrich the semantic information of code features. Then, by combining a Base Transformer Encoder (BTE) and a Detail CNN Encoder (DCE), we introduce a dual-branch encoder to capture the global structure and local detail features of the smart contract code, respectively. Finally, to focus the model's attention on vulnerability-related characteristics, we employ the Deep Residual Shrinkage Network (DRSN). Experimental results on three types of high-risk vulnerability datasets demonstrate performance compared to state-of-the-art methods, and our method achieves an average detection accuracy of 90%.

Shrinking farm size and fragile farm resources pose a significant challenge to the sustainability of small-scale farms. Efficient resource utilization in small-scale farms is crucial to achieving farm sustainability through endogenous mechanisms. However, the precise mechanisms to integrate physical resources to achieve farm sustainability are not very clear yet. By capturing the interaction among farm resources as a network phenomenon, we identify the discrete resource interactions (RIs) in different types of small-scale farms of Indian Sundarbans, which are associated with higher farm sustainability. Thirty-two linkages, 11 reciprocal linkages, 22 triads, and three ‘core elements’ that occurred and cooccurred on highly sustainable farms are found to be critical in achieving farm sustainability. Using the properties of resource interaction networks as explanators of farm sustainability, we anticipate that sustainability in small-scale farms can be achieved by strategically creating new RIs on the farm. However, there may be limitations to such achievement depending on the nature of RI and type of farm. The analytical approach helps to understand the structural basis of sustainability in small-scale farms, and this approach can be used to achieve farm sustainability through the strategic integration of existing farm resources in the smallholder systems.

Perovskite based solar cells have achieved tremendous progress reaching record efficiency in the past 5 years. Numerous new processes and chemistry have been reported and contribute to the perovskite rapid progress. Continuous efficiency improvements are still necessary for perovskite solar cells, and an exploratory data analysis on devices performance over multiple studies could boost the technology development. Such analysis could identify patterns or provide insights that are not obvious in a single study. Here we present a high quality dataset containing only independently certified Pb-based perovskite solar cells summarizing their efficiency, relevant I-V metrics, manufacturing processes and materials used. Analysis over the dataset provides insights on how aperture size, perovskite deposition methods and materials used in each functional layer affect the final solar cell efficiency and I-V metrics. Future directions are also suggested for efficiency improvements.

From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded in the very environment we live in. We still do not fully understand how information takes the form of cities, and how our minds deal with it in order to learn about the world, make daily decisions, and take part in the complex system of interactions we create as we live together. This paper addresses three related problems that need to be solved if we are to understand the role of environmental information: (1) the physical problem: how can we preserve information in the built environment? (2) The semantic problem: how do we make environmental information meaningful? And (3) the pragmatic problem: how do we enact environmental information in our daily lives? Attempting to devise a solution to these problems, we introduce a three-layered model of information in cities, namely environmental information in physical space, environmental information in semantic space, and the information enacted by interacting agents. We propose forms of calculating entropy in these different layers, and apply these measures to archetypal urban cases and simulated scenarios. Our results suggest that ordered spatial structures and diverse land use patterns encode information, and that aspects of physical and semantic information affect coordination in interaction systems.

The gravitational constant is equivalent to natural units in its six unit dimensions. Evaluating the classical formulas in each of these dimensions shows that gravitational potentials are proportional to the Planck scale by the ratio of a body's radial density to a radial density limit in the ratio of Planck length to Planck mass.

The physical and economic sustainability of using Built Environment Wind Turbine (BEWT) systems depends on the wind resource potential of the candidate site. Therefore, it is crucial to carry out a wind resource assessment prior to deployment of the BEWT. The assessment results can be used as a referral tool for predicting the performance and lifespan of the BEWT in the given built environment. To date, there is limited research output on BEWTs in South Africa with available literature showing a bias towards utility-scale or conventional ground based wind energy systems. This study aimed to assess wind power generation potential of BEWT systems in Fort Beaufort using the Weibull distribution function. The results show that Fort Beaufort wind patterns can be classified as fairly good and that BEWTs can best be deployed at 15m for a fairer power output as roof height wind speeds require BEWT of very low cut-in speed of at most1.2ms⁻¹.

Climate change is unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems and the fisheries sector. This study documented the past occurrence of extreme climate change impacts, such as supertyphoon Pablo (ST: Bopha), which severely affected Baganga, Davao Oriental, about ten years ago. A mixed-methods data collection was used, combining semi-structured interviews with small-scale fishers (N=120) in four fishing villages and focus group discussions (N=4, participated by about 4 focus groups) on assessing the impacts and their adaptation after climatic events occurred. Our findings indicate that the four selected fishing villages were exposed to common factors of climate change events that destroyed many lives and their livelihood. Including a decrease in catch per trip and the fishing operations disruption (98%). However, due to the impact of the supertyphoon, small-scale fishers in Baganga developed psychological distress (emotional 44% and physical 24%) due to the extreme event or disaster and economic losses (32%). In order to survive, their adaptation strategies relied on government and non-government-provided provisions and projects, e.g., planting trees, constructing a sea wall with wave breakers, cash for work, and tourism as an alternative livelihood. Despite this, our study revealed that the community had limited knowledge on the impacts of climate change, lack clear management goals especially for fishers, and the widespread use of illegal fishing gears. The local government must strongly implement rules, policies, and adaptation measures that will contribute to better and more resilient communities. This can help them to withstand future shocks and provide sustainable fisheries resources that will benefit all the fishers. The study will be useful to policymakers, disaster management group and organization that will help assist affected communities highly affected by climatic events.

River regulations ultimately degrade fluvial forms and morphodynamics and simplify riparian and aquatic habitats. For several decades, river restoration actions have been performed to recover geomorphic processes and diversify these habitats to enhance both river biodiversity and ecosystem services. The objective of this study is to provide quantitative feedback on the experimental restoration of a large regulated and by-passed river (the Upper Rhine downstream of the Kembs Dam, France/Germany). This restoration consisted of the construction of two transverse groynes and the removal of bank protection. A monitoring framework composed of topo-bathymetric surveys as well as flow velocity and grain size measurements was established to assess the channel morphodynamic responses and evaluate their effects on habitat suitability for five native fish species using habitat models. A riverscape approach was used to evaluate the landscape changes in terms of both the configuration and the composition, which cannot be considered with classic approaches (e.g., WUA). Our results show that the two transverse groynes and, to a lesser extent, bank erosion, which was locally enhanced by the two groynes, increased habitat diversity due to the creation of new macroforms (e.g., pools and mid-bars) and fining of the bed grain size. Using a riverscape approach, our findings highlight that the restoration improved lentic fish habitats (eel and juvenile nase species) due to slowing of the local current and the deposition of fine sediments downstream of both groynes. As a consequence, the restoration improved the habitat suitability of the studied reach for more fish species compared with the pre-restoration conditions. This study also demonstrates that the salmon habitats downstream of the restored reach were improved due to fining of the bed grain size. This finding highlights that for restorations aimed at fish habitats, the grain size conditions must be taken into consideration along with the flow conditions. Furthermore, the implementation of groynes, while not a panacea, can be a strategy for improving fish habitats on highly regulated rivers, but only when more functional and natural options are impossible due to major constraints.

The hypothesis posed was whether participation in LaLiga Genuine Santander (competitive football) influenced the quality of life (QL) of the people who participated in it, since their perception of themselves is enhanced by all the aformentioned factors (self-determination, social inclusion, emotional well-being, physical well-being, material well-being, rights, personal development, interpersonal relationships). The objective was to evaluate the QL of people with Down's Syndrome (DS) using their self-perception (n=39) and the perception of the informants (family members, teachers) (n=39). The KidsLife-Down Scale, with a few modifications was used. In general, differences of opinion between the subgroups of participants with DS and informants showed that results were higher in terms of perception for participants in the DS subgroup. Scores for all variables were higher for those participants with DS who said they did engage in practicing competitive football. Despite the perception of informants provides a great deal of information regarding the QL of participants with DS, the latter should be involved in the evaluation process and their self perceptions taken into account. Our research shows that participation in the league modifies the perceptions of the participants with Down's Syndrome regarding their quality of life. However, these perceptions are not shared by the informants.

Recent observations of the dark energy density have demonstrated the fine-tuning problem, and the challenges faced by theoretical modeling. In this study, we apply the self-similar symmetry (SSS) model, describing the hierarchical structure of the universe based on the Dirac large numbers hypothesis, to Einstein's cosmological term. We introduce a new similarity dimension, D_B, in the SSS model. Using the D_B SSS model, the cosmological constant Λ is simply expressed as a function of the cosmic microwave background (CMB) temperature. The result shows that both the gravitational constant G and Λ are coupled with the CMB temperature, which simplifies the solution of Einstein's field equations for the variable Λ-G model.

Febrile neutropenia (FN) is a major concern in patients undergoing chemotherapy for diffuse large B-cell lymphoma (DLBCL); however, the overall risk of FN is difficult to assess. This study aimed to develop a model for predicting the occurrence of FN in patients with DLBCL. In this multicenter, retrospective, observational analysis, a multivariate logistic regression model was used to analyze the association between FN incidence and pretreatment clinical factors. We included adult inpatients and outpatients (aged ≥ 18 years) diagnosed with DLBCL who were treated with chemotherapy. The study examined 246 patients. Considering FN occurring during the first cycle of chemotherapy as the primary outcome, a predictive model with a total score of 5 points was constructed as follows: 1 point each for viral hepatitis, extranodal involvement, and a high level of soluble interleukin-2 receptor and 2 points for lymphopenia. The area under the receiver operating characteristic curve of this model was 0.844 (95% confidence interval: 0.777–0.911). Our predictive model can assess the risk of FN before patients with DLBCL start chemotherapy, leading to better outcomes.

In this research, a model is presented to detect and monitor the rotor bar’s condition of large motors. This proposed model uses two diagnostic methods MCSA and ZCT, to extract the fault components. The input of the proposed model is only the motor current at two levels of 80% and 100% of the nominal motor load, which by using the two methods MCSA and ZCT and making changes in how to use them can be the disadvantages of other methods such as incorrect detection of rotor bars in Large motors with variable load, the harmonical stator voltage (or the presence of the drives) and asymmetric conditions. The extracted components are classified using neural network, instead of experimental and human resources constraints. Using this classification algorithm is high accuracy and the ability to implement in conventional processors. The proposed model has been trained andtested using currents of real large motor data and 96.87% accuracy using neural network to detect faults and monitor the online status of the rotor bars. On the other hand, the proposed model has been implemented in the industrial environment (FiroozkoohCement Factory) and has been able to correctly determine the rotor bars of 4 large suspicious motors announced by the factory technicians.

This paper integrates carrier manifolds from control theory and hybrid systems modeling to develop a novel mathematical framework for Artificial General Intelligence (AGI). Carrier manifolds represent the state space of complex AGI systems, while hybrid systems model discrete and continuous dynamics together. The proposed architecture embeds carrier manifold into GPTProX, a hybrid AI solver combining conversational AI, logic programming, and optimization.

Despite the growing capabilities of large language models, concerns exist about the biases they develop. In this paper, we propose a novel, automated mechanism for debiasing through specified dataset augmentation in the lens of bias producers that can be useful in a variety of industries, especially ones that are “restricted” and have limited data. We consider that bias can occur due to intrinsic model architecture and dataset quality. The two aspects are evaluated using two different metrics we created. We show that our dataset augmentation algorithm reduces bias as measured by our metrics.

The predominance of English and Latin-based large language models (LLMs) has led to a notable deficit in native Arabic LLMs. This discrepancy is accentuated by the prevalent inclusion of English tokens in existing Arabic models, detracting from their efficacy in processing native Arabic's intricate morphology and syntax. Consequently, there is a theoretical and practical imperative for developing LLMs predominantly focused on Arabic linguistic elements. To address this gap, this paper proposes ArabianGPT, a series of transformer-based models within the ArabianLLM suite designed explicitly for Arabic. These models, including ArabianGPT-0.1B and ArabianGPT-0.3B, vary in size and complexity, aligning with the nuanced linguistic characteristics of Arabic. The AraNizer tokenizer, integral to these models, addresses the unique morphological aspects of Arabic script, ensuring more accurate text processing. Empirical results from fine-tuning the models on tasks like sentiment analysis and summarization demonstrate significant improvements. For sentiment analysis, the fine-tuned ArabianGPT-0.1B model achieved a remarkable accuracy of 95%, a substantial increase from the base model's 56%. Similarly, in summarization tasks, fine-tuned models showed enhanced F1 scores, indicating improved precision and recall in generating concise summaries. Comparative analysis of fine-tuned ArabianGPT models against their base versions across various benchmarks reveals nuanced differences in performance, with fine-tuning positively impacting specific tasks like question answering and summarization. These findings underscore the efficacy of fine-tuning in aligning ArabianGPT models more closely with specific NLP tasks, highlighting the potential of tailored transformer architectures in advancing Arabic NLP.

We review the literature on medical discourse and attempt to build a computational model of it. Medical discourse sheds a light on communication structure of patient-doctor and other communication scenarios in healthcare and should be leveraged to facilitate and automate this communication when it is possible and practical. We propose a unified framework to represent communication discourse at the meta-level, where the subject of the communication is expressed in a language object. So far, the broad range of work on medical discourse is detached from computational discourse analysis, and we explore the possibilities of filling this gap and computationally treat the peculiarities of how information is passed between the agents in a hospital setting. We select the domain of question answering (QA) against a corpus of medical documents of diverse nature to evaluate our computational model of medical discourse. It turns out that applying specific structures obtained in medical discourse studies improves the relevance and efficiency of question answering.

The mutton sheep breeding industry has transformed significantly in recent years, from traditional grassland free-range farming to a more intelligent approach. As a result, automated sheep face recognition systems have become vital to modern breeding practices and have gradually replaced ear tagging and other manual tracking techniques. Although sheep face datasets have been introduced in previous studies, they have often involved pose or background restrictions (e.g., fixing of the subject’s head, cleaning of the face), which restrict data collection and have limited the size of available sample sets. As a result, a comprehensive benchmark designed exclusively for the evaluation of individual sheep recognition algorithms is lacking. To address this issue, this study develops a large-scale benchmark dataset, Sheepface-107, comprised of 5,350 images acquired from 107 different subjects. Images were collected from each sheep at multiple angles, including front and back views, in a diverse collection that provides a more comprehensive representation of facial features. In addition to the dataset, an assessment protocol is developed by applying multiple evaluation metrics to the results produced by three different deep learning models: VGG16, GoogLeNet, and ResNet50, which achieved F1-scores of 83.79%, 89.11%, and 93.44%, respectively. A statistical analysis of each algorithm suggested that accuracy and the number of parameters were the most informative metrics for use in evaluating recognition performance.

Traditional numerical techniques such as sliding mesh, dynamic grid mesh, and others, have many limitations in dealing with flow simulation with large-scale movement of solid boundaries; which is the case for complex-shaped hydraulic turbomachinery such as propellers, pumps and turbines. The immersed boundary (IB) method provides a new approach to solve the above limitations. Therefore, this study proposes an sharp-interface IB method based on the level-set function that is suitable for simulating the flow through turbomachinery with complex geometries. This method is applied to actual three-dimensional numerical simulations of high-Reynolds number propellers using an in-house computational fluid dynamics solver. The results show that the proposed method can provide comparatively accurate predictions of unsteady load coefficients within the propeller flow passage, and capture the correct propeller wake characteristics as well as the interaction between the propeller wake and free surface. This study aims at providing a theoretical basis and engineering reference for the application of the IB method in engineering numerical simulations.

Treating relapsed and refractory diffuse large B-cell lymphoma is still challenging for clinicians, but the available CAR-T and bispecific antibodies revolutionized therapy. Autologous stem cell transplantation was the most effective treatment modality previously. The authors report data from a single center over ten years. The retrospective study included 116 patients. There were 53 relapsed, 39 primary refractory cases, 19 had CNS involvement, and 5 received primary consolidation transplants. The median duration of follow-up was 46 months. The median event-free survival was 75 months, and the median overall survival was 105 months for all cases. Five-year overall survival was 59%, and event-free survival was 54%. Pretreatment prognostic factors at diagnosis had no effect on the outcome of transplantation. The authors found no difference between survival in relapsed or refractory cases, and the number of salvage lines or the germinal center / activated B-cell type also did not influence the results. Complete metabolic response before transplant confirmed by 18FDG PET/CT strongly affected survival. The pretransplant creatinine and CRP levels significantly influenced the long-term outcome. The number of stem cells infused did not affect survival, but engraftment within nine days did result in better survival. These data support the finding that the response to salvage therapy did select a better prognostic group who may still benefit from autologous transplantation.

Over the last several decades, large wildfires are increasingly common across the United States causing disproportionate impact on forest health and function, human well-being, and economy. Here, we examine the severity of large wildfires across the Contiguous United States over the past decade (2011-2020) using a wide array of meteorological, vegetational, and topographical features in the Deep Neural Network model. A total of 4,538 wildfire incidents were used in the analysis covering 87,305 square miles of burned area. We observed the highest number of large wildfires in California, Texas, and Idaho, with lightning causing 43 % of these incidents. Importantly, results indicate that the severity of wildfire occurrences is highly correlated with the climatological forcings, land cover, location, and elevation of the ecosystem. Overall, results may serve useful guide in managing landscapes under changing climate and disturbance regimes.

The energy loss of photons due to the cosmological red shift is interpreted, here, as a periodical process of transferring electromagnetic field energy into the space. The transferred energy portions are independent on photon energy if this transfer occurs with their frequency. The amounts of periodically released energy are so small that the related ultra-long wave length photons have to be understood as perfectly delocalized. Thus, the described point of view bridges the quantum micro cosmos with the macro cosmos. It is proposed to regard this energy exchange as a typical property of universal time arrow and to interpret the “large numbers”, in particular the dimensionless reciprocal of product of Hubbles constant and Planck time as the fundamental parameter describing cosmic evolution.

Although sources of seston are much more complicated in lakes compared to marines, the influences of different source on the spatiotemporal variations in seston stoichiometry are still underexplored, especially in large eutrophic floodplain lakes. Here, we investigated the seston stoichiometry across a typical large eutrophic floodplain lake (Lake Taihu) over one year. In addition, we used the n-alkanes proxies for source estimation which are more robust than other elemental indicators (e.g. C: N ratios). Throughout the study, the average value of C: N: P ratio of 143: 19: 1 across Lake Taihu was higher than the classical Redfield ratio, but closed to the synthesized data from other lakes. Generally, seston C: N ratios varied the least across all environments, but C: P and N: P ratios varied widely and shown a significant seasonal pattern with lower ratios of N: P and C: P during senescence seasons and higher ratios in the growing seasons. This seasonal change was mainly associated with the shift from terrestrial-derived seston to algal-derived seston as, the significant lower ratios of terrestrial-derived seston from surrounding agricultural watershed. Spatially, the mean ratios of each site were similar, except relative high values of C: P and N: P ratios in the algal dominated area. Statistically, the predictive power of environmental variables was strongly improved by adding n-alkanes proxies. However, apart from sources indicators, particulate phosphorus (PP) contents also partly explained the spatiotemporal variations in stoichiometric ratios. Nevertheless, the mechanisms behind the dynamics of PP could be totally different and source-specific. This study highlights the priority of using n-alkanes proxies as tools to identify the source of seston which is essential to interpret the spatiotemporal variations in seston stoichiometric ratios among eutrophic floodplain lakes.

The world is currently, subjected to the worst health crisis documented in modern history; an epidemic led by the novel coronavirus disease 2019 (COVID-19). At the epicenter of this crisis, healthcare professionals continue working to safeguard our well-being. To the regular high levels of stress, COVID new heights even more to healthcare professionals so depending on the area, specialty, and type of work. Here we investigated what are the tendencies, or areas most affected. Through an adaptation of the original COVID-stress scale, we developed a remote, fast test designed for healthcare professionals of the Northeastern part of Mexico, an important part of the country with economic and cultural ties to the US. Our results showed 4 key correlations as highly dependent: Work area – Xenophobia (p &lt; 0.045), Work with COVID patients - Traumatic stress (p &lt; 0.001) and Total number of COVID patients per day – Traumatic stress (p &lt; 0.027), and Total number of COVID patients - Compulsive checking and reassurance. Overall concluding that normal levels of stress have increased (mild – moderate). Additionally, we further determine that the fear of being an asymptomatic patient (potential to spread without knowing) continues being a concern.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

This research explores the depolymerization of waste polymethyl methacrylate (PMMAW) from dental material in fixed-bed semi-batch reactors, focusing on three production scales: laboratory, technical, and pilot. The study investigates the thermal degradation mechanism and kinetics of PMMAW through thermogravimetric (TG) and differential scanning calorimetry (DSC) analyses, revealing a two-step degradation process. The heat flow during PMMAW decomposition is measured by DSC, providing essential parameters for designing pyrolysis processes. The results demonstrate the potential of DSC for energetic analysis and process design, with attention to standardization challenges. Material balance analysis across the production scales reveals a temperature gradient across the fixed bed negatively impacting liquid yield and methyl methacrylate (MMA) concentration. Reactor load and power load variables are introduced, demonstrating decreased temperature with increased process scale. The study identifies the influence of temperature on MMA concentration in the liquid fraction, emphasizing the importance of controlling temperature for efficient depolymerization. Furthermore, the research highlights the formation of aromatic hydrocarbons from the remaining char, indicating a shift in liquid composition during the depolymerization process. The study concludes that lower temperatures below 450 °C favor liquid fractions rich in MMA, suggesting the benefits of lower temperatures and slower heating rates in semi-batch depolymerization. The findings contribute to a novel approach in analyzing pyrolysis processes, emphasizing reactor design and economic considerations for recycling viability. Future research aims to refine and standardize the analysis and design protocols for pyrolysis and similar processes.

This paper presents a novel method to extract local features, which instead of calculating local extrema computes global maxima in a discretized scale-space representation. To avoid obtaining precise scales by interpolation and to achieve perfect rotation invariance, two essential techniques, increasing the width of kernels in pixel and utilizing disk-shaped convolution template are adopted in this method. Since the size of a convolution template is finite and finite templates can introduce computational error into convolution, we sufficiently discuss this problem and work out an upper bound of the computational error. The upper bound is utilized in the method to ensure that all features obtained are computed under a given tolerance. Besides, the technique of relative threshold to determine features is adopted to reinforce the robustness for the scene of changing illumination. Simulations show that this new method attains high performance of repeatability in various situations including scale change, rotation, blur, JPEG compression, illumination change and even viewpoint change.

We are using the book “Towards Quantum Gravity with an article by Claus Kiefer as to a quantum gravity interpretation of the density matrix in the early universe. The density matrix we are using is a one loop approximation, with inflaton value and potential terms, like V(phi) using the Padmanabhan values one can expect if the scale factor is a ~ a(Initial) times t ^ gamma , from early times . In doing so, we isolate out presuming a very small initial time step candidates initial time values which are from a polynomial for time values due to the Kiefer Density value.

This paper investigates the hydroelastic responses of offshore floating solar photovoltaic farms (OFPVs) to minimize structural motion. The OFPV usually occupies a large sea space in the order of hectares and due to its huge structural length-to-thickness ratio, the structural deformation under wave action has to be taken into consideration. The flexible deformation of the structure under hydrodynamic loading is termed the hydroelastic response. Due to the relatively long structural length with respect to the encountering wavelength, the diffraction and radiation of waves have to be taken into account to accurately represent the hydrodynamic loadings on the floating platform. The numerical model is first validated by comparing the eigenvalues and eigenvectors of the OFPV obtained from the proposed numerical scheme with their counterparts obtained from an established finite element software. This is followed by the investigation of the hydroelastic response of various OFPVs designed in varying layout configurations. The various layout configurations are obtained by altering the floating modular units’ dimensions as well as the spacing of the OFPVs when deployed adjacent to each other. The optimal configuration that gives the best performance in terms of the overall smallest response, known as compliance, is then suggested. The results suggest that a longish OFPV layout has a lower hydroelastic response and the motion could be further reduced by increasing the global flexural stiffness via layout arrangement.

To prevent CO2 leakage and ensure the safety of long-term CO2 storage, it is essential to investigate the flow mechanism of CO2 in complex pore structures at the pore scale. This study focuses on reviewing the experimental, theoretical, and numerical simulation studies on the microscopic flow of CO2 in complex pore structures during the last decade. For example, advanced imaging techniques, such as X-ray computed tomography (CT) and nuclear magnetic resonance (NMR), are used to reconstruct the complex pore structures of rocks. Mathematical methods, such as Darcy's law, Young–Laplace’s law, and the Navier-Stokes equation, are used to describe the microscopic flow of CO2. Numerical methods, such as the lattice Boltzmann method (LBM) and pore network (PN) model, are used for numerical simulation. The application of these experimental and theoretical models and numerical simulation studies is discussed, considering the effect of complex pore structures. Finally, future research is suggested to focus on: (1) Conducting real-time CT scanning experiments of CO2 displacement combined with the developed real-time CT scanning clamping device to realize real-time visualization and provide quantitative description of the flow behavior of CO2 in complex pore structures; (2) The effect of pore structures change on the CO2 flow mechanism caused by the chemical reaction between CO2 and the pore surface, the flow theory of CO2 considering wettability and damage theory in a complex pore structures; (3) The flow mechanism of multi-phase CO2 in complex pore structures; (4) The flow mechanism of CO2 in the pore structures at multiscale and the scale upgrade from microscopic to mesoscopic to macroscopic. Generally, this study focuses on reviewing the research progress of CO2 flow mechanisms in complex pore structures at the pore scale and affords an overview of potential advanced developments to enhance the current understanding of CO2 microscopic flow mechanisms.

Marine mortar was the goal material and its multi-scale physical-chemical-mechanical characteristics were the principal interest in this study. The on-line multi-scale damage detection experiments art was designed to quantify the characteristics mathematically and graphically. The normal cylinder specimen with 70-day age was produced and investigated by dynamically global MSHCT scan and local detection of EDS, SEM and XRD. The experiments results indicated that the marine mortar offered the appreciable strength at the early age at least, although some saline minerals were generated during the preparation. The micro-interfacial behavior and the parental foci controlled the damage development of the marine mortar the performance of which was still the adjustable one by the composition optimization.

Constraint-based metabolic modeling approaches have enhanced our knowledge and understanding of the metabolism of prokaryotes and eukaryotes. This approach highly depends on the reconstruction process of genome-scale metabolic models (Mmodels). M-models can guide effective experimental design and yield new insights into the function and control of biological systems. Despite the recent advances in the automated generation of draft metabolic network reconstructions, the manual curation of these networks remains a labor-intensive and challenging task. Thus, these ten quick tips for the manual curation process are essential for optimizing high-quality metabolic model generation in less time. This collection of tips describes in great detail the resources and methods to ensure successful reconstruction. Furthermore, it increases the scope of other protocols of metabolic modeling by including resources to reconstruct eukaryotic organisms. Thus, all tips are applicable to a wide range of eukaryotic organisms. We believe this manuscript will interest a broad audience and researchers from different disciplines, spanning from microbiology and systems biology to biotechnology.

Grazing exclusion (GE) and rest grazing (RG) are important management to restore grassland ecosystems. In order to evaluate the effects and mechanisms of different grazing management on species diversity, vegetation community indices and soil variables were determined in the plots of Qilian Mountains in Gansu Province. The results showed that diversity effects and their regulating mechanisms had space-scale dependence under different grazing management. Species richness and species diversity indices of RG in grassland were significantly higher than that of GE at the regional scale. Additionally, three grazing management in mountain meadows had only a significant effect on species richness, but different management in mountain meadows and temperate steppes had a significantly different effect on species diversity indices. Meanwhile, soil variables only influenced species diversity at the regional scale. Most of community and soil variables at each scale had positive effects on species diversity, except that the direction of biodiversity effects was negative for species coverage, mean plant height, soil porosity (SK) and bulk density (BD) under two contrasting grazing management. In conclusion, choosing RG at the regional scale and select grazing management according to different grassland types at the local scale to restore degraded grassland vegetation.

Anastomosing rivers are wetland systems with multiple channels, and there are many constraints limiting in-situ observations of their hydrodynamics. Therefore, there are few reports on the hydrodynamic data of such rivers. In order to obtain the hydrodynamic parameters of the river channels without hydrological observations in the anastomosing rivers, this study proposes an expression method namely expression of channel morphological parameters (ECMP) for hydrodynamic calculations. The calculation formula of the ECMP method based on the shape factor, scale factor, and gradient factor of the flow cross-section as independent variables. This method can be used to calculate the average velocity, discharge, specific stream power, gross stream power and other hydrodynamic parameters of the flow cross-section at different water levels, only requiring the measurement of morphological parameters such as the average depth, width-depth ratio, and gradient of the flow (channel) cross-section. The applicability of the ECMP method was verified using measured hydrological data. The results show that the ECMP method is a practical calculation method with high computational accuracy and convenient application for calculating river hydrodynamic parameters. It has great application value in study on fluvial geomorphology and hydrodynamics, as well as in the reconstruction of ancient river hydrology and hydrodynamics.

As there exist no repulsive forces in strong interaction, in a hypothetical approach, strong interaction can be assumed to be equivalent to a large gravitational coupling. Based on this concept, strong coupling constant can be defined as a ratio of the electromagnetic force and the gravitational force associated with proton, neutron, up quark and down quark. With respect to the product of strong coupling constant and fine structure ratio, we review our recently proposed two semi empirical relations and coefficients 0.00189 and 0.00642 connected with nuclear stability and binding energy. We wish to emphasize that- by classifying nucleons as ‘free nucleons’ and ‘active nucleons’, nuclear binding energy can be fitted with a new class of ‘three term’ formula having one unique energy coefficient. Based on the geometry and quantum nature, currently believed harmonic oscillator and spin orbit magic numbers can be considered as the lower and upper “mass limits” of quark clusters.

The effect of filling velocity on positive macrosegregations in large size steel ingots was studied. Macrosegregation and macro-/micro-structure were characterized on the hot-tops and a portion of the upper section of two ingots. The measurements revealed that segregation features in the two ingots varied as a function of the alloying elements, and that the severity of positive macrosegregation in the casting body was reduced when the filling rate was increased. It was also found that at the higher filling rate, grain morphologies in the first solidified zones of the ingot changed from columnar to equiaxe, and secondary dendrite arm spacing (SDAS) became slightly smaller in the intermediate and final solidified zones. The experimental findings were analyzed in the framework of diffusion and convection controlled solidification, as well as liquid metal flow theories. The solute dependence of segregation features was related to the difference in solid-liquid partition coefficient and diffusion capability of each element in the liquid iron. Calculation of Reynolds numbers (Re) during the filling process, for both ingots, showed that higher filling velocity caused more instable movement of the liquid metal in the initial solidification stage, resulting in the modification of grain morphology, as well as accelerated solidification rate.

The effects of rare earth Y content on the microstructure and high-temperature oxidation properties of 47Fe-36Ni-15Cr-1.5Mn alloy at 1000°C were investigated. The results show that 47Fe-36Ni-15Cr-1.5Mn alloy oxidizes at 1000°C under laboratory atmospheric pressure to form an oxide film layer dominated by Cr2O3 and (Fe, Ni, Mn) Cr2O4 spinel, and the oxidation curve of the alloy follows the parabolic law. After the addition of rare earth Y, rare earth phases precipitated along the grain boundaries in the alloy, and the more Y content, the more precipitated phases in the grain boundaries. The alloy with added rare earths was oxidized at a high temperature of 1000 °C for 2160 min, the oxidation law still followed the parabolic law, while the rare earth phase at the grain boundary reacted with the oxygen atoms infiltrated from the outside to generate a rare earth Y-rich oxide residing at the boundary between the grain boundary and the precipitated phase of the alloy. Add 0.5 wt.% rare earth Y 47Fe-36Ni-15Cr-1.5Mn-0.5Y alloy 1000 ° C high temperature oxidation of the formation of spinel oxide crystalline particles, dense and complete oxide film layer, the surface of the addition of a small amount of (0.5 wt.%) rare earth Y after the refinement of the oxide particles, and in the alloy grain boundaries in the form of oxides reside in the alloy to inhibit the cations in the matrix and the oxygen negative ions. and oxygen-negative ions in the alloy matrix, improving the antioxidant performance of the alloy. With the further increase of rare earth Y, during the oxidation of the alloy at high temperature, the precipitation phase at the grain boundary promotes the inward diffusion of oxygen, resulting in the deterioration of the antioxidant property of the alloy.

The characteristics of the eddy mass transport are estimated depending on the values of the parameters of a large-scale flow that forms under the conditions of the shelf seas in the Arctic. For this, the results of numerical simulation of the Kara Sea with a horizontal resolution permitting the development of mesoscale eddies are used. The parameters resulting from numerical experiment are considered as a statistical sample and are analyzed using methods of sensitivity study and clustering of sample elements. Functional dependencies are obtained that are closest to the simulated distributions of quantities. These expressions make it possible, within the framework of large-scale models, to evaluate the characteristics of the cross-isobatic eddy mass transport in the diffusion approximation with a counter-gradient flux. Numerical experiments using the SibCIOM model showed that areas along the Fram branch of the Atlantic waters trajectory in the Arctic as well as the shelf of the East Siberian and Laptev seas with adjacent deep water areas are most sensitive to proposed parameterization of eddy exchanges. Accounting for counter-gradient eddy fluxes turned out to be less important.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rain water. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima (2019). The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increases approximately 17%~18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

A multi-server parallel system dispatches the incoming job, which contains kn tasks into n servers. A job is considered to be computed if all the tasks associated with the job are processed. One job’s tasks can be encoded into at least kn “replicas” such that the job is considered to be served if any kn replicas finishing computation. In this paper, we analyze the random scheduling policy of a multi-server computing system under discrete time model in terms of Quality of Exponent (QoE), which is defined as the probability exponent that a typical job can be computed within a given number of time slots. We let kn/n be a constant. Assuming that any task of any job can be randomly dispatched by a “scheduler” to any server, and computing each task takes exactly one time slot. We divide the calculation of probability exponent into two parts, exponent of numerator and exponent of denominator. For the denominator, we give the almost exact exponent using Lagrange multiplier method, while for the numerator, an upper bound of the numerator’s exponent is provided. In addition, we also express the exponent in terms of information theoretical quantities and reconsider both of exponents in the context of large deviation theory.

Estimating Visual Quality of Street Space (VQoSS) is pivotal for urban design, environmental sustainability, civic engagement, etc. Recent advancements, notably in deep learning, have enabled large-scale analysis. However, traditional deep learning approaches are hampered by extensive data annotation requirements and limited adaptability across diverse VQoSS tasks. Multimodal Large Language Models (MLLMs) have recently demonstrated proficiency in various computer vision tasks, positioning them as promising tools for automated VQoSS assessment. In this paper, we pioneer the application of MLLMs to VQoSS change estimation, with our empirical findings affirming their effectiveness. In addition, we introduce Street Quality GPT (SQ-GPT), a model that distills knowledge from the current most powerful but inaccessible (not free) GPT-4, requiring no human efforts. SQ-GPT approaches GPT-4’s performance and is viable for large-scale VQoSS change estimation. In a case study of Nanjin, we showcase the practicality of SQ-GPT and knowledge distillation pipeline. Our work promises to be a valuable asset for future urban studies research.

Most of the pore-scale imaging and simulations of non-Newtonian fluid are based on the simplifying geometry of network modeling and overlook the fluid rheology and heat transfer. In the present paper, we developed a non-isothermal and non-Newtonian numerical model of the flow properties at pore-scale by direct simulation of the 3D micro-CT images using a Finite Volume Method (FVM). The numerical model is based on the resolution of the momentum and energy conservation equations. Owing to an adaptive meshing technique and appropriate boundary conditions, rock permeability and mobility are accurately computed. A temperature and concentration-dependent power-law viscosity model in line with the experimental measurement of the fluid rheology is adopted. The model is first applied at isothermal condition to 2 benchmark samples, namely Fontainebleau sandstone and Grosmont carbonate, and is found to be in good agreement with the Lattice Boltzmann method (LBM). Finally, at non-isothermal conditions, an effective mobility is introduced that enables to perform a numerical sensitivity study to fluid rheology, heat transfer, and operating conditions. While the mobility seems to evolve linearly with polymer concentration, the effect of the temperature seems negligible by comparison. However, a sharp contrast is found between carbonate and sandstone under the effect of a constant temperature gradient. Besides concerning the flow index and consistency factor, a good master curve is derived when normalizing the mobility for both the carbonate and the sandstone.

Milk production from Asiatic swamp buffalo is a new enterprise in Laos. As yields are limited, provision of high-quality Cow-Calf molasses nutrient blocks containing 10% urea (UMNB10) may improve productivity. A trial in a recently established commercial buffalo dairy examined dietary supplementation of lactating buffalo cows with UMNB10, with 3 groups of 9 cows in mid-lactation randomly selected. Two groups received ad-libitum access to UMBs with the remaining group free of block supplements. All animals were daily fed fresh Napier grass (30kg), corn (750gm), rice bran (1.45kg), plus accessed fresh Mulatto grass. Daily milk production (DMP) and body condition score (BCS) were recorded for the 2 months of access to UMB. Average DMP for the 2 supplemented groups were 1.02 litres and 0.96 litres, compared to 0.78 litres for the control group, suggesting improved milk productivity of 31% and 24% from accessing UMB. Partial budget analysis identified a strong incentive for use of the molasses blocks, with a net profit of USD408 and USD295 over a 30-day period for the supplemented groups. Molasses nutrient blocks may be a simple motivator for smallholder farmers in developing countries to increase the efficiency of large ruminant production, improving rural livelihoods, food security and potentially, reducing GHG emissions.

Involving local people in natural area management is very important to address the complexity of environmental management issues for sustainable use of local resources. Participatory methods require the contribution of local stakeholders in decision making. Mapping the environmental views of local communities allows for detecting aspects that could facilitate management efforts. This research – in the frame of the Skyros LIFE project and the PAMNATURA project - measures local acceptability of the conservation actions proposed by the LIFE project in Skyros Island (Greece) in relation with recording local people’s environmental orientation using the 15-item revised New Ecological Paradigm (NEP) scale. The research was carried out by means of questionnaires. The LIFE project proposed actions were grouped into three categories according to their theme, i.e. promoting (a) Nature protection, (b) Agro-pastoralism and (c) Ecotourism. The sample seems to largely agree with the LIFE project proposals, while the results showed high scores for most of the NEP scale items, implying pro-environmental beliefs, though there appears disagreement or neutrality regarding a few items. Local acceptability of the proposed actions was found to correlate to local people’s environmental concern measured through the NEP scale. Drawing on the results, implementation of actions related directly or indirectly to economic activities, preservation of traditional activities, as well as environmental education, interactive informing and consultation could enhance local participation. Skyros island seems to offer an appropriate social background for applying participatory and adaptive management and implementing conservation programs.

Considering the differences between the European and African continents concerning the management of the mining production sector, we decided to carry out this study with the main objective of demonstrating that, in Africa, mining can positively change the quality of life of the populations where it develops and, at the same time, it is possible to respect the environment, which is our main wealth. To achieve these objectives, it is necessary to present the mining activity of the continent, emphasizing both the negative aspects and its strong points. The most important thing is to make a good diagnosis of the situation, which will allow us to cure our "patient", that is, African mining production.

Background This paper draws learnings and successes based on field implementation experience spanning four years (2016–2019) of implementing CLTS by Prince of Peace Orphans and Widows Vision, a community-based organization located in Kaberamaido district in eastern Uganda. Methods The study aimed to document, disseminate and inform from an evidence-based point of view how adaptation and collaborative engagements triggers learning from mistakes to inform iterative changes from improvements and success.This is a descriptive paper that used project documents review based on field implementation experience. Existing project reports were synthesised, collated and curated for evidence. Data were drawn from project reports and records to inform narratives in writing. Implementation of the project was executed in homogenous rural communities occupied by people of the same dialect, cultural and social settings. Results We note that success in CLTS implementation can hardly be achieved by merely following prescriptions in handbooks and guidelines but rather by devising innovative community engagement and other participatory and community-driven techniques that foster adaptive management, promote ownership, and buy-in.Having learned from our failures, we used data to inform decisions and transformatively deviated from traditional CLTS implementation and introduced high impact and innovative approaches such as the use of CLTS helpdesks and Situation room, the Pamoja approach, learning labs and iterative feedback loops, innovatively tackling slippage and carefully introducing the follow-up mandona approach. These enhanced experiential learning and ultimately resulted in sustained sanitation behaviour. Conclusions The CLTS approach as outlined in the handbook needs to be flexibly adapted to address contextual needs. Reflective and learning sessions reinforced with routine feedback loops from implementers and beneficiaries yields tremendous results, propagates experiential learning, and ultimately results in a transformative deviation from undesirable to desired sanitation behaviours. These innovative approaches once carefully blended have proved to be sustainable, are adaptable and can work in an even larger scale and in a variety of contexts.

Eco-friendly and low-cost water-based nanolubricants containing rutile TiO2 nanoparticles (NPs) were developed for accelerating their applications in industrial-scale hot steel rolling. The lubrication performance of developed nanolubricants was evaluated in a 2-high Hille 100 experimental rolling mill at a rolling temperature of 850 ℃ in comparison to that of pure water. The results indicate that the use of nanolubricant enables to decrease the rolling force, reduce the surface roughness and the oxide scale thickness, and enhance the surface hardness. In particular, the nanolubricant consisting of 4 wt% TiO2, 10 wt% glycerol, 0.2 wt% sodium dodecyl benzene sulfonate (SDBS) and 1 wt% Snailcool exhibits the best lubrication performance by lowering the rolling force, surface roughness and oxide scale thickness up to 8.1%, 53.7% and 50%, respectively. The surface hardness is increased by 4.4%. The corresponding lubrication mechanisms are attributed to its superior wettability and thermal conductivity associated with the synergistic effect of rolling, mending and laminae forming that are contributed by TiO2 NPs.

Biological gels (bio-gels) are hydrated polymer networks that serve diverse biological functions, which often lead to intentional or unintentional exposure to particulate matter. In this work, we derive a microscopically motivated framework that enables the investigation of penetration mechanisms into bio-gels. We distinguish between two types of mechanisms: spontaneous (unforced) penetration and forced penetration. Using experimental data available in literature, we exploit the proposed model to characterize and compare between the micro-structures of respiratory, intestinal, and cervicovaginal mucus and two types of biofilms. Next, we investigate the forced penetration process of spherical and ellipsoidal particles into a locally quadrilateral network. The proposed framework can be used to improve and complement the analysis of experimental findings in vitro, ex vivo, and in vivo. Additionally, the insights from this work pave the way towards enhanced designs of nano-medicines and allow to assess risk factors related to the nano-pollutants exposure.

Severe postoperative pain affects most patients after thoracotomy and is a risk factor for post-thoracotomy pain syndrome (PTPS). This randomized controlled trial compared preemptively administered ketamine versus paravertebral block (PVB) versus control in patients undergoing posterolateral thoracotomy. The primary outcome was acute pain intensity on the visual analog scale (VAS) on the first postoperative day. Secondary outcomes included morphine consumption, patient satisfaction, and PTPS assessment with Neuropathic Pain Syndrome Inventory (NPSI). Acute pain intensity was significantly lower with PVB compared to other groups at four out of six time points. Patients in the PVB group used significantly less morphine via a patient-controlled analgesia pump than participants in other groups. Moreover, patients were more satisfied with postoperative pain management after PVB. PVB, but not ketamine, decreased PTPS intensity at 1, 3, and 6 months after posterolateral thoracotomy. Acute pain intensity at hour 8 and PTPS intensity at month 3 correlated positively with PTPS at month 6. Bodyweight was negatively associated with chronic pain at month 6. Thus, PVB but not preemptively administered ketamine decreases both acute and chronic pain intensity following posterolateral thoracotomies. The trial was prospectively registered at the Australian New Zealand Clinical Trial Registry (https://www.anzctr.org.au/; ACTRN12616000900415; 07 July 2016).

While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.

Survey data from 42 Australian eastern seaboard veterinary practices involving 506 cases are reported with regard to clinical signs, disease severity, mortality, use of pharmaceuticals, and recovery times. New measures of disease severity (visual analogue scales (VAS) and facial expressions) were tested alongside “gold standard” measures (neuromuscular junction (NMJ) scores). Univariable and multivariable logistic regression analyses were conducted to evaluate associations between variables. The VAS scores were progressive, prognostic (especially the respiratory scores) and correlated with the NMJ scores. The presence of inspiratory dyspnoea and crackles on the day of hospitalization, progressing to expiratory dyspnoea and an expiratory wheeze 24 hours later were highly predictive of mortality. Altered facial features on hospital admission were also highly predictive of mortality. The previously used respiratory score (using various clinical signs) was not predictive of mortality. Older animals had a higher mortality rate and no gender or breed susceptibility was found. The only pharmaceuticals that were positively associated with mortality were tick anti-serum and, in severe cases, antibiotics. The use of many pharmaceutical products (acepromazine, atropine, steroids, antihistamines, antiemetics, diuretics and S8 anti-anxiety and sedation drugs) had no effect on mortality. More drug classes were used with increasing clinical severity and specific factors (e.g. vomiting/retching, hydration) affected the period of hospitalisation. Geographic variation in respiratory signs and toxicity scores was evident, whereas mortality and disease severity were not different across regions.

Forest recreation can be successfully conducted for the purpose of psychological relaxation, as has been proven in previous scientific studies. During the winter in many countries, when snow cover occurs frequently, forest recreation (walking, relaxation, photography, etc.) is common. Nevertheless, whether forest therapy conducted in a forest environment with a snow cover will also have a positive effect on psychological indicators remains unknown. Furthermore, male subjects frequently participate in forest therapy experiments, whereas females are rarely involved. Thus, in this study, the effectuality of forest recreation during winter and with snow cover was tested on 32 young females. For these reasons, the experiment involved 15-minute periods of relaxation in a forest environment or in an urban environment, in addition to a pre-test under indoor conditions. Four psychological questionnaires (POMS, PANAS, ROS, SVS) were administered to participants before and after interventions. Results showed that participants’ levels of negative mood, as measured by different aspects of the POMS questionnaire (tension-anxiety, anger-hostility, depression-dejection, confusion, fatigue), decreased after exposure to the forest environment. In contrast, both tension-anxiety and anger-hostility increased in the urban environment. The indicator of negative affect from the PANAS questionnaire also increased after exposure to the urban environment, whereas the indicator of positive affect based on PANAS was higher in the forest environment than in the urban environment. Restorativeness and subjective vitality exhibited higher values after exposure to the forest environment in comparison to those from the control and pre-test. The changes in these indicators demonstrates that forest recreation in the snow during winter can significantly increase psychological relaxation in young females, as well as showing that recreation can be successfully conducted under these winter conditions.

Modern language models are designed to generate text so realistic that it could easily be mistaken for human-authored content. Additionally, they can engage in conversations with humans in a manner that appears coherent and reasonable. The epitome of this technological advancement is ChatGPT, a model based on OpenAI's Generative Pretrained Transformer (GPT) language model. With its ability to produce high-quality content in mere seconds, ChatGPT surpasses other chatbots in terms of capabilities, drawing significant interest and excitement from both the business community and academic researchers. This study offers a comprehensive review of current research on ChatGPT, delving into its technological foundation, supportive mechanisms, and findings regarding its benefits across various fields and application areas. We evaluate and discuss the strengths and weaknesses of ChatGPT based on this review and suggest potential avenues for future research.

Weaning is a critical period in the pig’s life. Piglets are confronted with abrupt changes to their physical and social environment, as well as management and nutritional changes. Weaning was always associated with a growth check and was frequently accompanied by post-weaning diarrhea in piglets. However, rapid increases in litter size, in the last decade, has increased within-litter piglet weight variation, with piglets now generally lighter at weaning, making the challenges associated with weaning even greater. Many interventions can be employed during the suckling period to ease the weaning transition for piglets. Pre-weaning strategies such as supervised farrowing (assistance with suckling, oxytocin provision), provision of pain relief to sows around farrowing, split-suckling, early oral supplementation with glucose, bovine colostrum, fecal microbiota transplantation, feed additives, solid and liquid creep feeding (milk and liquid feed) have all been investigated. The objective of these strategies is to stimulate earlier maturation of the digestive tract, improve immunity, reduce latency to the first feed post-weaning and increase early post-weaning feed intake and growth. This review focuses in particular on: 1) pain relief provision to sows around farrowing, 2) split-suckling of piglets, 3) pre-weaning provision of supplementary milk and/or liquid feed, 4) other strategies to stimulate earlier enzyme production (e.g. enzyme supplementation) and 5) other nutritional strategies to promote improved gut structure and function (e.g. L-glutamine supplementation). Correctly implementing these strategies can not only increase post-weaning growth and reduce mortality but also maximize lifetime growth in pigs.

Large Language Models (LLMs) have revolutionized the field of Artificial Intelligence with their ability to understand and generate natural language discourse. This has led to the use of LLMs in various creative fields such as music, art, and storytelling, which has sparked a debate on the impact of LLMs on human creativity. This article explores the cyclic effect of LLMs on human creativity, where LLMs can generate an ever-evolving cycle of creative output from both humans and machines. The article also highlights the importance of responsible and ethical use of LLMs, including privacy and copyright issues with the training data used by LLMs. The article emphasizes the need for transparency, data security measures, and AI governance policies to protect user data and ensure the safe use of LLMs. It also calls for the development of educational materials and resources to increase public understanding of LLMs and their ethical implications. The article concludes by highlighting the potential of LLMs as powerful tools for communication and education, but also emphasizes the need for ethical considerations to ensure the responsible and beneficial use of LLMs in society.