South Africa is a water stressed country experiencing mass urbanisation especially towards coastal cities. The country is already enduring the impacts of global warming and climate change with risk of water scarcity in many areas. The risk was evident with Cape Town near encounter with ‘Day Zero’ i.e., the day when water supplies would have been switched off and residents required to queue for daily water rations. The drought exposed the inadequa-cies of the existing water supply system. Paradoxically, in the same drought period, vast amounts of unutilized stormwater that could have augmented water supply run unabated into the ocean through rivers around the city. The study determined that the problem was not necessarily water shortage but lack of adequate water storage. This study investigated the suitability of coastal reservoirs for stormwater harvesting on the over 3000 km South African coastline. The objective was to identify suitable locations for coastal reservoirs. The study un-dertook a systematic process of selecting several candidate locations and eliminating unsuita-ble sites based on international best practice i.e., coastal topography, climate, hydrology, fluvi-al environment, catchment size and river water quality. Nine candidate sites were identified and ranked based on suitability and associated benefits. The identified locations in order of ranking include Knysna River, Berg River, Buffalo River, Kowie River, Thukela River, Orange River, Port of Richards Bay, Port of Durban, and Lourens River. The Knysna site, with a mean annual precipitation of 600 - 800 mm/annum and mean annual runoff of 100 - 500 Mm3/annum, was determined to be the most optimal location.

The conventional well placement was done manually by using a numerical reservoir simulator, and it required a lengthy trial-and-error process. It required great experience and expertise to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. In addition, the traditional gradient-based methods such as Line-search and Trust-region were not viable in terms of maximum results obtained. Gradient-based methods were too dependent on the surface gradient of the solution and may only converge to local optima instead of global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. Thus, genetic algorithms were utilized to automate the manual trial-and-error process and to overcome the limitations of the traditional gradient-based method. The objectives of this study were to analyse the effect of different initial well placement distributions, the number of random solution sizes, and the crossover rate on cumulative oil production. A synthetic reservoir model built using CMG Builder was used as the testing platform for the optimization problems. Well-placement parameterization and optimization set-up were carried out using the CMG CMOST optimization tool. The integration of CMG IMEX and CMOST optimized cumulative oil production based on the objectives of the study. The results obtained showed that the higher number of random solutions used resulted in higher cumulative oil production, with more generations needed to reach the optimum solution. It can be concluded that the larger number of random solutions used increased the probability of reaching the optimum solution, but will take more generations.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

Fingerprints are essential for human identification and are valuable tools in criminal investigations. The pursuit of new materials for digital printing is expanding, with increasing interest in natural compounds such as bixin, sourced from annatto seeds. Despite its traditional use as a natural dye with medicinal properties, the potential of bixin in papilloscopy remains largely untapped. In this study, we meticulously extracted bixin from annatto seeds and meticulously developed composites incorporating zinc carbonate (bixin/ZnCO3) and kaolinite (bixin/kaolinite). UV-visible spectroscopy was used for characterization, and the extracted bixin showed absorption peaks at 429, 453, and 481 nm, which were very similar to standard peaks at 429, 457, and 487 nm. The two samples also had the same retention times (7.07 min) according to further liquid chromatography analysis. Sweat pores were easier to detect thanks to the effectiveness of the bixin/ZnCO3 and bixin/kaolinite composites in creating high contrast sebaceous and natural latent fingerprints. These results highlight the composites’ potential as novel and fascinating instruments for papilloscopy applications, which might also improve forensic investigations.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

Eutrophication, a global concern, impacts water quality, ecosystems, and human health. It’s crucial to monitor algal blooms in freshwater reservoirs, as they indicate the trophic condition of a waterbody through Chlorophyll-a (Chla) concentration. Traditional monitoring methods, however, are expen-sive and time-consuming. Addressing this hindrance, we developed models using remotely sensed data from the Sentinel-2 satellite for large-scale coverage, including its bands and spectral indexes, to estimate the Chla concentration on 149 freshwater reservoirs in Ceará, Brazil. Several machine learning models were trained and tested, including k-nearest neighbours, random forests, extreme gradient boosting, the least absolute shrinkage, group method of data handling (GMDH), and sup-port vector machine models. A stepwise approach determined the best subset of input parameters. Using a 70/30 split for the training and testing datasets, the best-performing model was the GMDH, achieving an R2 of 0.91, MAPE of 102.34%, and RMSE of 20.38 g/L, which are values consistent with the ones found in the literature. Nevertheless, the predicted Chla concentration values were most sensitive to the red, green, and near infra-red bands.

The granulomatous cheilitis (GC) presents a heterogeneous group of disorders characterised by a granulomatous inflammation/reaction of the lips to various stimuli. Numerous etiologies have been proposed, including genetic, immunologic, allergic and infectious. Among the secondary causes of GC, a distant infection by Mycobacterium tuberculosis should be considered. The GC could be the clinical presentation of a tuberculide resulting from a hypersensitivity reaction to an underlying focus of active or latent tuberculosis infection (LTBI). This communication describes a woman diagnosed with GC related to LTBI, who responded well to antituberculosis treatment.

The ongoing global pandemic caused by coronavirus disease 2019 (COVID-19) has once again demonstrated the significance of the Coronaviridae family in causing human disease outbreaks. As SARS-CoV-2 was first detected in December 2019, information on its tropism, host range, and clinical presentation in animals is limited. Given the limited information, data from other coronaviruses may be useful to inform scientific inquiry, risk assessment and decision-making. We review the endemic and emerging alpha- and betacoronavirus infections of wildlife, livestock, and companion animals, and provide information on the receptor usage, known hosts, and clinical signs associated with each host for 15 coronaviruses discovered in people and animals. This information can be used to guide implementation of a One Health approach that involves human health, animal health, environmental, and other relevant partners in developing strategies for preparedness, response, and control to current and future coronavirus disease threats.

Human Immunodeficiency Virus (HIV) infection and its latent recurrent infection make vaccine development a significant challenge for traditional vaccines; however, the mRNA delivery of multiepitope antigens capable of creating antibodies against the surface proteins of HIV-1 and HIV-2 along with their respective Nef proteins, responsible for the latent infection can bring a most effective, as well as affordable solution to the unresolved epidemics of HIV. In this paper, we present the complete design of a multiepitope vaccine to prevent acute infections and inactivate Nef proteins that block the MHC-1 and MHC-2 pathways to hide the virus for later reinfection.

The Human Herpesviruses persist in the form of a latent infection in specialized cell types. During latency, the herpesvirus genomes associate with cellular histone proteins and the viral lytic genes assemble into transcriptionally repressive heterochromatin. Although there is divergence in the nature of heterochromatin on latent herpesvirus genomes, in general the genomes assemble into forms of heterochromatin that can convert to euchromatin to permit gene expression and therefore reactivation. This reversible form of heterochromatin is known as facultative heterochromatin and is most commonly characterized by polycomb silencing. Polycomb silencing is prevalent on the cellular genome and plays a role in developmentally regulated and imprinted genes, as well as X chromosome inactivation. As herpesviruses initially enter the cell in an un-chromatinized state, they provide an optimal system to study how de novo facultative heterochromatin is targeted to regions of DNA and how it contributes to silencing. Here, we describe how polycomb-mediated silencing potentially assembles onto herpesvirus genomes, synergizing what is known about herpesvirus latency with facultative heterochromatin targeting to the cellular genome. A greater understanding of polycomb silencing of herpesviruses will inform on the mechanism of persistence and reactivation of these pathogenic human viruses and provide clues regarding how de novo facultative heterochromatin forms on the cellular genome.

Tuberculosis (TB) is an infectious-contagious disease caused by M. tuberculosis (Koch’s bacillus). About one-quarter of the world’s population is infected with that bacillus and at risk of developing TB disease. Latent tuberculosis corresponds to people who have been infected by TB bacteria but are not (yet) ill. The most vulnerable population to TB activation includes HIV infected, drug abuse and autoimmune disease patients. Multiple Sclerosis (MS) is a chronic and autoimmune neurological disease caused by lymphocytic infiltration. Its prevalence worldwide is 22.2 million cases of MS. There is a relation between TB and MS: due to immunomodulation or immunosuppression treatment of MS (reactivation of latent infection), or due to the intense inflammatory response before the infection of the bacillus (increased susceptibility to the development of autoimmune diseases). Screening for TB includes complete patient history, physical exam, chest radiography, and Tuberculin Skin Test or IGRA (Interferon Gamma Release Assay). This investigation is suggested when MS drugs (immunomodulatory and immunosuppressant medications) are prescribed. If a patient has positive results, the treatment for MS should not be delayed for the finishing TB treatment. In this paper, considering the high prevalence of tuberculosis, we recommend that TB screening should be also done at the moment of Multiple Sclerosis diagnosis.

Background: The diversity of butterflies relies on the accessibility of food plants and the quality of their habitat. Methods: The purpose of this study was to evaluate the diversity butterfly based on latent GLM in 3 different Habitat. At the same time, we perform the step construction of Tweedie Distribution both in species levels and individual level. Results: Our finding can be shown by accuracy AIC, AICc, and BIC. Conclusions: In modelling with latent glm tweedie it can conclude that the our model is suitable for use at the species or individual level.

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

Physics behind collimated highly directional nature of lasers, and factors that keep the seven coloured waves that form white light together during their journey from Sun to Earth, in the face of the natural disruptive forces, is not fully understood. Energy levels were measured, in terms of alterations in induced current and voltage, in beams from a red laser, white LED light and the Sunlight before and during their disruption by diffusers (frosted glass for the lasers) and diffractors (diffraction grating for the white light) using a photovoltaic solar cell panel attached to a digital multimeter. Results show that disruption of the beams results in release of extra energy named as ‘Latent Light Binding’ Energy’. It is hypothesized that the ‘binding’ energy keeps laser waves firmly bound together both end-on and side-on enabling laser beams to travel long distances in collimated manner. Likewise, the 7 coloured waves that constitute white light are kept together, probably side-on, in their journey from the Sun to the Earth. The observation that diffraction of sunbeam is associated with increased power generation provides a new lead to improve harnessing of solar energy, where, currently, the focus is mainly on improving efficiency of photovoltaic cell.

Anthropogenic activities such as the damming of rivers have resulted in the formation of depositional systems for sediments that are naturally transported along river channels all over the world. The steady accumulation of sediments has profound effects on how reservoirs function. As the reservoir ages, the impact of sedimentation becomes more pronounced. In an alluvial channel, the dynamics of sediment movement, scour, and deposition are exceedingly complicated. The quantitative and qualitative management of river engineering heavily relies on sediment motion. One of the key concerns affecting reservoir storage capacity is reservoir sedimentation. Understanding the form and behavior of the river or reservoir is necessary for a scientific approach to sedimentation. An overview of reservoir sedimentation processes, and models of reservoir and shallow water bodies is provided in this article. More research in the developing fields is advised for continuing studies on reservoir sedimentation due to climate change effects

Modified structure along latent tracks and track formation process have been investigated in poly(allyl diglycol carbonate), PADC, which is well recognized as a sensitive etched track detector. This knowledge is essential to develop novel detectors with improved track registration property. The track structures of protons and heavy ions (He, C, Ne, Ar, Fe, Kr and Xe) have been examined by means of FT-IR spectrometry, covering the stopping power region between 1.2 to 12,000 eV/nm. Through a set of experiments on low-LET radiations – such as gamma ray -, multi-step damage process by electron hits was confirmed in the radiation-sensitive parts of the PADC repeat-unit. From this result, we unveiled for the first-time the layered structure in tracks, in relation with the number of secondary electrons. We also proved that etch pit was formed when at least two repeat-units were destroyed along the track radial direction. To evaluate the number of secondary electrons around tracks, a series of numerical simulations were performed with Geant4-DNA. Therefore, we are proposing new physical criterions to describe the detection thresholds. Futhermore, we propose a present issue of the definition of detection threshold for semi-relativistic C ions. And as a possible chemical criterion, formation density of hydroxyl group is suggested to express the response of PADC.

This paper investigates the relationship between public debt and economic growth in the context of a panel kink regression with latent group structures. The proposed model allows us to explore the heterogeneous threshold effects of public debt on economic growth based on unknown group patterns. We propose a least squares estimator and demonstrate the consistency of estimating group structures. The finite sample performance of the proposed estimator is evaluated by simulations. Our findings reveal that the nonlinear relationship between public debt and economic growth is characterized by a heterogeneous threshold level, which varies among different groups, and highlight that the mixed results found in previous studies may stem from the assumption of a homogeneous threshold effect.

Probabilistic latent semantic analysis is a statistical technique developed for information retrieval and spanned many fields. It yields intuitive and solid results. However, the rigidity of the assumptions and the iterative nature derived from the Expectation-maximization algorithm generate several problems, dividing detractors and enthusiasts. In this manuscript, we first describe the Probabilistic latent semantic analysis. After, we discuss reformulations that attempt to solve these problems. We pay special attention to the works relating Probabilistic latent semantic analysis and the Singular value decomposition Theorem. Also, Probabilistic latent semantic analysis can be the basis for other techniques, such as kernelization or probabilistic transfer learning, and those that extend the descriptive character of the Principal component analysis to an inferential tool and open a window of opportunities.

Toxoplasmosis is a neglected anthropozoonosis caused by the obligate intracellular protozoan, Toxoplasma gondii. The role of non-human primates in the epidemiology of human toxoplasmosis is not clear. Acute and highly fatal cases of toxoplasmosis are frequently reported in new world monkeys and asymptomatic infections in old world monkeys. Here we report detection of latent natural T. gondii infection in olive baboons during a screening exercise to select animals for an experimental toxoplasmosis study. Archived serum samples from 32 olive baboons (Papio anubis), 23 wild caught and nine colony-born, were screened for T. gondii DNA using nested PCR. Eighteen (56.25%) samples were from females and fourteen (43.75%) from males. Toxoplasma gondii DNA was detected in 21 (65.6%) baboons. 13 females (40. 6%) and eight males (25%). Five baboons (24%) which tested positive were from the Institute of Primate Research colony but there was no statistical significance between them and the wild trapped (p=0.453). There was neither statistical significance (p=0.373) between sex and infection status nor between area of origin and infection status (p>0.05). These results indicate that olive baboons get infected with T. gondii in the wild and during captivity and may be significant reservoirs of human infections, especially where they may be trapped for bushmeat. We recommend a country-wide study to establish true prevalence of toxoplasmosis among non-human primates and identify associated parasite strains.

Thermophysical characterization of three paraffin waxes (RT27, RT21 and RT35HC) is carried out in this study using DSC, TGA and transient plane source technics. Then, a numerical study of their melting in a rectangular enclosure is examined. The enthalpy-porosity approach is used to formulate this problem in order to understand the heat transfer mechanism during the melting process. The analysis of the solid-liquid interface shape, the temperature field shows that the conduction is the dominant heat transfer mode in the beginning of the melting process. It is followed by a transition regime and the natural convection becomes the dominant heat transfer mode. The effects of the Rayleigh number and the aspect ratio of the enclosure on the melting phenomenon are studied and it is found that the intensity of the natural convection increases as the Rayleigh number is higher and the aspect ratio is smaller. In the second part of the numerical study, a comparison of the performance of paraffins waxes during the melting process is conducted. Results reveals that from a kinetically RT21 is the most performant but in term of heat storage capacity, it was inferred that RT35HC is the most efficient PCM.

The aim of this study was to use latent profile analysis to identify specific profiles of burnout syndrome in combination with work engagement and to identify whether job satisfaction, psychological well-being, and other sociodemographic and work variables affect the probability of presenting a profile of burnout syndrome and low work enthusiasm. A total of 355 healthcare professionals completed the Spanish Burnout Inventory, the Utrecht Work Engagement Scale, the Job Satisfaction Scale, and the Psychological Well-Being Scale for Adults. Latent profile analysis identified 4 profiles: 1) burnout with high indolence (BwHIn); 2) burnout with low indolence (BwLIn); 3) high engagement, low burnout (HeLb); and 4) in the process of burning out (IPB). Multivariate logistic regression showed that a second job in a government health care institution; a shift other than the morning shift; being divorced, separated or widowed; and work load are predictors of burnout profiles with respect to the HeLb profile. These data are useful for designing intervention strategies according to the needs and characteristics of each type of burnout profile.

The formation of hydrogen sulfide (H₂S) in petroleum reservoirs by anaerobic microbial activity is called biogenic souring of reservoirs and is a risk in the oil and gas industry as the compound is extremely toxic, flammable and corrosive. In this paper, we present a workflow and the tools to assess biogenic souring from a pragmatic engineering perspective. The retention of H₂S in the reservoir due to the reactions with iron-bearing rock minerals (e.g. siderite) is shown in a theoretical approach here and supported with literature data. Cases are given for two fields under secondary (waterflooding) and tertiary flooding with microbial enhanced oil recovery (MEOR). The use of the Monte Carlo method as a numerical modelling tool to incorporate uncertainties in the measured physical/chemical/ biochemical data is demonstrated as well. A list of studies conducted with different chemicals alone or in combination with various biocides to mitigate biogenic souring provides an overview of potential inhibitors as well as possible applications. Furthermore, the results of static and dynamic inhibition tests using molybdate are presented in more detail due to its promising mitigation ability. Finally, a three-step workflow for the risk assessment of biogenic souring and its possible mitigation is presented and discussed.

The chemically synthesized polymer polyacrylamide (HPAM) in conventional reservoirs has achieved excellent oil displacement, but its oil displacement is poor in extreme reservoir environments. To develop biopolymer oil flooding agent under extreme reservoir conditions, the viscosity increasing and rheological properties of three biopolymers, diutan gum, xanthan gum, and scleroglucan, were studied under extreme reservoir conditions (high salt, high temperature, strong acid, and alkali), and the effects of temperature, mineralization, pH, and other factors on their viscosities and long-term stability properties were analyzed and compared. The results showed that under the temperature of 90℃ and below, the three kinds of biopolymers had the best viscosity-increasing ability. The viscosity of the three kinds of biopolymers was 80.94, 11.57, and 59.83mPa·s, respectively, when the concentration was 1500mg/L and the salinity was 220g/L. At the shear rate of 250s-1,100℃~140℃, scleroglucan has the best viscosification. At 140℃, the solution viscosity is 19.74mPa·s, and the retention rate can reach 118.27%. The results of the long-term stability study showed that the solution viscosity of scleroglucan with mineralization level of 220 mg/L was 89.54% viscosity retention in 40 days, and the diutan gum could be stabilized for 10 days, and the viscosity was maintained at 90 mPa·s. All three biopolymers are highly acid and alkali-resistant, with viscosity variations of less than 15% in the pH3~10 range. Rheological tests have shown that both of them have better viscoelastic properties than xanthan gum due to the peculiar double-helix structure of xanthan gum and the rigid triple-helix structure of scleroglucan. Therefore, the two biopolymers, diutan gum, and scleroglucan have the potential for extreme reservoir oil displacement applications, and it is recommended to use diutan gum for oil displacement in reservoirs up to 90℃ and scleroglucan for oil displacement in reservoirs between 100℃ and 140℃.

Using the fluorescent method in the modification of Krasnoyarsk State University, we study development (as chlorophyll content, ∑CHL) and photosynthetic activity of phytoplankton in seven large flat reservoir of the Volga River cascade (Russia) in August 2915–2017. In period of maximal warming of water, average ∑CHL varied in limits of 19.4–33.7 μg L–1 in the Upper Volga, 8.5–27.8 μg L–1 in the Middle Volga, and 5.2–11.3 μg L–1 in the Lower Volga. Photosynthetic activity coefficient (PhAC) varied mostly in limits of 0.12–0.59 with average of 0.22–0.38 and only in 2017 decreased to minimal <0.10 and average <0.20. The average PhAC values shows the normal physiological state of the phytoplankton of the Upper Volga during all periods of observation, occasional decrease of PhAC in the Middle Volga, and low photosynthetic activity in the Lower Volga. A decrease in the average ∑Chl and PhAC in 2017 was under cyclonic windy weather with a large amount of precipitation, low solar radiation, and large volume of flow. Trend towards a decrease in ∑CHL, like decrease in PhAC from the Upper Volga to the Lower Volga is explained by increasing in the flow rate and volume of runoff downstream the Volga River.

As a result of the COVID 19 outbreak that has affected the whole world, teacher leadership has gained more significance. Teacher leadership is a multidimensional concept. While some teachers exercise leadership only at the classroom level, others exercise leadership at macro level. This level of leadership enactment is directly related to how teachers construct their professional identity in relation to leadership. This study aims to explore the leadership-related professional identities of teachers who came to the fore especially during the COVID 19 pandemic period by using the latent profile analysis method. The data were collected a sample of 710 teachers. Teachers completed Teacher Leadership Behavior Scale that measures teacher leadership behaviors at four levels: classroom, parental, micro-level, macro-level. Participants also completed Rosenberg Self-Esteem Scale, Teacher Self-Efficacy Scale, Openness to Authority Scale, and Job Satisfaction Scale. As a result of latent profile analysis, three distinct profiles of teacher leadership identity emerged: those who exercise leadership at a minimum level, an intermediate level and a maximum level across all four levels of teacher leadership. These profiles were labeled as "extended professionality," "intermediate professionality," and "restricted professionality," drawing upon Hoyle's (1974) conceptualization of teacher professional identity. These findings suggest that teachers construct their identity differently about teacher leadership. It is essential for school leaders to first explore those different levels of professional identity and tailor their professional development activities accordingly.

CO₂ enhanced oil recovery (EOR) has been proven its capability to explore the unconventional tight oil reservoirs and potential for geological carbon storage. Meanwhile, the extremely low permeability pores exaggerate the difficulty CO₂ EOR and geological storage processing in the actual field. This paper initiates the ultrasonic-assisted approach to facilitate the oil-gas miscibility development and finally contribute to unlock more tight oils. First, the physical properties of crude oil with and without ultrasonic treatments were experimentally analysed through gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR) and viscometer. Second, the oil-gas minimum miscibility pressures (MMPs) were measured from the slim-tube test and the miscibility developments with and without ultrasonic treatments were interpreted from the mixing-cell method. Third, the nuclear-magnetic resonance (NMR) assisted coreflood tests were conducted to physically model the recovery process in porous media and directly obtain the recovery factor. Basically, the ultrasonic treatment (40KHz and 200W for 8 hours) was found to substantially change the oil properties, with viscosity (at 60°C) reduced from 4.1 to 2.8mPa·s, contents of resin and asphaltene decreased from 27.94% and 6.03% to 14.2% and 3.79%, respectively. The FTIR spectrum shows the unsaturated C-H bond, C-O bond and C≡C bond in macromolecules were broken from ultrasonic, which caused the macromolecules (e.g., resin and asphaltenes) to be decomposed into smaller carbon-number molecules. Accordingly, the MMP was determined to be reduced from 15.8 to 14.9MPa from the slim-tube test and the oil recovery factor increased by over 10%. This study reveals the mechanisms of ultrasonic-assisted CO₂ miscible EOR in producing tight oils.

E-scooters are a micromobility transportation option for completing short trips. In recent years, many ‎cities welcomed shared e-scooters in an effort to offer more mode choices, increase travelers' ‎convenience, and reduce automobile use in their service areas. However, a knowledge gap still remains ‎regarding the acceptability of shared e-scooters as a transportation option, which motivates additional ‎research on user and non-user preferences and attitudes toward e-scooter use. This study investigates ‎latent variables impacting the adoption of shared e-scooters in urban areas, focusing on mode choice ‎factors and attitudes towards e-scooter use and car use. The study utilizes machine learning (ML) ‎techniques and SHAP analysis to analyze survey data (N=1196) collected from travelers in Washington, ‎D.C., Miami, FL, and Los Angeles, CA, in 2021 and 2022. A comparative analysis is performed to develop ‎comprehensive demographic profiles of e-scooter users. The analysis reveals gender (male), age (25-39 ‎years age group), higher income, and educational background as the most relevant factors toward e-‎scooter use. Attitudinal variations among e-scooter users and non-users underscore the complexity of ‎perceptions toward e-scooter use, with significant differences in mode choice factors and attitudes ‎toward the use of e-scooters and private vehicles. Notably, educational background ranked as a significant ‎factor in Washington, D.C., and Miami, while Factor 3, derived from factor analysis and encompassing car ‎use attitudes and the utilization of technology, emerged as influential in Los Angeles. This research ‎contributes fresh insights into factors shaping e-scooter adoption, offering a foundation for informed ‎urban transportation planning and policymaking. The holistic approach showcased in this study enhances ‎understanding of shared micromobility and its implications for urban mobility.

China is rich in coal resources under water bodies. However, for a long time, the safety prediction of high-intensity mining under water bodies is one of the problems encountered by the coal industry. It is of great significance to realize safe mining under water bodies, improve the recovery rate of coal resources and protect reservoir resources. Therefore, this article takes the No. 5 coal seam and No. 11 mining area of Wangwa Coal Mine as the research object, and integrates physical simulation, numerical simulation, theoretical analysis and other methods to study the development height of water-conducting fracture zones in fully mechanized top coal caving mining. Solid-liquid coupling physical simulation test reveals the failure characteristics of overlying strata in goaf and the seepage law of reservoir water under the influence of mining. By comparing the monitoring data of borehole leakage, the measured data obtained by borehole peeping with the height data of water-conducting fracture zone obtained by the traditional empirical formula of three-under standard, the error between the two is as high as -29.39 %. In this case, the variance correction coefficient is used to correct the empirical formula, and on this basis, in order to effectively protect the surface water dam and water body, the mining height of coal seam in the working face with limited height mining is inversely derived. The research results provide a basis for the safety prediction of high-intensity mining under the reservoir dam in the ecologically fragile areas of western China and provide a scientific guarantee for the formulation of safety measures under such conditions.

With the popularization of natural gas and the requirements for environmental protection, the development and utilization of natural gas is particularly important. The status of natural gas in China's oil and gas exploration and development is constantly improving, and the country is paying more and more attention to the exploitation and utilization of natural gas. The Upper Paleozoic tight sandstone in the Ordos Basin is characterized by low porosity, low permeability and large area of concealed gas reservoirs. By injecting CO2 into the formation, the recovery of natural gas can be improved, and at the same time, the stable storage of CO2 can be achieved to achieve a win-win situation of CO2 emission reduction and utilization. Injecting greenhouse gas CO2 into gas reservoirs for storage and improving recovery has also become a hot research issue. In order to improve the recovery efficiency of tight sandstone gas reservoir, this paper takes the complex tight sandstone of Upper Paleozoic in Ordos Basin as the research object, through indoor physical simulation experiments, carried out the influence of displacement rate, fracture dip angle, core permeability, core dryness and wetness on CO2 gas displacement efficiency and storage efficiency, and analyzed the influence of different factors on CO2 gas displacement efficiency and storage efficiency to improve the recovery and storage efficiency. The research results show that under different conditions, when the CO2 injection pore volume is less than 1PV, the relationship between the CH4 recovery rate and the CO2 injection pore volume is linear, and the tilt angle is 45 °. When the CO2 injection pore volume exceeds 1PV, the CH4 recovery rate increases slightly with the increase of displacement speed, the recovery rate of CO2 displacement CH4 is between 87% - 97%, and the CO2 breakthrough time is 0.7PV-0.9PV. In low-permeability and low-speed displacement cores, the diffusion of CO2 molecules is more significant. The lower the displacement speed is, the earlier the breakthrough time of CO2 is, and the final recovery of CH4 slightly decreases. Gravity has a great impact on CO2 storage and enhanced recovery. The breakthrough of high injection and low recovery of CO2 is earlier, and the recovery of CH4 is about 3.3% lower than that of low injection and high recovery. The bound water makes the displacement phase CO2 partially dissolved in the formation water, and the CO2 breakthrough lags about 0.1PV. Ultimately, CH4 recovery factor and CO2 storage rate are higher than those of dry core displacement. The research results provide theoretical data support for CO2 injection to improve recovery and storage efficiency in complex tight sandstone gas reservoirs.

This study introduces session-aware recommendation models, leveraging GRU (Gated Recurrent Unit) and attention mechanisms for advanced latent interaction data integration. A primary ad-vancement is enhancing latent context, a critical factor for boosting recommendation accuracy. We address existing models' rigidity by dynamically blending short-term (most recent) and long-term (historical) preferences, moving beyond static period definitions. Our approaches, pre-combination (LCII-Pre) and post-combination (LCII-Post) with fixed (Fix) and flexible learning (LP) weight configurations, are thoroughly evaluated. We conducted extensive experiments to as-sess our models' performance on public datasets such as Amazon and MovieLens 1M. Notably, on the MovieLens 1M dataset, LCII-PreFix achieved a 1.85% and 2.54% higher Recall@20 than II-RNN and BERT4Rec+st+TSA, respectively. On the Steam dataset, LCII-PostLP outperformed these models by 18.66% and 5.5%. Furthermore, on the Amazon dataset, LCII showed a 2.59% and 1.89% improvement in Recall@20 over II-RNN and CAII. These results affirm the significant enhancement our models bring to session-aware recommendation systems, showcasing their po-tential for both academic and practical applications in the field.

In this article, the quality of water in the reservoirs of Lake Arpi, Lake Yerevan, Akhuryan, Azat, Aparan and Kechut was estimated with usage of the Armenian Water Quality Index. It was established that in the waters of reservoirs the the maximum permissible concentration of copper, vanadium, aluminum, chromium, manganese, iron, NH4+ and NO2- regularly increases. The following computational algorithm was used for determination of the Armenian Water Quality Index values: to determine the number of cases of MPC excess of i-substance or indicator of water –n; to estimate the total amount of cases of the maximum permissible concentration (N) – N = ∑n; to computes log2N, nlog2n and ∑nlog2n; to determine geoecological syntropy (I) and entropy (H): I = ∑ nlog2n/N and H = log2N – I. Then, Geo-Ecological Evolving Organized index index was determined: G = H/I. Further, the total amount multiplicity of MAC exceedances was estimated: (M) - M=∑m and log2M was computed. Finally, Armenian Water Quality Index was obtained: AWQI = G + 0.1log2M. It was established that the Armenian Water Qquality Index showed a linear dependence on the Water Contamination Index, the Specific Combinatory Water Quality Index, the Geo-Ecological Evolving Organized index and an inverse dependence on the Canadian Water Quality Index.

Reservoirs are characterized by accumulation of sediments where micropollutants may concentrate, with potential toxic effects on downstream river ecosystems. However, sediment management such as flushing is needed to maintain storage capacity. Climate change is expected to increase sediment loads, but potential effects on their quality are scarcely known. In this context, sediment contamination by trace elements (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) and organics (PAHs, PCBs, C>12) was analyzed in 20 reservoirs located in Italian Central Alps. A strong As and a moderate Cd, Hg and Pb enrichment was emphasized by Igeo, with potential ecotoxicological risk according to PEC quotients. Siltation, granulometry, total organic carbon (TOC) and altitude resulted as the main drivers governing pollutant concentrations in sediments. According to climate change models, expected increase of rainfall erosivity will enhance soil erosion and consequently the sediment flow to reservoirs, potentially increasing coarse grain fractions and thus potentially diluting pollutants. Conversely, increased weathering may enhance metal fluxes to reservoirs. Increased vegetation cover will potentially result in higher TOC concentrations, which may contrast contaminant bioavailability and thus toxicity. Our results may provide elements for a proper management of contaminated sediments in a climate change scenario aiming at preserving water quality and ecosystem functioning.

Despite its remote discovery (1977) and numerous reports of its presence in vari-ous plant species in many countries, the available molecular information for the artichoke Italian latent virus (AILV) is still limited to a single complete genome sequence (RNA1 and 2) isolate from grapevine (AILV-V) and to a partial sequence portion from RNA2 of an isolate of unknow origin and host, both reported in the GenBank. Here we report the results of molecular analyses conducted on RNA2 of AILV isolates, sequenced for the first time in this study, together with the first-time finding of AILV in a new host plant species, i.e., chard (Beta vulgaris subsp. vulgaris). The different AILV isolates sequenced are from artichoke (AILV-C), gladiolus (AILV-G), sonchus (AILV-S) and chard (AILV-B). At the bio-logical level, the AILV-B was found to be involved with vein clearing and mott-ling symptoms on chard leaves. At the molecular level, sequencing results of RNA2 segments showed that AILV-C, AILV-G, AILV-S and AILV-B were 4,629 nt in length (excluding the 3’ terminal polyA tail), hence one nt shorter than that of AILV-V reported in the GenBank. The comparative sequence analysis between the CR of RNA2 of all isolates showed that AILV-V was the most variable isolate, with the lowest sequence identities of 83.2% and 84.7% at the nucleotides and amino acids levels, respectively. Putative intra-species sequence recombination sites were predicted among the AILV isolates, of which the AILV-V, AILV-C and AILV-B genomes were found to be mostly involved. This study adds further mo-lecular information on the previously unrecorded high genomic variability of the Nepoviruses of subgroup B, together with information on recombinations that may have conditioned the infection and transmission of AILV in nature; thus learning the way forward to design a new integrated pest management of chard plantation.

The work analyses the way in which symptoms and life themes manifest in middle-aged adults diagnosed with major recurrent depression. Specifically, the relationships between symptoms, life themes, and life themes - symptoms have been analyzed. For this purpose, Spearman correlation, and the methods of Latent Semantic Indexing (LSI) were used. Seven symptoms and twenty-six life themes were identified in the patients analyzed as well as similarities of symptoms/life themes (at patient level), the ranking of the importance of symptoms on each life theme (at the level of the group of patients), the rankings of the similarities of life themes in relation to different symptoms or various groups of symptoms (at the level of the group of patients), and dysfunctional cycles of symptoms and life themes (at patient level). The findings only refer to the patients analyzed. Although our findings cannot be generalized, there is a possibility that some of them may also be encountered in other patients. However, the design of the work can be used to initiate other similar studies.

The devastating COVID-19 pandemic forced academia to go virtual. Educational institutions around the world have stressed online learning programs in the aftermath of the pandemic. However, because of insufficient access to ICT, a substantial number of students failed to harness the opportunity of online learning. This study explores the latent digital divide exhibited during the COVID-19 pandemic while online learning activities are emphasized among Bangladeshi students. It also investigates the digital divide exposure and the significant underlying drivers of the divide. A cross-sectional survey was employed to collect quantitative data mixed with open-ended questions to collect qualitative information from the student community. The findings revealed that despite the majority of students have physical access to ICT but only 32.5% of students could attend online classes seamlessly, 34.1% of the students reported the data prices as the critical barrier, and 39.8% of students identified the poor network infrastructure is the significant barrier for them to participate in online learning activities. Although most students possess physical access to the device and the Internet, they face the first-level digital divide due to the quality of access and maintaining subscriptions. Consequently, they fail to take advantage of physical access, resulting in the third-level digital divide (Utility Gap) and submerging them into a digital divide cycle. This paper aimed to explore the underlying issues of the digital divide among Bangladeshi students to assist relevant stakeholders (e.g., the Bangladesh government, Educational Institutions, Researchers) in providing the necessary insights and theoretical understanding to arrange adequate support for students to undertake conducive online learning activities.

This article shows that the recently proposed latent D-scoring model of Dimitrov is statistically equivalent to the two-parameter logistic item response model. An analytical derivation and a numerical illustration are employed for demonstrating this finding. Hence, estimation techniques for the two-parameter logistic model can be used for estimating the latent D-scoring model. In an empirical example using PISA data, differences of country ranks are investigated when using different metrics for the latent trait. In the example, the choice of the latent trait metric matters for the ranking of countries. Finally, it is argued that an item response model with bounded latent trait values like the latent D-scoring model might have advantages for reporting results in terms of interpretation.

Climate change in the coming decades could intensify extreme events such as severe droughts. Combined with the possible increase of water demands, these changes exert a large pressure on the water systems. In order to confirm this assumption, a set of scenarios was proposed in this study to consider the combined impact of climate changes and the increase in water demand on the main multiple-use reservoirs of São Francisco River, Brazil. For this purpose, five CMIP6 climate models were used considering two greenhouse gas emissions scenarios: the SSP2-4.5 and SSP5-8.5. The naturalized and withdraw streamflows were estimated to the adopted reser-voirs considering all existing, new and projected demands. The conjunction of scenarios indicat-ed an increase in Potential Evapotranspiration, a possible significant reduction in water availa-bility, a growth in water demand mainly for irrigation and a substantial reduction in the perfor-mance of the evaluated reservoirs.

The last series of Raven's standard progressive matrices (SPM-LS) test were studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCM). For dichotomous item response data, an alternative estimation approach for RLCMs is proposed. For polytomous item responses, different alternatives for performing regularized latent class analysis are proposed. The usefulness of the proposed methods is demonstrated in a simulated data illustration and for the SPM-LS dataset. For the SPM-LS dataset, it turned out the regularized latent class model resulted in five partially ordered latent classes.

Tuberculosis (TB) is the primary cause of death by a single infectious agent; responsible for around two million deaths in 2016. A major virulence factor of TB is the ability to enter a latent or Non-Replicating Persistent (NRP) state which is presumed untreatable. Approximately, 1.7 billion people are latently infected with TB and on reactivation many of these infections are drug resistant. As the current treatment is ineffective and diagnosis remains poor, millions of people have the potential to reactivate into active TB disease. The immune system seeks to control the TB infection by containing the bacteria in a granuloma, where it is exposed to stressful anaerobic and nutrient deprived conditions. It is thought to be these environmental conditions that trigger the NRP state. A number of in vitro models have been developed that mimic conditions within the granuloma to a lesser or greater extent. These different models have all been utilised for the research of different characteristics of NRP Mycobacterium tuberculosis, however their disparity in approach and physiological relevance often results in inconsistencies and a lack of consensus between studies. This review provides a summation of the different NRP models and a critical analysis of their respective advantages and disadvantages relating to their physiological relevance.

Data-driven models (DDMs) are extensively used in environmental modeling but face challenges due to limited training data and potential results not adhering to physical laws. To address this challenge, this study developed a process-guided deep learning (PGDL) model, integrating a long short-term memory (LSTM) neural network and a process-based model (PBM), CE-QUAL-W2 (W2), to predict water temperature in a stratified reservoir. The PGDL included an energy constraint term from W2's thermal energy equilibrium into the cost function of the LSTM, besides the mean square error term. In PGDL, parameters were optimized by penalizing deviations from the energy law, ensuring adherence to physical constraints. Compared to LSTM, PGDL demonstrated enhanced satisfaction with the energy balance and superior performance in water temperature prediction. Even with less field data for training, PGDL outperformed both LSTM and calibrated W2 after pre-training with data generated using the uncalibrated W2. Therefore, integration of DDM with a PBM ensured physical consistency in water temperature prediction for complex stratified reservoirs with limited data. Moreover, pre-training the PGDL with PBM proved highly effective in mitigating bias and variance due to insufficient field measurement data.

Microorganisms inhabiting subsurface petroleum reservoirs are key players in biochemical transformations. The interactions of microbial communities in these environments are highly complex and still poorly understood. This work aimed to assess publicly available metagenomes from oil reservoirs and implement a robust pipeline of genome-resolved metagenomics to deci-pher metabolic and taxonomic profiles of petroleum reservoirs worldwide. Analysis of 301,2 Gb of metagenomic information derived from heavily flooded petroleum reservoirs in China and Alaska to non-flooded petroleum reservoirs in Brazil enabled us to reconstruct 148 MAGs of high and medium quality. At the phylum level, 74% of MAGs belonged to bacteria and 26% to ar-chaea. The profiles of these MAGs were related to the physicochemical parameters and recovery management applied. The analysis of the potential functional core in the reservoirs showed that the microbiota was specialized for each site, with 31.7% of the total KEGG orthologies annotated as functions (1,690 genes) common to all oil fields, while 18% of the functions were site-specific, i.e., present only in one of the oil fields. The oil reservoirs with lower level of intervention were the most similar to the potential functional core, while the oil fields with longer history of water in-jection had greater variation in functional profile. These results show how key microorganisms and their functions respond to the distinct physicochemical parameters and interventions of the oil field operations such as water injection and expand the knowledge of biogeochemical trans-formations in these ecosystems.

For the purpose of clean energy hydropower development, the construction of reservoirs has been continuously promoted in the Jinsha River basin for many years, and how the reservoirs affect the water and sediment process is a very necessary topic to study. This study is based on the gauged water and sediment data (span from the 1960’s to 2020) at Shigu, Panzhihua, and Xiangjiaba stations downstream located in the trunk channel of the river, and uses Mann-Kendall trend test method and double cumulative curve method to comprehensively judge the variation trends of runoff and suspended sediment load and reveal their credible mutation years. The linear regression method is used to reveal the variation characteristics of the relationship between water and sediment before and after the abrupt change years. The results show that the variations in runoff at Shigu and Panzhihua stations have significant and relatively obvious increasing trends, respectively, and that at Panzhihua station has a mutation year of 1985. The runoff at Xiangjiaba Station slightly increased but not significantly. The variation of suspended sediment load showed a temporal and spatial differentiation. The variation of sediment discharge at Shigu Station showed an increasing trend with a mutation year of 1997. For Panzhihua Station, it showed an increasing trend before 1998, but has significantly decreased since 1998. The fluctuation of sediment transport at Xiangjiaba Station was significant before 1998, but the trend is unclear. In the period of 1998−2020, it showed a significant decreasing trend, especially since 2013, when the mean annual suspended sediment load only accounted for 0.61% of its multi-year average. The variations of mean annual sediment concentration and sediment inflow coefficient at the hydrological stations is consistent with the variation trend of sediment transport. Before 2013, the correlation between water and sediment was strong, but thereafter it was extremely weak. The two sudden years of 1998 and 2013 are consistent with the year when large reservoirs were built in the river basin. The construction of large reservoirs and their large amount of sediment retention are the key reasons for the sudden changes in the water-sediment relationship and the sharp decrease in sediment transport in the downstream reach of the reservoir dam. The climate and underlying surface changes in the study area are not significant, and their impact on the water and sediment processes in the watershed is limited.

We present a generic and open-source framework for the numerical modeling of the expected transport and storage mechanisms in unconventional gas reservoirs. These unconventional reservoirs typically contain natural fractures at multiple scales. Considering the importance of these fractures in shale gas production, we perform a rigorous study on the accuracy of different fracture models. The framework is validated against an industrial simulator and is used to perform a history-matching study on the Barnett shale. This work presents an open-source code that leverages cutting-edge numerical modeling capabilities like automatic differentiation, stochastic fracture modeling, multi-continuum modeling and other explicit and discrete fracture models. We modified the conventional mass balance equation to account for the physical mechanisms that are unique to organic-rich source rocks. Some of these include the use of an adsorption isotherm, a dynamic permeability-correction function, and an embedded discrete fracture model (EDFM) with fracture-well connectivity. We explore the accuracy of the EDFM for modeling hydraulically-fractured shale-gas wells, which could be connected to natural fractures of finite or infinite conductivity, and could deform during production. Simulation results indicates that although the EDFM provides a computationally efficient model for describing flow in natural and hydraulic fractures, it could be inaccurate under these three conditions: 1. when the fracture conductivity is very low. 2. when the fractures are not orthogonal to the underlying Cartesian grid blocks, and 3. when sharp pressure drops occur in large grid blocks with insufficient mesh refinement. Each of these results are very significant considering that most of the fluids in these ultra-low matrix permeability reservoirs get produced through the interconnected natural fractures, which are expected to have very low fracture conductivities. We also expect sharp pressure drops near the fractures in these shale gas reservoirs, and it is very unrealistic to expect the hydraulic fractures or complex fracture networks to be orthogonal to any structured grid. In conclusion, this paper presents an open-source numerical framework to facilitate the modeling of the expected physical mechanisms in shale-gas reservoirs. The code was validated against published results and a commercial simulator. We also performed a history-matching study on a naturally-fractured Barnett shale-gas well considering adsorption, gas slippage & diffusion and fracture closure as well as proppant embedment, using the framework presented. This work provides the first open-source code that can be used to facilitate the modeling and optimization of fractured shale-gas reservoirs. To provide the numerical flexibility to accurately model stochastic natural fractures that are connected to hydraulically-fractured wells, it is built atop other related open-source codes. We also present the first rigorous study on the accuracy of using EDFM to model both hydraulic fractures and natural fractures that may or may not be interconnected.

Patients with heart failure have difficulty in self-care management, as daily monitoring and recognizing symptoms do not readily trigger an action to avoid hospital admissions. The purpose of this study was to understand the impact of a nurse-led complex intervention on symptom recognition and fluid restriction. A latent growth model was designed to estimate self-care management and quality of life changes on patients with heart failure and assessed by a pilot study, for three months, to sixty-three patients (33 control, 30 intervention). Patients in the control group had a higher risk of hospitalisation (IRR 11.36; p<.001) and emergency admission (IRR 4.24; p<.001) at three-months follow-up. Analysis of the time scores demonstrated that the intervention group had a clear improvement in self-care behaviours (βSlope. Assign-ment_group=-.881; p<.001) and in the quality of life (βSlope. Assignment_group=1.739; p<.001). This study supports that a nurse-led program on symptom recognition and fluid restriction can have a positive impact on self-care behaviours and quality of life in patients with heart failure.

The research presents the Methodology of Improving the Accuracy in Text Classification in Light of Modelling the Latent Semantic Relations (LSR). The aim of this Methodology is to find the ways of eliminating the Limitations of Discriminant and Probabilistic methods for LSR revealing and customizing the Text Classification Process to the more accurate recognition of the text tonality. This aim should be achieved by using the knowledge about the text’s Hierarchical Semantic Context in the form of Corpora-based Hierarchical Sentiment Dictionary. The main scientific contribution of this research is the following set of approaches to improve the qualitative characteristics of Text Classification process: combination of the Discriminant and Probabilistic methods allowing to decrease the influences of the Limitations of these methods on the LSR revealing process; considering each document as a complex structure allowing to estimate documents integrally by separated classification of topically completed textual component (paragraphs); taking into account the features of Argumentative type of documents (Reviews) allowing to use the author’s subjective evaluation of text tonality for development the Text Classification methodology. Tonality, expressed by the Review’s author, has a significant, but not critical, effect on the qualitative indicators of Sentiment Recognition.

Leak of carbon dioxide (CO2) from conventional underground carbon storage reservoirs is an increasing concern. It is highly desirable to inject CO2 into low-temperature reservoirs so that CO2 can be locked inside the reservoir in solid state as CO2-hydrates. Marine gas hydrate reservoirs and surrounding water aquifers are attractive candidates for this purpose. However, the nature of low-permeability of these marine sediments hinders injection of CO2 in commercial scale due to the low-injectivity of wells with conventional completions. This study investigates injection of CO2 into the low-permeability marine reservoirs using a new type of well namely radial-lateral wells (RLW). An analytical model was developed for predicting CO2 injectivity of the RLW to assess well injectivity improvement. A case study and sensitivity analysis were performed with field data from the South China Sea. Result of analysis reveals that the injectivity of the RLW is nearly proportional to reservoir permeability, lateral wellbore length, and number of laterals. CO2 injection rate is predicted to be 19 tons/day to 250 tons/day, which is 3 to 15 times higher than the injectivity of frac-packed wells. It is feasible to inject CO2 into the low-permeability-low-temperature marine reservoirs at commercial flow rates. This work provides an analytical tool to predict CO2-injectivity of RLW in low-temperature marine reservoirs for leak-free CO2 storage.

HIV-1 protease (PR) is a viral enzyme that cleaves viral polyprotein precursors to convert them into functional forms, a process essential to generate infectious viral particles. Due to its broad substrate specificity, HIV-1 PR can also cleave certain host cell proteins. Several studies have identified host cell substrates of HIV-1 PR and described the potential impact of their cleavage on HIV-1-infected cells. Of particular interest is the interaction between PR and the caspase recruitment domain-containing protein 8 (CARD8) inflammasome. While PR typically has low levels of intracellular activity prior to viral budding, induction of premature PR activation to trigger CARD8-mediated cell killing may help eliminate latent reservoirs in people living with HIV. In this review, we discuss the viral and host substrates of HIV-1 protease and highlight potential applications and advantages of targeting CARD8 sensing of HIV-1 PR.

Especially for drought periods, the higher the accuracy of reservoir inflow forecasting, the more reliable the water supply from a dam. The article focuses on probabilistic forecasting of seasonal inflow to reservoirs and determines estimates from the probabilistic seasonal inflow according to drought forecast results. The probabilistic seasonal inflow was forecasted by a copula-based Bayesian network employing a Gaussian copula function. Drought forecasting was performed by calculation of the standardized streamflow index value. The calendar year is divided into four seasons; the total inflow volume of water to a reservoir for a season is referred to as the seasonal inflow. Seasonal inflow forecasting curves conforming to drought stages produce estimates of probabilistic seasonal inflow according to the drought forecast results. The forecasted estimates of seasonal inflow were calculated by using the inflow records of Soyanggang and Andong dams in the Republic of Korea. Under the threshold probability of drought occurrence ranging from 50 to 55 %, the forecasted seasonal inflows reasonably matched critical drought records. Combining the drought forecasting with the seasonal inflow forecasting may produce reasonable estimates of drought inflow from the probabilistic forecasting of seasonal inflow to a reservoir.

Multi-step ahead streamflow forecasting is of practical interest for the operation of hydropower reservoirs. We provide generalized results on the error evolution in multi-step ahead forecasting by conducting several large-scale experiments based on simulations. We also present a multiple-case study using monthly time series of streamflow. Our findings suggest that some forecasting methods are more useful than others. However, the errors computed at each time step of a forecast horizon within a specific case study strongly depend on the case examined and can be either small or large, regardless of the forecasting method used and the time step of interest.

This research paper aims to examine the various aspects of cryptocurrencies, from their inception to their current status in the financial market, using a multidisciplinary approach that incorporates mathematical and psychological methods to explore the factors that contribute to the success of celebrity endorsements and the potential risks associated with them. The first section (1.1) of this research paper will provide an overview of cryptocurrencies, exploring their history, functionality, and impact on the global financial market. This will involve examining the technical details behind cryptocurrencies, such as blockchain technology, and the differences between various types of virtual assets. The research will also discuss the potential advantages and disadvantages of investing in cryptocurrencies, as well as the regulatory challenges they face. The second section (2.1) of the research paper will focus on the psychological aspect of cryptocurrency investing, analyzing the connection between personality traits and the likelihood of purchasing a cryptocurrency based on a celebrity endorsement. This will involve investigating Howard Gardner's theory of multiple intelligences to understand the qualities that make people more susceptible to investing in a cryptocurrency without prior knowledge (Gardner, 1983). The third section (3.1) of the research paper will delve into the mathematical side of cryptocurrency investing, examining the factors that contribute to the success of celebrity endorsements and the artificial growth of cryptocurrencies. This will involve developing software to calculate the artificial growth of a cryptocurrency over a 24-hour period and analyzing the data to understand the underlying factors driving its value. By taking a multidisciplinary approach, this research will shed light on the complexities of investing in virtual assets and help inform investors of the potential risks and benefits of investing in cryptocurrencies through qualitative and quantitative analyses and through the use of a Multi-Level Latent Class Analysis (LCA).

The microscopic pore structure of tight sandstone reservoir significantly influences the characteris-tics of CO2 flooding after water flooding. The research was conducted using various techniques such as casting thin sections, high pressure mercury injection, scanning electron microscopy, Nu-clear magnetic resonance (NMR) testing, and a self-designed high-temperatures and high-pressures microscopic visualization displacement system. Three type cores with different pore structures were selected for the flooding experiments and the microscopic visualization displace-ment experiments, including CO2 immiscible flooding, near-miscible flooding, and miscible flood-ing after the conventional water flooding. The characteristics of CO2 flooding and the residual oil distribution after water flooding were quantitatively analyzed and evaluated. The results show that: (1) During the water flooding process, the oil produced from type I and type III samples mainly comes from large and some medium pores. Oil utilization of all pores is significant for type II samples. The physical properties and pore types have a greater impact on water flooding. Type I and II samples are more suitable for near-miscible flooding after water flooding. Type III samples are more suitable for miscible flooding after water flooding. (2) In the CO2 flooding, oil recovery increases gradually with increasing pressure for all three types of samples. Type II core samples have the highest recovery. Before miscibility, the oil recovered from type I and type II samples was primarily from large pores, however, the oil recovery mainly comes from medium pores when reaching miscibility. As for the type III samples, the oil produced in the immiscible state mainly comes from large and medium pores, and the enhanced oil recovery mainly comes from medium and small pores after reaching the near-miscible phase. (3) It can be seen from the microscopic re-sidual oil distribution that oil recovery will increase as the petrophysical properties of the rock model improve. The oil recovery of near-miscible flooding after water flooding regarding the type II model is up to 68.11%. The oil recovery of miscible flooding after water flooding about type III model is the highest at 74.57%. With increasing pressure, the proportion of flake residual oil grad-ually decreases, while the proportion of droplet-like and film-like residual oil gradually increases. Type II samples have a relatively large percentage of reticulated residual oil in the near-miscible stage.

Background: The coexistence of HIV infection and latent tuberculosis infection (LTBI) presents a significant public health concern due to the increased risk of tuberculosis (TB) reactivation and progression to active disease. The multicenter observational cohort study, TUBHIVIT, conducted in Italy from 2017 to 2023, aimed to assess the prevalence of LTBI among people living with HIV (PLHIV) and their outcomes following LTBI screening and therapy initiation. Methods: We performed a prospective study in 5 referral centers for HIV care in Italy. PLHIV who consented to participate underwent QuantiFERON-TB Gold Plus and clinical, microbiological, and radiological assessments to exclude subclinical tuberculosis, as opportune. PLHIV diagnosed with LTBI that started chemoprophylaxis were followed until the ending of therapy. Results: A total of 1105 PLHIV were screened for LTBI using the QuantiFERON-TB Gold Plus test, revealing a prevalence of 3.4% of positive results (38/1105). Non-Italy-born individuals exhibited a significantly higher likelihood of testing positive. Thirty-one were diagnosed with LTBI, 1 showed active subclinical TB, 6 were lost to follow-up before discriminating between latent and active TB. Among PLHIV diagnosed with LTBI, 83.9% (26/31) started chemoprophylaxis. Most individuals received 6-9 months of isoniazid-based therapy. Of the 26 PLHIV commencing chemoprophylaxis, 18 (69.2%) completed the therapy, while 3 discontinued it and 5 were still on treatment at the time of the analysis. Adverse events were observed in two cases, while in one case the patient refused to continue the treatment.

Phase change materials (PCMs) have emerged as promising solutions for latent heat thermal energy storage (LHTES) systems, offering considerable potential for storing energy derived from renewable sources across various engineering applications. The present study focused on optimization of solar cooling system by integrating LHTES with different PCM tank configuration. TRNSYS simulation software was selected for the study and collected experimental data from laboratory system prototype was used for system validation. The results indicate that the use of PCM led to a noteworthy decrease of 6.2% in auxiliary energy consumption. Furthermore, the duration during which the heat carrier temperature flow exceeded 90°C from the storage tank to the auxiliary heater was extended by 27.8% when PCM was utilized, compared to its absence. The use of PCM in LHTES is more effective under variable weather conditions. On the day when changes in weather conditions were observed, around 98% of the cooling load was provided by produced sun energy. The results of the research can be used to optimize the solar cooling system, which will help reduce the environmental impact of cooling systems running on non-renewable fuels.

Microemulsions with excellent properties have shown significant potential for enhancing oil recovery from tight formations through spontaneous imbibition. This work present a high-temperature-tolerant lower-phase microemulsion (HTLP-ME) using a microemulsion dilution method. The properties and morphological characteristics of HTLP-ME were evaluated and proposed a enhanced spontaneous imbibition oil recovery mechanism using imbibition tests and CT scanning technology. The results show that the optimum concentration of HTLP-ME is 0.2wt% has a superior thermal stability, small particle size, lower IFT, good wettability alteration ability, and minimum adsorption loss. Imbibition and CT experiments showed that the longer the imbibition distance, the better is the effect on spontaneous imbibition oil recovery. Furthermore, the solubilization coefficient and self-driving force were defined and calculated to quantitatively analyze the imbibition mechanisms. The imbibition mechanisms demonstrate that the reduction of oil/solid adhesion is due to the synergistic effect of IFT reduction and wettability alteration, and the ability to increase the imbibition distance through a larger self-driving force.

Well placement optimization in a given geological setting for a fractured geothermal reservoir is a prerequisite for enhanced geothermal operations. High computational cost associated in the framework of fully coupled thermo-hydraulic-mechanical (THM) processes in a fractured reservoir simulation, makes the well positioning as a missing point in developing a field scale investigation. Here, in this study, we shed light on this topic through examining different injection-production well (doublet) position in a given real fracture network. Water and CO2 are used as working fluids for geothermal operations and importance of well positions are examined using coupled THM numerical simulations for both the fluids. Results of this study are examined through the thermal breakthrough time, mass flux and the energy extraction potential to assess the impact of well position in a two-dimensional reservoir framework. Almost ten times of the difference between the final amount of heat extraction is observed for different well position but with the same well spacing and geological characteristics. Furthermore, stress field is be a strong function of well position that is important with respect to the possibility of unwanted stress development. As part of the MEET project, this study recommends to perform similar well placement optimization study for each fracture set in a fully coupled THM manner before a field well drilling.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

We aimed at analyzing Chlorophyll-a and CDOM dynamics from field measurements and at assessing the potential of multispectral satellite data for retrieving water-quality parameters in three small surface reservoirs in the Brazilian semiarid region. More specifically, this work comprises i) analysis of Chl-a and trophic dynamics; ii) characterization of CDOM; iii) estimation of Chl-a and CDOM from OLI/Landsat-8 and RapidEye imagery. The monitoring lasted 20 months within a multi-year drought, which contributed to water-quality deterioration. Chl-a and trophic state analysis showed a highly eutrophic status for the perennial reservoir during the entire study period, while the non-perennial reservoirs ranged from oligotrophic to eutrophic, with changes associated with the first events of the rainy season. CDOM characterization suggests that the perennial reservoir is mostly influenced by autochthonous sources, while allochthonous sources dominate the non-perennial ones. Spectral-group classification assigned the perennial as CDOM-moderate and highly eutrophic reservoir, whereas the non-perennial ones were assigned as CDOM-rich and oligotrophic-dystrophic reservoirs. The remote sensing initiative was partially successful: the Chl-a was best modelled using RapidEye for the perennial; whereas CDOM performed best with Landsat-8 for non-perennial reservoirs. This investigation showed high potential for retrieving water quality parameters in dry areas with small reservoirs.

With the development of artificial intelligence, the ability of capturing the background characteristics of hyperspectral imagery (HSI) is improved and promising performance in hyperspectral anomaly detection (HAD) tasks is yielded. However, existing methods proposed in recent years still suffer from certain limitations: 1) constraints are lacking in the deep feature learning process in terms of the issue for absence of prior background and anomaly information. 2) hyperspectral anomaly detectors with traditional self-supervised deep learning methods fail to ensure prioritized reconstruction of the background. 3) architectures of fully connected deep network in hyperspectral anomaly detectors lead to low utilization of spatial information and destruction for original spatial relationship of hyperspectral imagery, and disregard spectral correlation between adjacent pixels. 4) hypotheses or assumptions for background and anomaly distributions restrict the performance of many hyperspectral anomaly detectors because the distributions of background land covers are usually complex and not assumable in real-world hyperspectral imagery. With the consideration of above problems, in this paper, we propose a novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency (FCAE-DCAC) for HAD which is carried out in a self-supervised learning-based processing. Firstly, the density-based spatial clustering of applications with noise algorithm and connected component analysis are utilized for successive spectral and spatial clustering to obtain more precise prior background and anomaly information, which facilitates the separation between background and anomaly samples during the training of our method. Subsequently, a novel fully convolutional auto-encoder (FCAE) integrated with spatial-spectral joint attention (SSJA) is proposed to enhance the utilization of spatial information and augment feature expression. In addition, a latent feature adversarial consistency network is proposed to achieve pure background reconstruction with the ability of learning actual background distribution in hyperspectral imagery. Finally, a triplet loss is introduced to enhance the separability between background and anomaly, and the reconstruction residual serves as the anomaly detection result. We evaluate the proposed method on seven groups of real-world hyperspectral datasets, and the experimental results confirmed the effectiveness and superior performance of the proposed method versus nine state-of-the-art methods.

A single geological carbon dioxide (CO2) storage within salinity aquifer as a paramount stratagem in the context of forthcoming CO2 sequestration initiatives. Within the expansive tapestry of terrestrial salinity aquifers in China, replete with nuances in mineral composition and structural diversity, a paradigm distinct from the marine sedimentary basins of North America, a labyrinthine stratigraphic environment of elevated complexity unfolds. Consequently, conspicuous lacunae and insufficiencies manifest within the existing knowledge reservoir pertaining to CO2-water-rock (mineral) reaction mechanisms. Notably, a conspicuous dearth of insights prevails concerning the dissolution kinetics inherent to individual minerals embroiled in these reactions. The present investigation undertakes a scrupulous exploration into the dissolution and erosive processes manifest within four emblematic terrestrial minerals in conjunction with CO2. Furthermore, the study meticulously scrutinizes the evolution of ionic composition and pH within the formation water throughout the trajectory of the geochemical reactions. To accomplish this, a simulation apparatus is configured to emulate conditions germane to temperature, pressure, and mineralization characteristics characteristic of a prototypical salinity aquifer reminiscent of the Daqing oilfield in China. The findings that emerge from this scrutiny reveal that the erosive action of CO2 fluid begets varying degrees of dissolution within the four minerals under investigation. Moreover, our meticulous inquiry lays bare that, in the terminal phases of the reaction process, feldspar precipitates secondary minerals, characterized primarily by dawsonite, in response to the aquatic milieu typifying the profound salinity stratum of terrestrial sedimentation. This milieu is notably enriched with Na+ ions and NaHCO3. This phenomenon suggests that feldspar, under these specific conditions, assumes the mantle of a mineral amenable to carbon sequestration, thus enriching the reservoir for CO2 mineralization within the salinity stratum of terrestrial sedimentation.

Here are analysed data taken in two hydrocarbon fields ("A" and "B"), located in the western part of Sava Depression (North Croatia). They are in the secondary phase of production. The selected reservoirs "L" (in the “A” Field) and "K" (“B”) are of the Lower Pontian (Upper Miocene) age and belong to Kloštar-Ivanić Formation. Due to strong tectonics, there are numerous tectonic block, relatively rarely sampled with well and laboratory tests. Here are selected two variables for interpolation - reservoirs permeabilities and the injected volumes of field water. The following interpolation methods are described, compared and applied: Nearest Neighbourhood, Natural Neighbour (the first time in the Sava Depression) and Inverse Distance Weighting. The last one has been proven as the most appropriate for datasets with size lower than 20 points.

The gas-water relative permeability curve plays a crucial role in reservoir simulation and development for condensate gas reservoirs. In this study, we conducted a series of high temperature and high pressure analysis experiments on real gas cores from Wells A and B in Block L of the Yinggehai Basin to investigate the effects of temperature, pressure, and different types of gas media on gas-water seepage. The experimental results demonstrate that: Temperature has a significant impact on both gas and water relative permeability, particularly on the former. As temperature increases, gas relative permeability shows a substantial increase while water relative permeability remains relatively unchanged. Under the same effective stress, increasing pressure causes downward shifts in both the gas and water relative permeability curves; however, there is a more pronounced decrease in gas relative permeability. Gas type has minimal influence on phase permeability except at higher water saturation where differences become apparent. When water saturation ranges from 80% to 50%, there is no significant variation observed in the measured relative permeability of different displacement gases; however, as water saturation exceeds 80%, distinctions gradually emerge. At bound water saturation conditions, nitrogen exhibits lower relative permeability compared to simulated gases with approximately 92% similarity between them. This investigation into the characteristics of gas-water relative permeability in high temperature and high pressure condensate reservoirs within Yinggehai Basin provides valuable insights for efficient development strategies for similar reservoirs.

Coal permeability data are critical in the prevention and control of coal and gas outbursts in mines and are an important reservoir parameter for the development of coalbed methane. The mechanism by which permeability is affected by gas pressure is complex. We used a self-developed true triaxial seepage experimental device that collects lignite and anthracite coal samples, sets fixed axial pressure and confining pressure, and changes gas pressure by changing the orientation of the coal seam to study the influence of the gas pressure on the permeability of the coal seam under the conditions of different coal types and different bedding orientations. Coal permeability decreased rapidly and then decreased slowly and tended to be stable with the increase in gas pressure. This conforms to the power exponential fitting relationship, and the fitting degree reaches more than 99%. The permeabilities of lignite and anthracite were basically the same under various pressure conditions, indicating that the influence of coal type on coal permeability was not significant. The comparison of the two anthracite coal samples showed that the sample's permeability with a bedding plane vertical to the seepage direction was significantly lower than that of the bedding plane parallel to the seepage direction, indicating that gas seeped more easily along the bedding. The sensitivity coefficient of permeability with the change in gas pressure was calculated. The analysis showed that coal permeability was sensitive to changes in gas pressure during the low-pressure stage. When the gas pressure was greater than 0.8 MPa, the sensitivity coefficient was significantly reduced, which may be related to the slow increase in the amount of gas absorbed by the coal seam in the high-pressure stage. A theoretical calculation model of coal seam permeability considering adsorption/desorption and seepage effects was proposed and then verified with experimental results showing that the theoretical model better reflected the permeability characteristics of coal and predicted its permeability. Using the finite element simulation software COMSOL, the extraction efficiency of the coal seam gas under different gas pressure conditions was simulated. The results showed that with an increase in gas pressure, coal permeability and extraction efficiency decreased. In the low-pressure stage, the reduction in the extraction efficiency was more obvious than that in the high-pressure stage.

Buruli ulcer (BU), caused by Mycobacterium ulcerans, is a neglected tropical disease associated with freshwater habitats. A variety of limnic organisms harbor this pathogen, including aquatic bugs (Hemiptera: Heteroptera), which have been hypothesized to be epidemiologically important reservoirs. Aquatic Hemiptera exhibit high levels of diversity in the tropics, but species identification remains challenging. In this study, we collected aquatic bugs from emerging foci of BU in the Southwest Region of Cameroon, which were identified using morphological and molecular methods. The bugs were screened for mycobacterial DNA and a selection of 20 mycobacteria-positive specimens from the families Gerridae and Veliidae were subjected to next-generation sequencing. Only one individual revealed putative M. ulcerans DNA, but all specimens contained sequences from the widespread alpha-proteobacterial symbiont, Wolbachia. Phylogenetic analysis placed the Wolbachia sequences into supergroups A, B and F. Circularized mitogenomes were obtained for seven gerrids and two veliids, the first from these families for the African continent. This study suggests that aquatic Hemiptera may have a minor role (if any) in the spread of BU in Southwest Cameroon. Our metagenomic analysis provides new insights into the incursion of Wolbachia into aquatic environments and generates valuable resources to aid molecular taxonomic studies of aquatic Hemiptera.

Apple latent spherical virus (ALSV) is widely used as a virus-induced gene silencing (VIGS) vector for function genome study. However, the application of ALSV in soybean is limited by the resistance of many varieties. In this study, the genetic loci linked to the resistance of a resistant soybean variety Heinong 84 was mapped by high-throughput sequencing‒Bulk Segregation Analysis (HTS‒BSA) using a hybrid population crossed from Heinong 84 and a susceptible variety Zhonghuang 13. Results showed that the resistance of Heinong 84 to ALSV is controlled by two genetic loci located on chromosome 2 and 11, respectively. Cleaved amplified polymorphic sequences (CAPS) markers were developed for identification and genotyping. Inheritance and biochemical analyses suggest that the resistance locus on chromosome 2 plays a dominant dose-dependent role, while the other locus contributes a secondary role in resisting ALSV. The resistance locus on chromosome 2 might encode a protein that can directly inhibit viral proliferation, while the secondary resistance locus on chromosome 11 may encode a host factor required for viral proliferation. Together, these data reveal novel insights on the resistance mechanism of Heinong 84 to ALSV, which will benefit for the application of ALSV as a VIGS vector.

Smear-ripened cheeses host complex microbial communities that play a crucial role in the ripening process. Although bacteriophages have been frequently isolated from dairy products, their diversity and ecological role in such type of cheese remain underexplored. In order to fill this gap, the main objective of this study was to isolate and characterize bacteriophages from the rind of a smear-ripened cheese. Thus, viral particles extracted from cheese rind were tested against a collection of bacterial isolates through a spot assay. In total, five virulent bacteriophages infecting Brevibacterium aurantiacum, Glutamicibacter arilaitensis, Leuconostoc falkenbergense and Psychrobacter aquimaris species were obtained. All exhibit a narrow host range, being only able to infect a few cheese-rind isolates within the same species. The complete genome of each phage was sequenced using both Nanopore and Illumina technologies, assembled and annotated. Sequence comparison with known phages revealed that four of them may represent at least new genera. The distribution of the five virulent phages into the dairy-plant environment was also investigated by PCR and three potential reservoirs were identified. This work provides new knowledge on the cheese rind viral community and an overview of the distribution of phages within a cheese factory.

The paper investigates the possible use of a low strength domestic sand (D) (up to today useless – not considered as proppant source) of small particle sizes, instead to that of high strength imported commercial sand (C), as a prospective micro-proppant for low permeability reservoirs in Poland. There is need to develop national unconventional gas resources like tight gas, shale gas and coalbed methane. An important energy source of value and readily available in Poland is coal. The basins of this resource are large and bears low permeability coalbed methane reservoirs which needs to be developed to contribute to the energy security, economy and environmental needs of the country. These reservoirs need technological assistance such as hydraulic fracturing which makes use of proppants for development. Most of the commonly used proppants over the years for fracturing have been large grain size commercial proppants of high strength material content bought abroad. Investigated finer proppants are known to have the ability to penetrate narrow fracture networks to ensure effective high reservoir volume and conductivity for production. Results from presented laboratory research shows the D - proppant, which is cheaper and readily available, has the 3K class with low settling rates as a potential micro-proppant for effective transportation, enhancement of conductivity and production rate in the narrow fractures of low permeability reservoirs. Future using of domestic proppant will decrease stimulation cost and will have positive impact on the environment due to omitting long distance transportation from abroad.

The Oil reservoirs with low permeability account for a large proportion in the world, they surpass half of the total number of the oil reservoirs in China, it is important to exploit this kind of reservoir effectively. The exploitive results of these reservoir using normal water flooding methods are very poor because of the thine pores, bad connections and so on. However, these problems can be well solved by applying gas injection techniques. In this paper, the effects on the recovery effects exerted by the injection parameters such as the oxygen content in the injected air, the injection speed etc. were studied by several experiments using independently designed equipments aiming at one low permeable sandstone reservoir in China. Several conclusions were made from the experiment results: the best recovery effects can be achieved by injecting the oxygen reduced air with 8% of oxygen at the speed of 0.3ml/min (7.41×10-4PV/min) using the methods of injecting the air slugs and the foaming agent slugs alternately; the best oxidation time of the oil was 168 hours and the final oil recovery could be enhanced by 26.5% in this method. It was also showed by the experiments that the larger the permeability ratio is, the larger the recovery factor will be increased. At last, several equations about relationships between the EOR and the air injection parameters were revealed according to the results of the experiments which may offer some references to the LTO process mechanisms study in the similar oil reservoir.

Mesozoic-Palaeozoic marine carbonate rocks are important hydrocarbon reservoirs in the Central Uplift area of the South Yellow Sea Basin (SYSB). Due to the lack of boreholes and the great heterogeneity of carbonate reservoirs, the distribution of porous carbonate reservoirs and their related key controlling factors remain unclear. Based on seismic inversion and isotope analysis, this study explores the factors affecting the distribution of porous Carboniferous-Early Permian carbonate reservoirs in the SYSB. In this study, the log-seismic characteristics of porous carbonate reservoirs, sensitive lithology parameters, and physical property parameters are extracted and analyzed. The pre-stack simultaneous inversion technique is applied to predict the lithology properties and physical properties of the porous carbonate reservoirs. Moreover, the sedimentary of carbonate is analyzed using isotopes of carbon, oxygen, and strontium. The results indicate that porous carbonate reservoirs with porosities of 3%~5% mainly occur at the paleo-highland (Huanglong Formation and Chuanshan Formation) and the slope of paleo-highland (Hezhou Formation). The porous carbonate reservoirs of the Qixia Formation are only locally developed. In addition, the study area was dominated by a warm and humid tropical climate from the Carboniferous to Early Permian, with four sea-level eustatic fluctuation indicated by the negative and positive δ13C excursions. When the sea level fell, the study area was exposed and denuded, and the supply of terrigenous detrital was dominated, which significantly influenced the carbonate deposit and diagenesis. This study highlights that sedimentation was a key factor in controlling the quality of Carboniferous-Early Permian carbonate reservoirs. The methods proposed in this study can be used in other carbonate-dominated strata worldwide.

In order to understand the impact of lithologic heterogeneity of continental mixed fine-grained sedimentary rocks on reservoir brittleness in western Qaidam basin, the mechanical properties of the rocks and their correlation with mineral composition and petrographic characteristics were studied by measns of mineralogy, petrography and triaxial stress test. The results show that the reservoir rocks can be divided into 5 different types according to the mechanical properties of the reservoir (characteristics of stress-strain curves), among them Type I and III belong to similar elastoplastic failure model, type II shows a special pulse failure mode for plastic material, type IV shows a failure mode of mixed characteristics, and type V exhibits a typical plastic failure model. The correlation between minerals and mechanical properties indicates that quartz and feldspar, which are often considered brittle minerals, do not contribute much to the brittleness of continental fine-grained sedimentary rocks. The main minerals affecting reservoir brittleness are dolomite and clay minerals, and their contributions to reservoir brittleness are positive and negative, respectively. The petrographic analysis results prove that the abnormal correlation between rock mechanical properties and quartz and feldspar is caused by the different rock fabrics. When dolomite forms a rock skeleton, it typically exhibits greater strength, brittleness and physical properties than other minerals. Based on the results, a brittleness evaluation standard for continental fine-grained sedimentary rock reservoir is proposed, and the validity of the standard is verified by the spatial correlation between the lithology probability model and the micro-seismic monitoring data, indicating that the spatial heterogeneity of dolomite-rich rock is the main controlling factor for the development of ‘sweet spot’ in the Cenozoic continental fine-grained sedimentary rock reservoir in the Western Qaidam Basin.

Interpolation is procedure that depends on spatial and/or statistical properties of analysed variable(s). It is special challenging task for data that included low number of samples, like dataset with less than 20 data. This problem is especially emphasized in the subsurface geological mapping, i.e. in the cases where data are taken solely from wells. Successful solutions of such mapping problems ask for knowledge about interpolation methods designed primarily for small datasets and dataset itself. Here are compared two methods, namely Inverse Distance Weighting and Modified Shepard’s Method, applied for three variables (porosity, permeability, thickness) measured in the Neogene sandstone hydrocarbon reservoirs (Northern Croatia). The results showed that pure cross-validation is not enough condition for appropriate map selection, but also geometrical features need to be considered, for datasets with less than 20 points.

Pollution of sub-surface water reservoirs mainly rivers and streams through contaminated water point sources (CWPS) was studied. The objective was to formulate a discrete time delay mathematical model which describes the dynamics of reservoir pollution using mixing-problem processes that involve single species contaminants such as nitrates, phosphorous and detergents. The concentration of pollutants was expressed as a function of the inflow and outflow rates using the principle for the conservation of mass. Systems of ODEs generated from principles of mixing problems were refined into a system of DDEs so that the concentration of pollutant leaving the reservoir at time would be determined at some earlier instant, for the delay. The formulated model is a mathematical discrete time delay model which would be used to describe the dynamics of sub-surface water reservoir pollution. The results from the validation of the model were analyzed to determine how time delays in the mixing processes affect the rate of particle movement in water reservoirs.

Geothermal energy aims at harnessing the heat of the Earth to produce energy, from the near-surface to great depths. Emphasis is put on geothermal reservoirs in crystalline rocks, hence vol-canic islands and crystalline basements of sedimentary basins based on three examples world-wide. Hot brines circulate in those rocks and are responsible for their hydrothermal alteration because of fluid-rock interactions. This includes dissolution of preexisting minerals and crystal-lization of newly formed ones which provide many information of crucial importance for a better exploration of those reservoirs. For example, the crystallization of clay minerals results from the dissolution of preexisting minerals (feldspar and ferro-magnesian minerals in plutonic, volcanic or metamorphic rocks) or from the direct precipitation from geothermal brines, in specific condi-tions. Clay minerals are found in both the geothermal reservoirs and in the clay-cap found above them. Other newly formed minerals such as quartz, carbonates or sulfates have also recorded the conditions of temperature and salinity encountered by fossil reservoirs which can be evaluated thanks to the study of fluid inclusions trapped during their crystallization. This paper presents results from several geothermal deep sites and surface analogues to pinpoint the role played by newly-formed minerals in the characterization of geothermal reservoirs and their cap-rock.

Brine-dependent recovery process has seen much global research efforts in the past two decades because of their benefits over other oil recovery methods. The process involves the tweaking of the ionic composition and strength of the injected water to improve oil production. In recent years, several studies ranging from laboratory coreflood experiments by many researchers to field trials by several companies admit to the potential of recovering additional oil in sandstone and carbonate reservoirs. Sandstone and carbonate rocks are composed of completely different minerals, with varying degree of complexity and heterogeneity, but wettability alteration has been widely considered as the consequence rather than the cause of brine-dependent recovery. However, there is no consensus on the cause as several mechanisms have been proposed to relate the wettability changes to the improved recovery. This review paper aims to provide a state-of-the-art development in published research and various efforts of the industry. This review outlines an overview of laboratory and field observations, descriptions of underlying mechanisms and their validity, the complexity of the oil-brine-rock interactions, modelling works, and comparison between sandstone and carbonate rocks. The provided information is intended to provide the reader with up-to-date information, point to relevant studies for those who are new and those implementing either laboratory- or field-scale projects to speed up the process of further investigations in this research area. Overall, the outcome of this review would potentially be of immense benefit to the oil industry.

The power generation from hydroelectric plants has increased worldwide, contributing to the participation of the renewable sources to the energy matrix. In the semiarid Brazilian Northeast (NEB), thousands of small dams have been built over time as a solution for water supply. Although incompatible with hydropower generation due to the conflict with human water supply in the region, small reservoirs accumulate water and hydraulic energy at high altitudes. In this work, simulations were performed to assess how the arrangement of various sized reservoirs impact the power demand for water distribution in the Banabuiú River Basin – BRB (19,800 km²), Brazil. The power required to pump water from all 1,405 reservoirs to the districts is 6.5 GWh/year, whereas in the scenario with the 12 larger strategic reservoirs only, the power demand reaches 45.3 GWh/year. Although representing roughly 60% of the water availability of the BRB and being able to supply all the districts, the Arrojado Lisboa reservoir alone would demand 195 GWh/year to supply water to the entire basin, i.e. 30 times the power required in the real reservoir arrangement. By storing water at high altitudes and distributing it spatially, the small reservoirs increase the energy efficiency on the water distribution system.

Antimicrobial resistance is a major public health concern. Rodents and shrews live in closer proximity to humans and animals and serve as reservoirs for the transmission of several diseases, including AMR pathogens. There is no data available from India on surveillance of AMR bacteria in rodents and shrews. In this study, bacterial pathogens viz, Staphylococcus sp, Escherichia coli and Salmonella sp were isolated from rodents and shrews and genetic elements conferring antimicrobial resistance in the pathogens were screened by PCR. Bacterial pathogens in the oropharyngeal and anal swabs collected from the rodents and shrews trapped (n=100) were cultured on selective media such as Mannitol salt, Mac Conkey and Xylose lysine deoxycholate media to isolate Staphylococcus sp., E. coli and Salmonella sp. respectively. A total of 76 (80%) S. aureus and 19 (20%) Staphylococcus non aureus were isolated. E. coli was isolated in 89 samples and among the Salmonella sp (n=59), 16 (27%) were S. enteritidis and 29 (49.1%) were S. typhimurium. In S. aureus isolates, mec A and mec C (MRSA) were detected in 40 (52.6%) and 6 (7.9%) isolates respectively. Also, 7 (36.84%) and 1 (5.3%) Staphylococcus non aureus isolates were tested to harbour mec A and mec C genes. A total of 77 (86.5%) E. coli isolates had genes encoding ESBL [TEM in 21 (23.59%), SHV in 45 (50.6%) and CTXM in 11 (12.4%)]. Among the 45 pathogenic Salmonella sp, 44 (97.78%) harboured AMR genes [tet in 13 (28.9%), sul3 & sul4 in 20 (44.4%) and qnrA in 11 (24.4%)]. Thirty-eight animals harboured more than one zoonotic pathogen and 21 with multi-drug resistant genes. Our findings signify that these rodents and shrews may serve as sentinels to screen environment spillover of AMR pathogens and also act as reservoir to transmit MRSA, ESBL, Salmonella sp. human/animals. Also these animals aid in the transfer of antimicrobial resistance genetic elements to non-pathogenic organisms.

During the development of horizontal wells in bottom water reservoirs, the strong heterogeneity of reservoir permeability leads to premature bottom water breakthrough at locations with high permeability in the horizontal wellbore, and the water content rises rapidly, which seriously affects production. In order to cope with this problem, a new technology has emerged in recent years that utilizes gravel filling to block the flow in the annulus between the horizontal well and the borehole, and utilizes the Inflow Control Device (ICD) completion tool to carry out segmental water control in horizontal wells. Unlike conventional horizontal well ICD completions that use packers for segmentation, gravel pack combined with ICD completions breaks the original seg-mentation routine and increases the complexity of production dynamic simulation. In this paper, the flow in different spatial dimensions such as reservoir, gravel packed layer, ICD completion section and horizontal wellbore is modeled separately, and the annular pressure at different locations is used as the solution variable for the coupled solution, which realizes the prediction of oil production, water production and water content of gravel pack combined with ICD completions of horizontal wells. The model was used to calculate the effects of different crude oil viscosities, different reservoir permeabilities, different permeabilities of gravel packed layers, and different development stages on the water control effects of gravel pack combined ICD completions and conventional ICD completions at field conditions. This study provides a basis for using gravel pack combined ICD completions in horizontal wells in bottom water reservoirs.

In deep geological analysis of data, these are input data that are few and include a small set of data. In a small set of case data, it is necessary to obtain reliable data of individual geological variables from this type of data. The paper analyzes the possibility of applying the bootstrap method on variables that are important in the exploration and production of hydrocarbons. The variables analyzed were the following: porosity and total costs of disposal formation water. The case study was made on the data of reservoir "K", field "B" located in the western part of the Sava Depression. The analysis of the results showed the possibility of applying the bootstrap method in the analysis of deep geological data with the application of three different sizes of resampling dataset.

In order to solve the problem of the poor oil displacement effect of high molecular weight alkali/surfactant/polymer (ASP) solution in low permeability reservoirs, Daqing Oilfield uses a partial quality tool to improve the oil displacement effect in low permeability reservoirs. Without changing the oil displacement capability of high molecular weight ASP solution in high permeability oil layers, the ASP solution is actively sheared in low permeability oil layers by using a partial quality tool to increase the injection capability of the solution and improve the overall oil recovery. In order to study the ability of the partial quality tool to improve the oil displacement effect, firstly, the matching degree of high molecular weight ASP solution to low permeability cores is studied, and the ability of quality control tools to change the molecular weight is studied. Then, experimental research on the pressure and oil displacement effect of high molecular weight ASP solution before and after the actions of the partial quality tool is carried out. The results show that ASP solutions with molecular weights of 1900 × 104 and 2500 × 104 have a poor oil displacement effect in low permeability reservoirs. After the action of the partial quality tool, the injection pressure is reduced by 5.22 MPa, and the oil recovery is increased by 7.79%. The injection pressure of the ASP solution after shearing by the partial quality tool is lower than that of the ASP solution with the same molecular weight and concentration without shearing, but the oil recovery is lower. On the whole, the use of the partial quality tool can obviously improve the oil displacement effect in low permeability reservoirs.

Abstract: Radiation-induced skin injury can be a serious cutaneous damage and have specific characteristics. Asymptomatic periods are classified as the latent stage. The skin barrier plays a critical role in the modulation of skin permeability and hydration and protects the body against a harsh external environment. However, an analysis on the skin barrier dysfunction against radiation exposure in the latent stage has not been conducted. Thus, we investigated whether skin barrier is impaired by irradiation in the latent stage and aimed to identify the molecules involved in skin barrier dysfunction. We analyzed skin barrier function and its components in SKH-1 mice that received 20 and 40 Gy local irradiation. Increased transepidermal water loss and skin pH were observed in the latent stage of the irradiated skin. Skin barrier components, such as structural proteins and lipid synthesis enzymes in keratinocyte, increased in the irradiated group. Interestingly, we noted sebaceous gland atrophy and increased serine protease and inflammatory cytokines in the irradiated skin during the latent period. This finding indicates that the main factor of skin barrier dysfunction in the latent stage of radiation-induced skin injury is sebaceous gland deficiency, which could be an intervention target for skin barrier impairment.

Here is analysed the process of water re-injection in the two hydrocarbon reservoirs/fields in the Upper Miocene sandstone reservoirs, located in the western part of the Sava Depression (Croatia). Namely, those are the "A" field with "L" reservoir and the "B" field with "K" reservoir. Both currently produce hydrocarbons using a secondary recovery method, i.e. water injection (in fact re-injection of the field waters). Three regional reservoir variables had been analysed, namely porosity, permeability and injected water volumes. The number of data was small in all three cases. For porosity: reservoir “L” included 25 data, reservoir “K” 19 data; for permeability: reservoir “L” 10 data, reservoir “K” 18 data; for injected volumes of water: reservoir “L” 10 data; reservoir “K” 3 data. It defined selection of mapping algorithms mostly designed for small datasets (less than 20 points), i.e. Inverse Distance Weighting, Nearest and Natural Neighbourhood. Additionally, the Ordinary Kriging was used, but only with jack-knifed variograms, producing many “artificial points”. Results are extensively tested, using cross-validation and shape recognitions, and the Inverse Distance Weighting method is described as the most appropriate approach for mapping permeability and injected volumes in both reservoirs (“K” and “L”). The Kriging could be slightly outlined as the best approach for porosity. Obtained maps made possible application of the modified geological probability calculation as tools for prediction of successfulness of future injection (probability of 0.56). Consequently, results made possible to plan future injection more efficiently, with smaller injected volumes and same of higher hydrocarbon recovery. That could prevent useless injection, decrease number of injection wells, and save energy and funds invested in such processes.

There is a significant overlap between HIV infection and substance use disorders. Dopamine (DA) is the most abundantly upregulated neurotransmitter in Methamphetamine abuse, with receptors (DRD1-5) that are expressed by neurons as well as by a large diversity of cell types, including innate immune cells that are targets of HIV infection, making them responsive to the hyperdopaminergic environment that is characteristic of stimulant drugs. Therefore, the presence of high levels of dopamine may affect the pathogenesis of HIV, particularly in the brain. The stimulation of HIV-latently infected U1 promonocytes with DA significantly increased viral p24 levels in the supernatant at 24 hrs, suggesting effects on activation and replication. Using selective agonists to different DRDs, we found that DRD1 played a major role in activating viral transcription, followed by DRD4, which increased p24 with a slower kinetic. Transcriptome and systems biology analyses led to the identification of a cluster of genes responsive to DA, where S100A8 and S100A9 were most significantly correlated with the early increase of p24 levels following DA stimulation. Conversely, DA increased the expression of these genes’ transcripts at the protein level, respectively MRP8 and MRP14, which form a complex also known as Calprotectin. Interestingly, MRP8/14 was able to stimulate HIV transcription in latent U1 cells, and this occurred via binding to the receptor for advanced glycosylation end-product (RAGE). Using selective agonists, both DRD1 and DRD4 increased MRP8/14 on the surface and in the cytoplasm, as well as secreted in the supernatants. On the other hand, while DRD1/5 did not affect the expression of RAGE, DRD4 stimulation caused its downregulation, offering a mechanistic for the delayed effect via DRD4 on p24 increase. To cross-validate MRP8/14 as a DA signature with biomarker value, we tested its expression in HIV+ Meth users’ brains and peripheral cells. MRP8/14+ cells were more frequently identified in mesolimbic areas such as basal ganglia of HIV+ Meth+ cases compared to HIV+ non-Meth users or to controls. Likewise, MRP8/14+ CD11b+ monocytes were more frequent in HIV+ Meth users, particularly in participants with detectable viral load in the CSF. Overall, our results suggest that the MRP8 and MRP14 complex may serve as a signature to distinguish subjects using addictive substances in the context of HIV, and that this may play a role in aggravating HIV pathology by promoting viral replication in people with HIV who use Meth.

The aim of the study was to identify factors associated with non-adherence to tuberculosis (TB) preventive treatment among contacts with latent TB infection of new cases of pulmonary TB cases reported in Catalonia in 2019-2021. All contacts aged 18 years or older with a latent TB infection who received a TB preventive treatment were included in the study. The Chi square test and the odds ratios (OR) were used to assess the association between non-adherence to TB preventive treatment and the study variables, considering a p < 0.05 as statistically significant. Multiple logistic regression analysis was used to detect the in-dependent factors associated with TB preventive treatment non-adherence, considering a p < 0.05 as statistically significant. The percentage of non-adherence to TB preventive treatment found in this study was 23.7%. A multivariable logistic regression analysis determined that the following factors were significantly associated with TB preventive treatment non-adherence among adult contacts: “exposure at school or workplace” (aOR = 3.34), “exposure to an index case without laboratory confirmation of TB” (aOR = 2.07), “immigrant contact” (aOR = 1.81), “male gender” (aOR = 1.75) and “exposure duration <6 hours per week or sporadic exposure” (aOR = 1.60). By contrast, the factor “short-term TB preventive treatment regimen” (aOR = 0.38) was significantly associated with a lower treatment non-adherence. Adherence to TB preventive treatment should be improved among adult contacts of TB pulmonary cases with latent TB infection by recommending short-term treatment regimens and by developing health education activities, with a greater focus on contacts with factors associated with treatment non-adherence.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The western Sulige gas field is a new and key reserve area for the rolling development of the Sulige gas field in China. However, due to the complex gas–water relationship and the difficulty in identifying gas and water formation, the scale and benefit deployment of the gas field are seriously restricted. In particular, almost all of the wells in the area produce water and no water measurement has been carried out for any single well, which leads to an unclear understanding of the dynamic characteristics of the production wells, thus affecting the productivity calculations of the gas wells and the overall regional productivity evaluation. Based on the testing data for a gas well, the impacts of the reservoir property parameters on the gas and water production were analyzed by combining the production performance and static geological characteristics. It was determined that the physical parameters K, Kh, and φSg had good positive correlations with gas production but not with water production; thus, effective prediction cannot be obtained for water production in gas well testing. After the analysis of the liquid loading law, the gas wells were classified into three types: continuous liquid carrying production, slight liquid loading, and liquid loading wells. In general, up to 96% of the gas wells were liquid loaded. According to the different production performances exhibited in the different stages of the gas wells, five types of methods for diagnosing water production wells were proposed (gas testing, pilot production, gas–liquid two-phase measurement testing, liquid level detection, and production performance analysis), as well as the diagnostic criteria and corresponding solutions. To obtain real-time water production data for each well and investigate the change of water-gas ratio (WGR) during the whole production process, a water production splitting method for gas wells based on three-dimensional geological modeling and numerical simulation combined with the constraints of the total water production of gas gathering stations was explored and established. The splitting results can be used to evaluate the water and gas productivity of gas wells and determine the best deliquification period. The gas well productivity when water production was considered was about 10% lower than that when water production was not considered. The best deliquification period was determined to be 125 days for wells with small water production, 20 days for wells with moderate water production, and 3 days for wells with serious water production. The results of this study could provide technical support for the scientific evaluation of gas well production indicators, reduction of development costs, and improvement of oil recovery.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.