An extensive thermodynamic study of N-methylformamide (CAS RN: 123-39-7) and N,N-dimethylformamide (CAS RN: 68-12-2), is presented in this work. The liquid heat capacities of N-methylformamide were measured by Tian–Calvet calorimetry in the temperature interval (250 – 300) K. The vapor pressures for N-methylformamide and N,N-dimethylformamide were measured using static method in the temperature range 238 K to 308 K. The ideal-gas thermo-dynamic properties were calculated using a combination of the density functional theory (DFT) and statistical thermodynamics. A consistent thermodynamic description was developed using the method of simultaneous correlation, where the experimental and selected titerature data for vapor pressures, vaporization enthalpies, and liquid phase heat capacities and calculated ide-al-gas heat capacities are treated together to ensure overall thermodynamic consistency of the results. Resulting vapor pressure equation is valid from the triple point to the normal boiling point temperature.

Although there are extensive literature reports on the use of gold nanoparticle (AuNP) based homogeneous assays for detection of biomolecules, very few experimental description and procedures involving their preparation are described. In this study, AuNPs conjugated to Bovine Serum Albumin or Envelope protein from Dengue II were developed as a homogeneous immunoassay for antibody detection. We report here optimization of key parameters to prepare an immunoassay like conjugation protein concentration, centrifugation time, electrolyte addition and assay temperature. We determined that saturating protein concentrations improved AuNPs surface coverage and uniformity of the assay and addition of sodium chloride improved sensitivity of the antibody detection method and assay stability. Furthermore, we showed that dynamic light scattering can be used to monitor changes in gold nanoparticles in the preparation and detection steps. Additionally, numerical simulations of the plasmonic optical response of AuNPs were carried out to scan for size-dependent response of the AuNPs. The AuNPs homogeneous immunoassay developed was further used in the detection of antibodies in vitro to detect Dengue virus infection.

Background: The transversus abdominis plane (TAP) block has gained increasing importance as a very effective pain relief in for caesarean section. This study aimed to compare bupivacaine (Group B), bupivacaine with dexmedetomidine (Group BD) and bupivacaine with dexamethasone (Group BDx) applied in ultrasound-guided TAP block in the treatment of CS postoperative pain. Material and Method: American Society of Anesthesiologists I and II pregnant women who underwent cesarean section were included in the study. Forty patients were admitted in each group. All patients were applied TAP block with ultrasound guidance by administering the medications of the group in which they were included. Results: Body mass index (BMI) and operation duration were higher in Group B (p*=0.01 and 0.004, respectively). Instant tramadol requirement and amount were higher in Group B at some of follow up times. Patient satisfaction scale were better in Group BD and Group BDx. Conclusion: TAP block significantly reduces pain after cesarean section, prolongs the time to first analgesic request, and reduces the need for additional opioid analgesics. The addition of adjuvant to the TAP block usually improves the postoperative clinical condition. However, some special conditions such as body mass index (BMI) may negatively affect the clinical situation. Comprehensive, standardized, randomized controlled studies are needed to compare results under different conditions.

Our study examines the association of the presence of mildew, cockroaches, and pets in homes as well as household dust allergens with the prevalence and/or severity of allergic diseases. No study has concurrently assessed home environment exposures in relation to allergic conditions in the general US population. Data from 5,409 participants from the 2005-2006 National Health and Nutrition Examination Survey living in their current homes for ≥1 year were analyzed. Multivariate logistic regression analyses between home exposures and allergic diseases prevalence and severity were performed. In adjusted analyses, mildew was associated with higher current asthma, allergies, and allergic rhinitis prevalence; endotoxin, with higher current asthma prevalence), and dust Canis familiaris (Can f) 1, with higher allergic rhinitis prevalence. However, presence of cockroaches and dust Dermatogoides farinae (Der f) 1 were associated respectively with lower current asthma and allergies prevalence. Presence of mildew, dust Der f1, Dermatogoides pteronyssinus (Der p) 1, Feline domesticus (Fel d) 1, and endotoxin were all associated with asthma and/or wheeze severity. Non-atopic asthma was more frequent with mildew and/or musty smell dust and higher dust Fel d1 concentration, while atopic asthma was more prevalent with higher Can f1and endotoxin concentrations in dust. This study confirms previous relationships and reports novel associations, generating hypotheses for future research.

Pyrochlore oxides (A2B2O7) are potential nuclear waste substrate material due to their superior radiation resistance properties. We performed molecular dynamics simulations to study the structural properties and displacement cascades in ytterbium titanate pyrochlore (Yb2Ti2O7). We computed threshold displacement energy ( Ed ) and lattice constant ( ao) of Yb2Ti2O7. The effect of displacement cascades in Yb2Ti2O7 of recoils of energies 1 keV, 2 keV, 5 keV, 10 keV in different crystallographic directions ([100], [110], [111]) were studied. The number of defects is found to be proportional to the energy of incident PKA. Additionally, the Ed of pyrochlore is computed and it exhibits anisotropy. Furthermore, radiation damage in high-entropy pyrochlore (HEPy) i.e., YbYTiZrO7, YbGdTiZrO7 , Yb0.5Y0.5Eu0.5Gd0.5TiZrO7 were investigated and compared with Yb2Ti2O7. It was found that HEPy have a larger Ed as compared with Yb2Ti2O7 which exhibits characteristic of lower radiation damage resistance than HEPy. Our simulation proposed that HEPy alloys are more radiation resistant than individual pyrochlore constituents . This work will provide atomic insights in developing substrate materials for nuclear waste applications.

Dietary factors are one of the risk factors that can impact the brain chemistry, which leads to mental distress. Based on our data mining approach, we found that mental distress in men is associated with eating unhealthy food. Our aim in this paper is to apply results from our big data analytics approach to inform system dynamics (SD) modeling to investigate the causal relationships between brain structures, nutrients from food and dietary supplements, and mental health. We perform descriptive analysis based on a large data set to estimate the SD modeling parameters. Finally, we calibrate the model towards a time series data collected for individuals on their dietary and distress patterns. The results reveal that bridging these different methodologies leads to further insights from the SD model and decreases the error of calibrated parameter values. Future research is needed to validate our initial results for investigating the relationship between mental distress and dietary intake.

Materials based on platinum metals with very good catalytic activity were tested in the reduction of p–nitrophenol (pNP) to p–aminophenol (pAP). The majority of presented catalytic materials are based on the adsorption of p–nitrophenol on the surface of the catalyst simultaneously with molecular hydrogen, coming from sodium borohydride in an aqueous medium, which reduces it. In the present paper, a catalytic material based on osmium dispersed in n–decanol or n–dodecanol is presented, which also works as an emulsion membrane, for the absorption of p–nitrophenol and molecular hydrogen at the n–alcohol aqueous solution interface. The hydrogenation of p–nitrophenol is carried out in a reaction and separation column in which the acid receiving phase emulsion is dispersed in the osmium nanodispersion, in n–alcohols. This emulsion circulates from the base of the column to its upper part in co-current or counter-current with the source phase consisting of p–nitrophenol and sodium borohydride. Experiments show that the circulation of counter-current phases is superior to that in co-current, and the emulsion based on n–decanol is more efficient than the one based on n–dodecanol. The increase in the pH difference between the source and receiving phases leads to the increase in the conversion of p–nitrophenol to p–aminophenol. The efficiency of separation of the reaction product in the receiving phase is lower than the conversion at the same operating time. The apparent catalytic rate constant (kapp) of the new catalytic material based on the emulsion membrane with nanodispersion of osmium nanoparticles (0.1×10−3 for n–dodecanol and 0.9×10−3 for n-decanol) is lower by an order of magnitude compared to those based on adsorption on catalysts from platinum metal group. The advantage of the tested membrane catalytic material is that it extracts p–aminophenol in the acid receiving phase. The paper proposes a mechanism of the studied reduction system.

This study presents an analysis of the spatial and temporal distribution of the two large destructive earthquakes that occurred in Lake Van area on October 23, and November 9, 2011, together with the azimuth-dependent distribution of the seismic activity and microseismicity clusters after the mainshocks, associated with the complex rupture processes of their aftershock sequence. The sequence began with the magnitude Mw 7.1 earthquake of 23 October and a second destructive earthquake of Mw 5.6. The aftershock sequences of the two mainshocks were linked to the local crustal faults beneath Lake Van area, followed successively and produced unusually intense activity and significant damage in the area. The main purposes of this study are to document the spatial and temporal distribution and evolution of the October 23, 2011 aftershock hypocenters and the azimuth-dependent distribution of seismic activity, and to understand the spatial and temporal character of the aftershock sequence using the distributional and evolutional patterns of the aftershock hypocenters. A total of 10,000 aftershocks were obtained from seismic data with a high signal-to-noise ratio over collected over three years from October 23, 2011 to March 2014. These aftershocks were plotted for the time periods from November 2011 through March 2012 to March 2014 and ≈ 5000 aftershocks were retained in the depth versus distance cross-sections to detect the clusters in the first step of study (November 2011–March 2012). The focal depth distribution of the aftershock clusters, the migration of hypocenter activity and microseismicity clusters were analyzed and the distributional patterns of the detected clusters were assessed using the geometric distribution of the aftershock hypocenters. The spatial and temporal distribution of aftershocks reveal interesting key features of the deep rupture complexity of the Van earthquake: (1) most prominent aftershocks have been located in the upper crust at depths shallower than 10 km beneath ruptured area, indicating that the upper crust is brittle and seismogenic; (2) two spatial clusters have been detected at 8-10 km depths and the upward extrapolation of these clusters intersects with faults; the main cluster (60 km wide) bounded by inferred reverse faults (f3 and f4) and the central cluster (25–30 km wide) bounded by faults (f1 and f2); (3) these spatial clusters form the largest volumetric pattern of the conical-shaped cluster at depths of about 25–30 km of the azimuth-dependent rotational projections, suggesting azimuthal distributions of deep rupture characteristics; and (4) the strongest temporal cluster of microseismicity derived from temporal distribution of aftershocks has been detected within an area of about 2.5–3.0 km² and it is spatially observed at 20 km depth within the central cluster, suggesting progressive failure of the adjacent patches of possible fault.

Although the phenomenon of serial killers has received great attention from media, governments, and public, very little information is known about them and very few theories are presented by researchers specifically their definition and motives for killing. Through cross tabulation analysis of top ninety-eight serial killers, this present study poses six questions that investigate the correlations between, offender's gender, offender's level of education, time span of killing, killing severity, number of victims, killer's type of abuse, motives for killing, and victim's profile. Findings show that males kill more than females and for longer time, less educated serial killers kill more horribly, female serial killers consider their family members easy target, and finally males kill most for enjoyment and sex and females kill for financial gains.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

Bulukumba Regency, South Sulawesi, Indonesia is one of the centres for whiteleg shrimp, Litopenaeus vannamei production that applies intensive technology. However, no information has been obtained regarding the characteristics and status of water quality in coastal areas with environmentally friendly concepts and the potential to receive a waste load. The study aimed to determine the performance of whiteleg shrimp culture in relation to temporal and spatial aspects and characteristic and water quality status. Measurement and sampling of water were carried out before stocking/initial of culture whiteleg shrimp (rainy season) and end of culture/after harvesting of whiteleg shrimp (dry season) at two locations in the coastal area of ​​Bulukumba Regency, namely Bonto Bahari Subdistrict (BB) and Gantarang Subdistrict (GT). Variables measured and analyzed included temperature, salinity, pH, dissolved oxygen, nitrate, nitrite, ammonia, phosphate, total suspended solids, and total organic matter. Data analysis with descriptive statistics, multivariate statistics, and non-parametric statistics. The Storet (Storage and Retrieval) method was used to determine the water quality status. The results showed that the culture of whiteleg shrimp was technology-intensive with a stocking density of 110 - 220 ind/m² with productivity between 13.9 - 44.4 tons/ha/cycle. The predicted waste load of N is 28.00 tons/cycle and P reaches 6.61 tons/cycle. Another result was that changes in water quality status during the rainy season were classified as moderately polluted at the BB location and complying quality standards at the GT location, while in the dry season, both locations were categorized as heavily polluted. Variables of water quality that caused the decrease in water quality status in both locations (BB and GT) were observed to increase salinity, nitrate concentration, and ammonia concentration. However, there was a decrease in dissolved oxygen concentration in the dry season.

The main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

The study shows that the volumes and surfaces of the $n$-simplices, $n$-orthoplices, $n$-cubes, and $n$-balls are holomorphic functions of $n$, which makes those objects omnidimensional. Furthermore, the volume of an $n$-simplex is shown to be a bivalued function of $n$, and thus the surfaces of $n$-simplices and $n$-orthoplices are also bivalued functions of $n$. Applications of these formulas to the omnidimensional polytopes inscribed in and circumscribed about $n$-balls reveal previously unknown properties of these geometric objects in negative dimensions. In particular, for $0 < n < 1$, the volumes of the omnidimensional polytopes are larger than those of circumscribing $n$-balls, while their volumes and surfaces are smaller than the volumes of inscribed $n$-balls. Reflection relations around $n = 0$ for volumes and surfaces of these polytopes inscribed in and circumscribed about $n$-balls are disclosed. Specific products and quotients of volumes and surfaces of the omnidimensional polytopes and $n$-balls are shown to be independent of the gamma function.

Amphiphilic block copolymers of N-vinyl pyrrolidone (NVP) and various vinyl esters (VEs), PNVP-b-PVEs, namely vinyl butyrate (VBu), vinyl decanoate (VDc) and vinyl stearate (VSt) were synthesized by RAFT polymerization techniques. The sequential addition of monomers methodology was employed starting from the polymerization of NVP followed by the polymerization of the VEs monomer. The reaction was conducted at 80oC in dioxane solutions using AIBN as initiator and O-ethyl S-(phthalimidylmethyl) xanthate as the CTA. The block copolymers were characterized by Size Exclusion Chromatography (SEC) and NMR spectroscopy. The thermal transitions of the copolymers were studied by Differential Scanning Calorimetry (DSC), whereas their thermal stability via Thermogravimetric Analysis (TGA) and Differential Thermogravimetry (DTG).

Atmospheric pollens were investigated using the Lanzoni VPSS 2000 device for 2 years between 2012 and 2013 in the Sarıkamış district of Kars province, one of the highest regions of Türkiye. A total of 37909 pollen grains were collected; 15,298 pollen grains in 2012 and 22611 pollen grains in 2013. Out of 43 identified taxa, 21 were arboreal and 22 were non arboreal. Pollen from arboreal plants accounted for 36.34% (13778 pollen) of the total, while pollen from non arboreal plants accounted for 63.56% (24095 pollen). The most frequent arboreal plants pollen in the Sarıkamış atmosphere were Pinaceae (29.79%), Cupressaceae/Taxaceae (2.54%), and Morus (1.30%). The main non arboreal plants pollen in the atmosphere of Sarıkamış were Poaceae (44.60%), Artemisia (2.98%), Amaranthaceae (2.79%), Rumex (2.41%), Urticaceae (2.33%), Plantago (2.19%), and Boraginaceae (1.40%). The maximum pollen concentration was observed in June.

To achieve n-type doping in diamond, extensive investigations employing first principles have been conducted on various models of phosphorus doping and boron-phosphorus co-doping. The primary focus of this study is to comprehensively analyze the formation energy, band structure, density of states, and ionization energy of these structures. It is observed that within a diamond structure solely composed of phosphorus atoms, the formation energy of an individual carbon atom is excessively high. However, the substitution of two carbon atoms leads to the conversion of diamond into a p-type semiconductor. Upon examining the P-B co-doping structure, it is revealed that the doped impurities exhibit a tendency to form more stable cluster configurations. As the separation between the freely doped atoms and the cluster impurity structure increases, the overall stability of the structure diminishes, consequently resulting in an elevation of the ionization energy. Analysis of the electronic density of states demonstrates that the electron orbit of the B atom makes negligible contributions to the impurity levels during P-B doping.

Sensitive and precise nucleic acid detection is critical for clinical diagnostics and biotechnological advancements. Diagnostic in infectious disease field is very unique from diagnosing any other disease, that is time is of the essence; in outbreaks people die even with each passing hour in some cases, if the correct diagnosis wasn't make; for example Zika in particularly is a very challenging virus to diagnose, because it's in very few numbers of copies in the infected person, so it need high sensitive diagnostic approach to spot it, In particular, the advanced tools SHERLOCKv2 and DETECTR, give almost an immediate detection of attomolar amounts of pathogenic nucleic acids with specificity similar to that of PCR but with slight technical settings and that will guide the correct intervention for the patient. SHERLOCKv2 and DETECTR technologies are game changers for our ability to identify infectious disease and rapid detection of tumor DNA or cancer-related viruses with ultra-sensitive tests that don’t require a lot of complicated processing to go through. In this paper, we will review cutting-edge infectious disease diagnosis by CRISPR-Cas systems.

Currently SARS-CoV-2 is spreading around the world as an Omicron strain. Recently, the Omicron variants (BQ.1 and BQ.1.1) were identified as novel Variants of Concern. UpToDate, there is little information about the Omicron Variants BQ.1 and BQ.1.1. The widely altered Omicron variants are spread globally, providing a high risk of infection surges with devastating consequences in some areas. The Omicron type of SARS-CoV-2 has a harm risk of reinfection, according to early reported findings. COVID-19 Variants particularly, BQ.1 and BQ.1.1 have gained global attention and caused a worldwide sensation since their discovery. Therefore, this communication discusses the present status of COVID-19 Variants BQ.1 and BQ.1.1, and their consequences.

Antioxidant, anti-inflammatory and chemo-preventive features have been reported for the carotenoid diatoxanthin. Diatoxanthin is only produced by a few groups of microalgae where it functions in photoprotection. Its large-scale production in microalgae is currently not feasible. In fact, rapid conversion into the inactive pigment diadinoxanthin is triggered when the cells are removed from the high-intensity light source, which will be the case during large-scale harvesting of microalgae biomass. Zeaxanthin epoxidase (ZEP) 2 and/or ZEP3 have been suggested to be responsible for the back-conversion of high-light accumulated diatoxanthin to diadinoxanthin in low light in diatoms. Using the CRISPR/Cas9 gene editing technology we knocked out the ZEP2 and ZEP3 genes in the already commercially used marine diatom Phaeodactylum tricornutum to investigate their role in the diadinoxanthin-diatoxanthin cycle, and to determine if one of the mutant strains could function as a diatoxanthin production line. Light shift experiments proved that ZEP3 encodes the enzyme converting diatoxanthin to diadinoxanthin in low light. Loss of ZEP3 caused the high-light accumulated diatoxanthin to be stable for several hours after the cultures had been returned to low light, suggesting that zep3 mutant strains could be suitable as commercial production lines of diatoxanthin.

Emerging infectious diseases (EIDs) continue to be a problem all across the world, but in certain areas the threat is greater than in others. The detection of new diseases will aid in the focus of surveillance efforts. Specifically, identifying a "patient zero" is critical step to help limit further transmission. In fact, several factors have been found to contribute to emerging infectious diseases emergence and transmission. Antigenic drift is an important factor that affects vaccine effectiveness and it is important for scientists and healthcare providers alike to understand how this process works in order to ensure that people receive effective vaccinations against infectious diseases. However, recent advances in biotechnology, immunology and artificial intelligence have enabled us to make progress in diagnosis, treatment, prevention and control of infectious diseases. The fight against infectious diseases will always be ongoing, but the advancement of bioscience offers a promising outlook for the near future. In the last two decades, several high impact zoonotic disease outbreaks have been linked to bat-borne viruses. These include SARS coronavirus, Hendra virus and Nipah virus. In addition, it has been suspected that ebolaviruses and MERS coronavirus are also linked to bats. It is being increasingly accepted that bats are potential reservoirs of a large number of known and unknown viruses, many of which could spillover into animal and human populations. In this article, we discuss the potential risk factors that contribute in emerging infectious diseases. Also, we discuss the management of disease prevention and control.

In this work, the Pumped Storage Unit (PSU) is proposed to be integrated with wind-thermal generation system owned by a company whose aim is to maximize its profit through optimal self-scheduling of its units by finding the best bidding strategy in day-ahead energy market. The mathematical formulation of the scenario based unit-commitment and coordinated trading problem is formulated as a stochastic mixed integer linear program. The formulation takes into account several uncertain parameters; such as the wind power generation, energy market prices, and imbalances up/down prices. The expected total profit obtained from energy trading with and without coordinating pumped storage system (PSS) with thermal-wind generation system were compared, and a significant improvement in profit resulted from coordination was observed. Furthermore, coordination between PSS and wind-thermal generation improve the conditional value at risk (CVaR) which monitors the biding risk level.

Social media platforms are not serving only as tools of communication rather they are acting like intricate systems managing our interactions. A major setback to our interactions occur when the flow of information in these networks gets distorted through polarization. It resembles a society where every debate turns into divide. Our research focuses exclusively on quantifying polarization as well as solving this issue head-on. In order to accurately gauge polarization, we’ve developed a new method that takes into consideration majority of its influencing factors. This helps us in correctly quantifying the polarization value of a given network and then by proposing it as an optimization problem we are attempting to maximally decrease polarization while staying within the set budget. We test our method on synthetic and real-world data sets, and find out that polarization is declining, and diversity is increasing. This proves that our recommendation engine has a penchant for finding the ideal connections between the nodes to start a dialogue. Our research presents a successful tactic to quantifying and reducing polarization in social media networks. The results indicate that our novel metric and intervention technique are effective in dismantling echo chambers, thereby promoting diversity in these networks.

Respiratory viral infections, including influenza, respiratory syncytial virus (RSV), and, more recently, the coronavirus disease 2019 (COVID-19) pandemic, continue to pose significant global health threats. Conventional treatments for these infections often face challenges such as limited efficacy, the emergence of drug-resistant strains, and the requirement for frequent administration. In recent years, nanobodies have emerged as a promising class of therapeutic agents due to their unique properties, including small size, high stability, and specific binding capabilities. This mini-review article focuses on the application of nanobodies as spray and aerosol particles for the treatment of respiratory viral infections. Furthermore, we highlight the remarkable efficacy of nanobodies in preclinical and clinical studies against respiratory viruses, including their ability to neutralize viral particles, inhibit viral replication, and modulate the host immune response. We discuss the potential advantages of using nanobodies as inhalable formulations, including their improved delivery to the respiratory tract, enhanced stability in aerosol form, and reduced systemic side effects. Additionally, we explore the various strategies employed to engineer nanobodies for optimal aerosol delivery, such as conjugation to carrier particles or formulation as dry powders. We also examine the potential challenges and limitations associated with the development of nanobody-based aerosol therapies, including production scalability, cost-effectiveness, and regulatory considerations.

Background and objectives: The fact that the results of troponin and Nt-proBNP interfere from biotin caused some commercial firms to update their measurement methods. In particular, the clinical incompatibility of cardiac test results may affect the risk of morbidity and mortality. The aim of this study is to investigate the interference effects of 7 different contrast agents on cardiac markers (Troponin-I, Nt-proBNP, Mass CK-MB, CK, AST, LDH) and coagulation tests (PT, APTT). Materials and Methods: Seven different contrast medias were added into control materials by using interference protocol. Concentration of PT, APTT, CK, AST, LDH, Mass CK-MB, Troponin-I, Nt-proBNP were measured by Sysmex CS-2100, Abbott c16000, Siemens Centaur XP and AFİAS-6 analyzer. The amount of deviations from target values were calculated. Results: 7 different contrast medias caused negative interference in troponin levels between 57.43% and 62.87%. It was found that different contrast medias produced false negativity in the Nt-proBNP test ranging from 6.11% to 96.01%. Enzymes and coagulation tests have been less affected. Conclusions: Different contrast medias may cause false negative cTnI and Nt-proBNP. Therefore, the contrast medias which causes the least interference should be preferred. The results of samples taken in the first hour of contrast imaging should be interpreted with care.

Background and objectives: This study were designed to determine uric acid concentration and renal histopathology of M. calabura L. stem bark extract in diabetic rats and to compare the natural product of M. calabura L. stem bark extract with allopurinol. Materials and Methods: A completely randomized design was used for the experiment which consisted of 6 treatment groups, each consisting of 4 rats, as follows: 1) NR, normal rat; 2) KN, diabetic rat (negative control); 3) KP, diabetic rats given allopurinol 10 mg/kg body weight; 4) EM150, diabetic rats given the test extract 150 mg/kg body weight/day; 5) EM300, diabetic rats given the test extract 300 mg/kg body weight/day; and 6) EM450, diabetic rats given the test extract 450 mg/kg body weight/ day. Results: The results showed that M. calabura L. stem bark extract decrease (p<0.05) uric acid levels in diabetic rats and no specific damage to renal proximal tubular cells was seen. Conclusions: It was concluded that M. calabura L. stem bark extract has a potential as an antihyperuricemic in diabetic rats. The recommended does was 300 mg/kg body weight to provide a significant effect on reducing the uric acid level in diabetic rats. Our findings support the use of this plant as a treatment for gout and other inflammatory diseases.

Focal vibration therapy can provide neurophysiological benefits. Unfortunately, standardized protocols are non-existent. Previous research presents a wide range of protocols with a wide range of effectiveness. This paper is part of a broader effort to identify effective, standardized protocols for focal vibration therapy. The vibration characteristics of four commercially available focal vibration devices that have been used for research and clinically were measured. An accelerometer was used for the measurements. Frequency and peak-to-peak amplitude were measured. Measurements were made when the devices were free and then again when they were strapped to the human body. Vibration frequency ranged from 120 to 225 Hz. Free vibration amplitude ranged from 2.0 to 7.9 g’s (peak-to-peak). When the devices were strapped to the body (constrained), vibration amplitude decreased by up to 65.7%. These results identify effective ranges of focal vibration frequency and amplitude. They illustrate the importance of identifying vibration environment, free or constrained, when quoting vibration characteristics. Finally, the inconsistency of multi-actuator devices is discussed. These results will guide protocol development for focal vibration and potentially better focal vibration devices.

The purpose of this study is to investigate the effect of academic advising on changing or maintaining majors in university degrees. It is also a goal of the study to determine which semester of the course study is most likely or less likely witness the change of major and whether advising contributes to that change. Through this correlational study, the researchers explored students’ perceptions about the academic advising they received and the relationship of its absence on students’ major change. The participants were 1725 undergraduate students from all year levels. One survey is used to collect the data for this study: Influences on Choice of Major Survey. Based on the findings, it is found that university advisors have a very poor effect on students' decisions to select their majors as 45.6% of the 1725 participants indicate NO influence of advising in their survey answers. Whereas career advancement opportunities, students' interests, and job opportunities indicate a strong effect on their majors’ selections as they score the highest means of 3.76, 3.73, 3.64 respectively. In addition, findings show that students are most likely changing their majors in their second year and specifically in the second semester. Second year major change scored 36.9% in the second semester and 30.9% in the first semester. More importantly, results indicate that there is a positive significant correlation between college advisor and change major in the second year (p = 0.000). It is to researchers understanding based on the findings that when students receive enough academic advising in the first year of study and continues steadily to the next year, the possibilities of students changing their majors decreases greatly.

Zirconium nitride (Zr-N) is a candidate material for inert matric fuel elements in breeder reactors. They have shown exceptional resistance to radiative corrosive environments. They have shown excellent resistance to radiation stability at operational conditions in current generation reactors. But being a candidate nuclear fuel material in generation reactors, their radiation stability at higher temperature conditions observed has not been reported. We have employed molecular dynamics simulations to study the damage cascades and radiation stability of ZrN at 600K. The process of primary damage evolution by considering varying overlapping cascades with 10, 20 keV incident PKA’s reported here. The defects interface interaction and diffusion mechanism at the interface are reported.

In the pre era of synthetic antibodies, pharmaceutical companies depend on finding novel drugs from medicinal plants and other traditional resources; while in present, technological advances in biology, computer and robotics give the researchers the ability to rewrite and edit DNA in order to synthesize very large sets of drug candidates; these novel and improved candidates serves the basis for creating another library of drug candidates and so on until we find the right biomolecule for the disease of interest. all these technologies combined together to synthesize therapeutic antibodies for many types of cancer, autoimmune diseases, and infectious diseases, that can address diseases much more readily to very rapidly get therapeutics into patients so that we can potentially have an impact on disease. The antibodies mechanism is recognize and bind to disease cells and pinpoint the immune system to attack those cells effectively. Now a days, they dependent on computational approach to guide and accelerate the process of antibodies engineering by combination of selection system and use of high-throughput data acquisition and analysis to build and construct populations of next generation antibodies that are thermo-stable, non-immunogenic as possible, and to be administered to many humans as possible. In this review, I will discuss the latest in silico methods for antibodies engineering.

Background and Objectives: The current study aimed to determine the impact of fasciotomy on mortality and morbidity in children and adults with crush-related AKI following the 2023 Kahramanmaraş earthquakes. Materials and Methods: The study included individuals who had suffered crush injuries after the 2023 Kahramanmaraş earthquakes and were identified as having acute kidney injury (AKI). Patients with AKI were divided into two groups based on age: those under 18 years and those over 18 years. A comparative analysis was conducted between the mortality and morbidity rates of patients who underwent fasciotomy and those who did not. Disseminated intravascular coagulopathy (DIC), sepsis, and adult respiratory distress syndrome (ARDS) have all been identified as contributors to morbidity. Results: The study was conducted with a total of 40 patients (21 males and 19 females) aged between four and 83 years. A total of 21 patients underwent fasciotomy and the patients underwent varying numbers of fasciotomy, ranging from zero to 11. The mortality rate was 12.5%, corresponding to five adult patients. No instances of mortality were reported in the paediatric cohort. The application of fasciotomy in instances of crush-induced AKI did not result in elevated levels of mortality in either the paediatric or adult demographic. Within the adult population, a substantial difference in the duration of dialysis was observed between individuals who underwent fasciotomy and those who did not. A statistically significant increase in the number of fasciotomy incisions was observed in patients diagnosed with sepsis compared with those without sepsis. The study found a significant positive correlation between the number of fasciotomy incisions and dialysis days. Conclusions: Neither adult nor paediatric patients with crush-induced AKI showed an increased risk of death after fasciotomy. The number of fasciotomy incisions significantly correlated with the development of sepsis. Despite experiencing delays in hospital admission for paediatric patients, the incidence of both crush syndrome and mortality rates among children remained relatively low.

This paper presents a theory on graph topological structure and graph coloring, proving that for any N-order graph structure (with a topological structure similar to ), the maximum number of colors required for coloring is less than or equal to . The Four Color Theorem is just one special case of this theory, with the maximum structure size for a four-color graph being a 4-order structure graph, hence requiring only a maximum of 4 colors for coloring.

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

Based on 2010, 2013 and 2015 CGSS data, the impact of Internet use and social capital on the income gap among farmers in the past five years is assessed at three time points using the OLS method and a quantile regression method. The study finds that (1) the income gap among farmers increases continuously in the five-year period, while Internet use plays a positive impact on farmers’ income growth in all five quartiles; the coefficient differences are all significantly negative, indicating that Internet use plays a positive role in alleviating the income gap between high-income and low-income farmer subgroups, and (2) social capital plays a positive role in moderating the income gap among farmers and that Internet use by farmers expands the boundary of social capital, which in turn increases the income level of and alleviates the income gap among farmers.

Capacity Expansion Models (CEMs) are optimization models used for long-term energy planning on national to continental scale. They are typically computationally demanding, thus in need of simplification, where one such simplification is to reduce the temporal representation. This paper investigates how using representative periods to reduce the temporal representation in CEMs distorts results compared to a benchmark model of a full chronological year. The test model is a generic CEM applied to Europe, equipped with a novel formulation for storage in model versions with reduced temporal representation. We test the performance of reduced models at penetration levels of wind and solar of 90%. Three measures for accuracy are used: (i) system cost, (ii) total capacity mix and (iii) regional capacity. We find that: (i) the system cost is well represented (~5% deviation from benchmark) with as few as ten representative days, (ii) the capacity mix is in general fairly well (~20% deviation) represented with 50 or more representative days, and (iii) the regional capacity mix displays large deviations (>50%) from benchmark for as many as 250 representative days. We conclude that modelers should be aware of the error margins when presenting results on these three aspects.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

This study investigates the performance and environmental impact of n-butanol blended with Jet-A fuel in turbo-engines, aiming to assess its viability as a sustainable aviation fuel (SAF). The research involves experimental testing of various blends, ranging from low to high concentrations of methanol, to determine their effects on engine performance and emissions. The experimental setup includes comprehensive measurements of engine parameters such as thrust, fuel consumption rates, and exhaust gas temperatures. Emissions of nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and unburned hydrocarbons (HC) are also analysed to evaluate environmental impacts. Key findings indicate that n-butanol/Jet-A blends can significantly enhance combustion efficiency and reduce emissions compared to conventional Jet-A fuel. Higher n-butanol concentrations lead to improved thermal efficiency and lower NOx and CO emissions. However, PM emissions slightly increase with higher methanol content. The study underscores the potential of n-butanol as a SAF for turbo-engines, highlighting its ability to mitigate environmental impacts while maintaining or improving engine performance. This research supports the feasibility of integrating n-butanol into Jet-A blends for turbo-engine applications, emphasizing its role in achieving more environmentally friendly aviation operations.

BACKGROUND: Lower limb skeletal muscle ischemia-reperfusion (IR) injury associated with increased morbidity and mortality is common in several clinical situations such as aortic aneurysms repairment, peripheral arterial surgery, vascular injury repairment, and shock. Although it is generally accepted that oxidative stress mediators have a significant role in IR injury, its precise mechanism is still unknown. Anecdotally, it is sustained not only by structural and functional changes in the organ it affects but also by damage to distant organs. The purpose of this report is to illustrate the effect of proanthocyanidin on IR injury. METHODS: In our study, 18 male Wistar albino rats were used. The subjects were divided into three groups of six each. (Group Control-C, Group Ischemia-Reperfusion -IR, Group Ischemia-Reperfusion and Proanthocyanidin-IR-PRO). Intraperitoneal proanthocyanidin was given to the IR and proanthocyanidin groups 30 minutes before laparotomy and 1-hour ischemia led to these two groups. After one hour, reperfusion started. Muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, muscle oval-central nucleus ratio, leukocyte cell infiltration, catalase enzyme activity, and TBARS were all examined in lower-limb muscle samples after one hour of reperfusion. RESULTS: When skeletal muscle samples were evaluated histopathologically, it was discovered that muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, and leukocyte cell infiltration with oval-central nucleus standardization were significantly higher in the IR group than group control and group IR-proanthocyanidin. Besides, oval-central nucleus standardization was significantly higher in the IR and proanthocyanidin group than in the control group. TBARS levels were significantly higher in the IR group than in the control and IR-proanthocyanidin groups while, catalase enzyme activity was found to be significantly lower in the IR group than in the control and IR and proanthocyanidin groups. CONCLUSION: As a consequence of our research, we discovered that proanthocyanidins administered before IR have a protective impact on skeletal muscle in rats. Further research in this area is required.

Climate change affects both human and natural systems. Afghanistan ranked globally on the top of highly vulnerable countries to the adverse effects of climate change. The agricultural communities of Afghanistan is highly affected by climate change. Understanding farmers’ real experiences on changing climate become crucial in planning the future adaptation strategies. This study assessed the farmers' perception of climate change and its impacts on farming communities. Primary data were collected through face-to-face interviews conducted with 120 household heads. Additional qualitative data were collected by conducting 4 Focus Group Discussions (FGDs), 4 Historical Timeline Calendars (HTCs), 18 Key Informant Interviews (KII), and sketches of 4 Crop Calendars. The study reveals that climate indicators have varied and changed. The farmers express their experiences of decreasing snowfall in winter and annual rainfall in spring and summer, which led to the intensity and frequency of drought and water shortages for agriculture and rangelands in the upper and lower part of the valleys. The temperatures in winter and summer have increased and led to earlier snow melting, earlier blooming, flowering, and greening of the plants. These changes affected both positively and negatively. There is a half-month new opportunity for cultivation and increased earlier animal ranching in the rangelands. These findings can be valuable inputs for developing effective and efficient adaptation strategies.

The corrosion morphology in grade 2205 duplex stainless steel wire has been studied to understand the nature of pitting and the causes of the ferrite phase's selective corrosion in acidic NaCl solution. It is shown that the corrosion mechanism is always pitting, which either manifests lacy cover perforation or densely-arrayed selective cavities developing on the ferrite phase. Pits with a lacy metal cover form in concentrated chloride solutions, whereas the ferrite phase's selective corrosion develops in diluted electrolytes, showing dependency on the chloride-ion concentration. The pit perforation is probabilistic and occurs on both austenite and ferrite grains. The lacy metal covers collapse in concentrated solutions but remain intact in diluted electrolytes. The collapse of the lacy metal cover happens due to hydrogen embrittlement. Pit evolution is deterministic and occurs selectively in the ferrite phase in light chloride solutions.

With an increased interest in applications that require a clean background image, such as video surveillance, object tracking, street view imaging and location-based services on web-based maps, multiple algorithms have been developed to reconstruct a background image from cluttered scenes. Traditionally, statistical measures and existing image quality techniques have been applied for evaluating the quality of the reconstructed background images. Though these quality assessment methods have been widely used in the past, their performance in evaluating the perceived quality of the reconstructed background image has not been verified. In this work, we discuss the shortcomings in existing metrics and propose a full reference Reconstructed Background image Quality Index (RBQI) that combines color and structural information at multiple scales using a probability summation model to predict the perceived quality in the reconstructed background image given a reference image. To compare the performance of the proposed quality index with existing image quality assessment measures, we construct two different datasets consisting of reconstructed background images and corresponding subjective scores. The quality assessment measures are evaluated by correlating their objective scores with human subjective ratings. The correlation results show that the proposed RBQI outperforms all the existing approaches. Additionally, the constructed datasets and the corresponding subjective scores provide a benchmark to evaluate the performance of future metrics that are developed to evaluate the perceived quality of reconstructed background images.

The rapid development of technology has led to the implementation of data-driven systems whose performance heavily relies on the amount and type of the data itself. In the latest decades, in the fields of bioengineering data management, among others, eye-tracking data has become one of the most interesting and essential components for many medical, psychological, and engineering research applications. However, despite the large usage of eye-tracking data in many studies and applications, a strong gap is still present in the literature regarding real-time data collection and management, which led to strong constraints for the reliability and accuracy of on-time results. To address this gap, this study aims to introduce a system that enables the collection, processing, real-time streaming, and storage of eye-tracking data. The system is developed by using Java programming language, WebSocket protocol, and Representational State Transfer (REST), improving the efficiency in transferring and managing eye-tracking data. Results were computed in two test conditions, i.e., local and online scenarios, within a time window of 100 seconds. The experiments conducted for this study were carried out by comparing the time delay between two different scenarios. Even if preliminary, results showed a significantly improved performance of data management systems in managing real-time data transfer. Overall, this system can significantly benefit the research community by providing real-time data transfer and storing the data, enabling more extensive studies using eye-tracking data.

This study aimed to screen the antibacterial activity of essential oils from different parts (leave and stem) of Salvia officinalis against some Gram positive and Gram negative bacteria using agar disc diffusion test, then the extracts were prepared by hydro distillation to extract the essential oils. Maceration and hexane extraction by Soxhlet were used to obtain crude extracts from the leave and stem. Essential oils from the leaves and the ethyl acetate extract of the leaves showed higher antimicrobial activity, while hexane extract of leaves and stems showed moderate antibacterial activity. In contrast the essential oil from the stems showed very low antibacterial activity. It was observed that the results gram positive bacteria (staphylococcus aureus) was more sensitive than Gram negative (Echerichia coli).

Reducing fertilizer-N rate, applying nitrification inhibitor (NI), and incorporating straw are widely recommended to improve N use efficiency of crops and decrease N losses. However, how these practices affect crop N uptake by regulating the fertilizer-N fate during the growing season is not well understood. We conducted a field 15N tracer study to explore the effectiveness of reduced N application, NI, and straw incorporation on fertilizer-N fates for maize cultivation in Northeast China. The following six treatments were used: 1) no N fertilization (control); 2) 200 kg urea-N ha−1 (100%N); 3) 200 kg urea-N ha−1 and 2400 kg dry-straw ha−1 (100%N+S); 4) 160 kg urea-N ha−1 (80%N, i.e., 20% reduction of N fertilization); 5) 160 kg urea-N ha−1 and nitrification inhibitor (Nitrapyrin) (80%N+NI); 6) 160 kg urea-N ha−1, nitrification inhibitor and 2400 kg dry-straw ha−1 (80%N+NI+S). Our results showed that the five N fertilization treatments yielded 16%–25% more grain and 39%–60% more crop N uptake than the control receiving no N fertilizer, but the differences among the five treatments were not statistically significant. In contrast to plant growth, changes in fertilizer-N fates in soil and plant pools were more pronounced. Compared with the 100%N treatment, 20% fertilizer-N reduction (80%N) decreased 15N concentration in topsoil and plant pools but increased the proportion of plant 15N recovery at harvesting (N use efficiency, NUE15N, 60% vs. 50%) (P &lt; 0.05). Nitrapyrin co-application (80%N+NI) delayed soil nitrification and increased soil 15N retention at harvesting (52% vs. 36%), thereby decreasing NUE15N significantly (P &lt; 0.05). Straw incorporation (100%N+S) decreased fertilizer-N retention compared with NI co-application because it promoted NUE15N significantly (P &lt; 0.05). The combined application of NI and straw (80%N+NI+S) was more conducive to fertilizer-N retention in soil. Our findings demonstrate that NI and straw additions are efficient strategies for stabilizing fertilizer-N in soils and potentially minimizing N loss; however, their effects on NUE15N vary and the related mechanism must be further clarified in long-term trials.

Of the 100,000 railroad bridges in the United States, 50% are over 100 years old. Many of these bridges do not meet the minimum vertical clearance standards, making them susceptible to impacts from over-height vehicles. Impacts can cause structural damage and unwanted disruption to railroad bridge services; rapid notification of the railroad authorities is crucial to ensure that the bridges are safe for continued use and to affect timely repairs. Therefore, researchers have developed approaches to identify these impacts to railroad bridges. Some recent approaches use machine learning to more effectively identify impacts from the sensor data. Typically, the collected sensor data is transmitted to a central location for processing. However, the challenge with this centralized approach is that the transfer of data to a central location can take considerable time, which is undesirable for time-sensitive events like impact detection that require rapid assessment and response to potential damage. To address the challenges posed by the centralized approach, this study develops a framework for edge implementation of machine learning predictions on wireless smart sensors. Wireless sensors are used because of their ease of installation and lower costs compared to their wired counterparts. The framework is implemented on the Xnode wireless smart sensor platform, thus bringing artificial intelligence models directly to the sensor nodes and eliminating the need to transfer data to a central location for processing. This framework is demonstrated using data obtained from events on a railroad bridge near Chicago; results illustrate the efficacy of the proposed edge computing framework for such time-sensitive structural health monitoring applications.

The compound, C27H23N3 (1), crystallizes in the triclinic system of the P-1 space group. The unit cell comprises a dimer of 1, in which the monomers are linked by two complementary hydrogen bonds between N1 and H1-C1 of another molecule. The dimers form chains along the a-axis through intermolecular interactions between the N2 acceptor atoms and C17 donors from molecules in the nearest neighbouring dimer. These interactions form extended sheets of the dimers of 1, along the ab plane. The quinolinylmeth-2-yl groups of 1 lie in almost orthogonal planes and their N1/2(q) donor atoms being away from the apical amino N3 atom.

DFT calculations on the photoisomerization reactions of pyridazine N-oxide derivatives are presented. The irradiation of 3,6-diphenylpyridazine N-oxide allowed to obtain the first excited singlet state that underwent to a ring opening reaction induced to the oxygen migration to the adjacent carbon atom, with the formation of a diazo derivative. This intermediate can give a ring closure reaction to give a pyrazole derivative, or, with a higher transition energy, it can lose nitrogen allowing the formation of 2,5-diphenylfuran. The irradiation of 3-phenylpyridazine N-oxide allowed the formation only of 2-phenylfuran. In this case, calculations allowed to explain this behavior. The first excited singlet state gave a photoisomerization reaction with the formation of the corresponding diazo intermediate. This intermediate could not be converted into the corresponding pyrazole derivative because it was converted into a N-formyl pyrazole never reported in literature. The only possible reaction is the loss of nitrogen and the formation of 2-phenylfuran.

The study examines n-balls, regular n-simplices, and n-orthoplices in real dimensions using novel recurrence relations that removed indefiniteness present in known formulas. They show that in the negative, integer dimensions volumes of n-balls are zero if n is even, positive if n = -4k - 1, and negative if n = -4k - 3, for natural k. Volumes and surfaces of n-cubes inscribed in n-balls in negative dimensions are complex, wherein for negative, integer dimensions they are associated with integral powers of the imaginary unit. The relations are continuous for n Î ℝ and show that the constant of π is absent for 0 ≤ n < 2. For n < -1 self-dual n-simplices are undefined in the negative, integer dimensions, and their volumes and surfaces are imaginary in the negative, fractional ones, and divergent with decreasing n. In negative, integer dimensions n-orthoplices reduce to the empty set, and their real volumes and imaginary surfaces are divergent in negative, fractional ones with decreasing n. Out of three regular, convex polytopes present in all natural dimensions, only n-orthoplices, n-cubes (and n-balls) are defined in the negative, integer dimensions.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

Community-acquired pneumonia (CAP) is among the most common causes of death and one of the leading healthcare concerns worldwide. It can evolve into sepsis and septic shock, which have a high mortality rate, especially in critical patients and comorbidities. The definitions of sepsis were revised in the last decade as “life-threatening organ dysfunction caused by a dysregulated host response to infection”. Procalcitonin (PCT), C-reactive protein (CRP), and complete blood count including white blood cells are among the most commonly analyzed sepsis-specific biomarkers also used in pneumonia in a broad range of studies. It appears to be a reliable diagnostic tool to expedite care of these patients with severe infections in the acute setting. PCT was found superior to most other acute phase reactants and indicators, including CRP as a predictor of pneumonia, bacteremia, sepsis and poor outcome. In addition, PCT use is beneficial to judge timing for cessation of antibiotic treatment in most severe infectious states. The clinicians should be aware of strengts and weaknesses of known and potential biomarkers in expedient recognition and management of severe infections. This manuscript is intended to present an overview of the definitions, complications and outcomes of CAP and sepsis, with special regard to PCT and other important markers.

The receptor-type protein tyrosine phosphatases (RPTPs) are involved in a wide variety of physiological functions which are mediated via their diverse extracellular regions. They play key roles in cell-cell contacts, bind various ligands and are regulated by dimerization and other processes. Depending on the subgroup they have been described as everything from ‘rigid rods’ to ‘floppy tentacles’. Here we review current experimental structural knowledge on the extracellular region of RPTPs and draw on AlphaFold structural predictions to provide further insights into structure and function of these cellular signalling molecules.

Photocatalysis is a promising method for methylene blue (MB) degradation due to its effectiveness and environmental compatibility. Among photocatalysts, titanium dioxide (TiO2) has been widely used for MB degradation due to its exceptional photocatalytic activity. However, the wide bandgap limits the degradation efficiency of TiO2 under visible light. Herein, an interstitial nitrogen-doped TiO2 (5%NT/TiO2) used thiourea as the N source is fabricated for the visible light-derived MB degradation. 5%NT/TiO2 exhibits an extended visible light absorption range. Besides, photoelectrochemical measurement shows an improvement in photocurrent response and charge transfer behavior on N/TiO2. Thus, 5%NT/TiO2 has enhanced photocatalytic activity compared to pristine TiO2 and substitutive N-doped TiO2 (5%NAB/TiO2). The accelerated photocatalytic MB degradation process on N/TiO2 should be mainly attributed to the interstitial N doping, which causes the appearance of new energy states and extended optical properties.

Nanocrystalline silicon oxide (nc-SiOx:H) is a multipurpose material with its varied application in solar cells as a transparent front contact, intermediate reflector, back reflector layer and even tunnel layer for passivating contacts, owing to easy tailoring of its optical properties. In this work, we systematically investigate the influence of gas mixture (SiH4, CO2, PH3 and H2), RF power and process pressure on the optical, structural and passivation properties of thin n-type nc-SiOx:H films prepared in an industrial, high throughput, plasma-enhanced chemical vapor deposition (PECVD) reactor. We provide a detailed description of the n-type nc-SiOx:H material develop-ment using various characterization techniques (SEM, EDX, Raman spectroscopy, and spectro-scopic ellipsometry) with a focus on the relationship between the material properties and the pas-sivation they provide to n-type c-Si wafers characterized by their effective carrier lifetime (τeff). Further, we also outline the parameters to be kept in mind while developing different n-type nc-SiOx:H layers for different solar cell applications. We report a tunable optical gap (1.8 – 2.3 eV) for our n-type nc-SiOx:H films as well as excellent passivation properties with τeff up to 3.5 ms (iVoc ~ 715 mV) before annealing. Oxygen content plays an important role in determining the crystallinity and hence passivation quality of the deposited nanocrystalline silicon oxide films.

Background Increasingly, healthcare organizations are using technology for the efficient management of data. The aim of this study was to compare the data quality of digital records with the quality of the corresponding paper-based records by using data quality assessment framework. Methodology We conducted a desk review of paper-based and digital records over the study duration from April 2016 to July 2016 at six enrolled TB clinics. We input all data fields of the patient treatment (TB01) card into a spreadsheet-based template to undertake a field-to-field comparison of the shared fields between TB01 and digital data. Findings A total of 117 TB01 cards were prepared at six enrolled sites, whereas just 50% of the records (n=59; 59 out of 117 TB01 cards) were digitized. There were 1,239 comparable data fields, out of which 65% (n=803) were correctly matched between paper based and digital records. However, 35% of the data fields (n=436) had anomalies, either in paper-based records or in digital records. 1.9 data quality issues were calculated per digital patient record, whereas it was 2.1 issues per record for paper-based record. Based on the analysis of valid data quality issues, it was found that there were more data quality issues in paper-based records (n=123) than in digital records (n=110). Conclusion There were fewer data quality issues in digital records as compared to the corresponding paper-based records. Greater use of mobile data capture and continued use of the data quality assessment framework can deliver more meaningful information for decision making.

A selective permeable membrane between two different solutions can generate osmotic pressure, Donnan potential, and ion/pH gradients based on various factors such as membrane type, solute concentration and temperature. In this study, we introduce a novel method for extracting energy from ion gradients through an innovative cycle, presenting intriguing experimental findings. Additionally, by leveraging Raoult’s Law, which describes the relationship between vapor pressure and solute presence, in conjunction with osmosis within a closed system, we successfully engineer the simplest iteration of Maxwell’s demon device. This pioneering approach to sustainable energy generation harnesses ambient temperature marking a significant advancement in energy research. Finally this renewable energy source is available all the time and everywhere.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

Air pollution is a critical issue impacting urban environments, leading to severe health problems and environmental degradation. This comprehensive review examines the potential of green systems—specifically green walls, active green walls, and urban greenery systems—to mitigate atmospheric pollutants such as particulate matter (PM), volatile organic compounds (VOCs), and carbon dioxide (CO2). By systematically analyzing 44 recent studies, the review highlights the pollutant capture efficiency of various green technologies and plant species in both indoor and outdoor settings. Active green walls, particularly those utilizing plant species such as Chlorophytum comosum and Sansevieria trifasciata, were found to be highly effective, with VOC reduction efficiencies up to 96.34%, PM reductions by 65.42%, and CO2 reduction rates reaching 4.8% under optimal conditions. The review identifies key strengths in current research, including diverse experimental setups and the use of sophisticated measurement techniques, but also notes significant limitations such as variability in experimental conditions and a lack of long-term performance data. The study underscores the importance of proper maintenance to sustain green systems' efficacy and highlights the potential issue of pollutant resuspension, which remains under-researched. Practical implications for urban planning are discussed, advocating for the integration of effective green systems into urban infrastructure to enhance air quality and public health. Recommendations for future research include the need for standardized metrics, long-term studies, economic feasibility analyses, and real-world validation of simulation models to better understand and optimize green systems for urban air pollution mitigation.

Human decision-making is increasingly supported by artificial intelligence (AI) systems. From medical imaging analysis to self-driving vehicles, AI systems are becoming organically embedded in a host of different technologies. However, incorporating such advice into decision-making entails a human rationalization of AI outputs for supporting beneficial outcomes. Recent research suggests intermediate judgments in the first stage of a decision process can interfere with decisions in subsequent stages. For this reason, we extend this research to AI-supported decision-making to investigate how intermediate judgments on AI-provided advice may influence subsequent decisions. In an online experiment (N=192), we found a consistent bolstering effect in trust for those who made intermediate judgments and over those who did not. Furthermore, violations of total probability were observed at all timing intervals throughout the study. We further analyzed the results by demonstrating how quantum probability theory can model these types of behaviors in human-AI decision-making and ameliorate the understanding the interaction dynamics at the confluence of human factors and information features.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

In this study, Fe, N co-doped biochar (Fe@N co-doped BC) was synthesized by carbonization-pyrolysis method and used as carbocatalysts to activate peroxymonosulfate (PMS) for sulfamethoxazole (SMX) removal. In the Fe@N co-doped BC/PMS system, the degradation rate of SMX (10.0 mg⋅L−1) was 90.2% within 40 min under optimal conditions. The radical quenching experiments, and electron spin resonance (ESR) analysis suggested that sulfate radicals (SO4•−), hydroxyl radicals (•OH) and singlet oxygen (1O2) participated in the degradation process. After the reaction, the proportion of pyrrolic N apparently decreased from 57.9% to 27.1%. Pyrrolic N served as active sites to break the inert carbon network structure and promote the generation of reactive oxygen species (ROSs). Besides, pyrrolic N showed stronger interaction with PMS and significantly reduced the activation energy required for the reaction (∆G = 23.54 kcal/mol). The utilization potentiality of Fe@N co-doped BC was systematically evaluated in terms of its reusability, and selectivity to organics. Finally, the intermediates of SMX were also detected.

Background and Aim: It is generally accepted that oxidative stress mediators play an important role in ischemia-reperfusion injury(I/R), although the exact mechanism is not fully elucidated. While the impact of silymarin on I/R injury in several tissues, including the myocardial, cerebral, gastric and liver tissue, has been examined, the present state of research on this topic remains insufficient to provide a widely accepted understanding. For this purpose, our objective was to examine the effect of silymarin on muscle tissue in rats subjected to lower extremity I/R injury. Method: After ethics committee approval, 18 male Wistar albino rats weighing between 225-275 g were used. The rats were divided into three groups containing six mice each, Control,Ischemia-Reperfusion and Silymarin-Ischemia/Reperfusion groups. Silymarin was administered intraperitoneally 30 minutes before the procedure.( 100 mg/kg-1 ) In the I/R groups, an atraumatic microvascular clamp was placed in the infrarenal abdominal aorta. After 120 minutes, the clamp was removed and reperfusion was achieved for 120 minutes. In muscle tissue samples taken at the end of the reperfusion period; Malondialdehyde (MDA) levels, catalase (CAT) enzyme activity levels and histopathological parameters were compared. Results: In the histopathological examination, no degeneration was observed in the muscle fibers in the control group, while findings of striated muscle damage such as muscle atrophy hypertrophy, muscle degeneration-congestion, internal of the muscle nucleus-oval-central nucleus, fragmentation-hyalinization and leukocyte cell infiltration were observed in the I/R group. In the S-I/R group, muscle atrophy hypertrophy, internal of the muscle nucleus-oval-central nucleus, fragmentation-hyalinization and leukocyte cell infiltration were observed to improve these damaged areas compared to the I/R group. MDA levels in the I/R group were found to be significantly higher than in the control and S-I/R groups. CAT enzyme activity was found to be significantly higher in the I/R group than in the control group. Conclusion:Our study revealed that the administration of silymarin at a dosage of 100 mg/kg-1 by intraperitoneal injection 30 minutes before ischemia in rats effectively decreased lipid peroxidation and oxidative stress. Additionally, it successfully reduced the injury caused by ischemia/reperfusion in muscle histology.

In this study, two donor-acceptor (D-A) type conjugated polymers namely PQSeCz and PQSeFl were designed and synthesized. Selenophene was incorporated as a π -bridge, quinoxaline as an acceptor unit while carbazole and fluorene were used as the donor units. Polymers were synthesized via palladium catalyzed Suzuki polymerization reaction. All molecules were characterized by 1H and 13C NMR Spectroscopy. The weight and number average molecular weights of the two polymers were determined by gel permeation chromatography (GPC). Electrochemical and spectroelectrochemical characterizations of the polymers were performed to investigate their optoelectronic properties. Oxidation potentials were 1.15 V/ 0.82 V and 1.11 V/ 0.82 V for PQSeCz and PQSeFl respectively, while reduction potentials were -1.26 V /-1.14 V and -1.48 V/ -1.23 V, respectively. In the visible region, maximum absorption wavelengths for the two polymers were 551 nm and 560 nm, respectively. Optical band gaps (Egop) were found from the lowest energy π – π∗ transition onsets as 1.71 eV and 1.58 eV, respectively. Both polymers showed good solubility in common solvents.

This study examines whether information about the winners of the Sustainability Reporting Award (SRA) contributes to the usefulness of the information in the financial statements. This study used a sample consisting of 110 winners of SRA (SRA firms) and 110 companies that did not receive SRA (non-SRA firms) from 2008 to 2016. The study found that earnings per share (EPS), book value per share (BVPS), and earnings per share change (EPSC) are value relevant information. Results of comparison between SRA firms and non-SRA fimrs, this study found that EPS positive association with stock price and with returns for SRA firms is higher than that for non-SRA firms. Findings of this study also show that, value relevance of BVPS for non-SRA firms is higher than that for SRA firms. When mesures of Price and BVPS are transformed into natural logarithm, the value relevance of BVPS for SRA firms is higher than that for non-SRA firms. Thus, the results are sensitive to measures of the variables. The findings of this study indicate that information about the winners of SRA contributes to the usefulness of financial statements.

This paper presents the experimental and numerical studies of the vertical stress distribution beneath the centerline of circular footings resting on the sand. Vertical stress values due to circular load in medium-dense sand were measured using soil stress transducers. Reduced-scale laboratory model tests were carried out in a square-shaped test box and vertical stresses were measured at the centerline of the circular footing at different depths of the sand. In order to determine the effect of footing width on vertical stress distribution, laboratory experiments were performed on circular footings of different diameters. In addition, a series of finite element analyses was carried out on the test model to validate the findings of the experimental study. In the numerical analysis, the sand was modeled as a non-linear elastoplastic material. The analyses were performed using the finite element method with two-dimensional axisymmetric and three-dimensional conditions. The results obtained from laboratory model tests and numerical analysis were compared with the vertical stress values obtained from the theoretical solution in the literature. Vertical stress distribution in horizontal planes at any depth from the footing base shows the same characteristic form in all methods. However, some differences were observed between experimental, numerical, and theoretical results and discussed.

Neuropathic pain (NeP) is a complex and debilitating condition that impacts millions of people globally. Although various treatment options exist, their effectiveness is often limited, and they can be accompanied by significant side effects. In recent years, there has been increasing interest in targeting the N-methyl-D-aspartate receptor (NMDAR) as a potential therapeutic approach to alleviate different types of neuropathic pain. This narrative review aims to provide a comprehensive examination of NMDAR antagonists, specifically ketamine, memantine, methadone, amantadine, carbamazepine, valproic acid, phenytoin, dextromethorphan, riluzole, and levorphanol, in the management of NeP. By analyzing and summarizing current preclinical and clinical studies, this review seeks to evaluate the efficacy of these pharmacologic agents in providing adequate relief for NeP.

The reaction of berberine derivatives containing at O-9 position N,N-disubstituted acetamide fragments with sodium borohydride in methanol at 0 °C leads to a mild reduction of the "C" cycle with the formation of corresponding tetrahydroberberine derivatives with moderate to good yields.

The acylation of unsymmetrical N-benzylbispidinols in aromatic solvents without external base led to formation of supramolecular gels, which possess different thickness and stability depending on the substituents in para-positions of benzylic group and nature of acylating agent as well as on the nature of the solvent used. Structural features of the native gels as well as of their dried forms were studied by complementary techniques including FT IR- and ATR-spectroscopy, AFM, TEM, SEM, SAXS. Structures of the key crystalline compounds were established by X-ray diffraction. Analysis of obtained data allowed speculating on the crucial structural and condition factors that governed the gel formation. The most important factors were: (i) absence of base, either external or internal; (ii) presence of HCl; (iii) presence of carbonyl and hydroxyl groups to allow hydrogen bonding; (iv) presence of two (hetero)aromatic rings at both sides of the molecule. The hydrogen bonding involving amide carbonyl, hydroxyl at 9th position and, very probably, ammonium N-H+ and Cl- anion appear to be responsible for the formation of infinite molecular chains required for the first step of gel formation. Subsequent lateral cooperation of molecular chains into fibers occured, presumably, due to the aromatic pi-pi-stacking interactions. sc-CO2 drying of the gels gave rise to aerogels morphology different from that of air dried samples.

Herein, two title compounds, N-Benzoyl-N’-4-cyanophenyl thiourea (I) and N-(4-nitrobenzoyl)-N’-4-cyanophenyl thiourea (II) were synthesized in high yield, via aroyl isocyanate and 4-aminobenzonitrile. The structure of the prepared compounds was characterized by elementary analysis and FT-IR, ¹H, ¹³C NMR spectroscopic methods. Cyclic voltammetric (CV) experiments were performed with glassy carbon electrode. The reduction potential values of different functional group such as nitro, cyano in title compounds were investigated using CV curves.

A gold(I) complex with a triphenylphosphine and a monodentate N,N-dimethyldithiocarbamate ligand was synthesized and characterized by Raman spectroscopy and single crystal X-ray diffraction. DFT calculations (Gaussian 09, PBE1PBE/Lanl2dz) were undertaken for a single complex in the gas-phase. The DFT-optimized structure is in good agreement with the crystal structure and the DFT-calculated Raman spectrum also is in excellent agreement with the experimental spectrum. Assignments of the Raman peaks are based on these DFT calculations. Frontier molecular orbitals were calculated and their nature is discussed.

Nowadays, the identification and characterization of grapevine cultivars resilient to climate and water stress while preserving quality traits is crucial for the wine industry. Therefore, the objective of this work was to characterize according to their aromatic potential 9 white and 6 red minority cultivars recently recovered from Castilla-La Mancha region (Spain), subjected at two different water deficit regimes: rainfed, with subsistence irrigation, and irrigated. For this, the varietal aromatic potential index (IPAv) and the detailed aromatic composition were analyzed by HS-SBSE-GC/MS, in extracts of two different ph. For IPAv values, red varieties did not show a clear trend with respect to irrigation. However, in white minority varieties, higher values were obtained under irrigation conditions. Thus, a clear differentiation of the minority varieties in comparison to the references was observed, primarily attributed to the content of esters and acids, in both white and red varieties. A notable contrast was observed at different pH, indicating a greater extractability of certain compounds like linalool, under more acidic conditions. This suggests that some recovered minority cultivars could be promising for cultivation in semi-arid regions with limited water, contributing to the wine sector sustainability in the future.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on the Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of ER and HCP measurements using data from multiple NDE technologies.

The COVID-19 pandemic has unveiled the critical role that supercomputers play in addressing global health crises. This perspective article explores the transformative impact of supercomputing in pandemic response, highlighting how these powerful machines have transitioned from crisis management tools to essential components of preparedness strategies. In this article, we examine the key contributions of supercomputers in combating the pandemic, including their ability to accelerate scientific research, facilitate data analysis, model complex scenarios, and optimize resource allocation. Furthermore, we delve into the role of supercomputing in strengthening public health infrastructure and preparedness. We analyze the lessons learned from the pandemic and emphasize the need for proactive investment in supercomputing capabilities, data infrastructure, and computational expertise as a crucial element of pandemic preparedness efforts. By harnessing the potential of supercomputers, countries can establish robust computational frameworks that enable real-time monitoring, early detection, and effective response to future outbreaks. Moreover, we address the challenges faced by supercomputing initiatives, including the need for enhanced international collaboration, equitable access to computing resources, and the ethical considerations associated with data privacy and security. We discuss potential strategies to overcome these challenges and foster a global network of interconnected supercomputing centers dedicated to pandemic preparedness and response. Finally, we highlight ongoing research and development efforts aimed at advancing supercomputing technologies, such as exascale computing and quantum computing, and their potential to revolutionize pandemic response. We emphasize the importance of sustained investment in research and development to ensure that supercomputing remains at the forefront of future pandemic preparedness strategies.

This research aimed to improve the interpretation of electrical resistivity (ER) results in concrete bridge decks by utilizing results from multiple nondestructive evaluations (NDE) techniques in machine learning algorithms. To achieve this, a parametric study was first conducted using numerical simulations to investigate the effect of various parameters on ER measurements, such as the degree of saturation, corrosion length, delamination depth, concrete cover, and the moisture condition of delamination. A data set from this study was used to build a machine-learning algorithm based on the Random Forest methodology. This algorithm was then implemented on data collected from a bridge deck in the BEAST® facility. The presented results demonstrate an improvement in the interpretation of ER measurements using data from other NDE technologies.

Marburg virus disease (MVD) is a hemorrhagic fever and cause death up to 88% of people and is the same as Ebola virus, It is transmitted through skin contact or mucous membrane in the eyes, nose or mouth with blood or body fluids like urine, saliva sweat, feces and by object contaminated with body fluids. Despite these facts, yet there is no approved vaccine have been developed for the eradication of Marburg virus infections. Therefore, this study described a multi epitope-based peptide vaccine against Marburg virus viral protein 35, using several immunoinformatics tools combined with molecular docking studies. Utilizing Vaxijen 2.0 server, the V35 protein revealed to be antigenic with a score of 0.4316. Prediction of the T-cell and B-cell epitopes was then conducted. RTFDAFLGV epitope was found to be the most promising one with binding affinity to the highest numbers of MHC I alleles, a positive score in the Class I immunogenicity study and non-allergen. These results were further confirmed by the good interaction of RTFDAFLGV to the groove of HLA-A*02:01 with binding energy of -8.1 kcal/mole. Finally, the vaccine was cloned in silico to ensure its validity and efficiency of expression. To ensure its safety and immunogenic profile, in-vitro and in-vivo bioassays are recommended to confirm these findings.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

With the rapid development of science and technology, many new concepts and terms appear, especially in English. Other languages try to express these concepts with words from their own vocabulary. In the specific case of Arabic, there are many ways to find a counterpart for a particular new concept, such as using an existing word to denote the new concept, derivation, and blending. When these methods fail, the new concepts are simply phonetically transliterated. This has the disadvantage that most of the transliterated terms do not conform to the rules of the Arabic language and lead to a distortion of the language. Some modern linguists call for using the generation strategy to translate the new terms into Arabic by using the unused Arabic roots. Therefore, it is necessary to provide a resource that contains all Arabic roots with a categorization of what is used, what is available for use, and what is rejected according to the phonetic system. This work provides a comprehensive lexicon that contains all possible Arabic triliteral roots, determines the status of each root in terms of usage and acceptability, and provides a mechanism for giving preference to roots when there is more than one root that indicates the desired meaning.

In this study, we introduce a new type curve in 3-dimensional space which called B-lift curve and we obtain the Frenet operators of the B-lift curve. Moreover, we consider the correpondence of Frenet operators between the Blift curve and the natural lift curve. Finally, we investigate the B-lift curve according to the main curve is slant helix or darboux helix.

Objective: It was aimed to investigate the cerebral vascular territories in stroke patients with NVAF as an etiologic factor. Material and Methods: A total of 104 patients who were referred to our hospital between January 2015 and September 2016, who were over 55 years of age, identified or documented as having a standard ECG or Holter ECG record on their medical history, and diagnosed with stroke were included. Our study was designed as a retrospective analysis of prospective data. Detailed history, physical examination and electrocardiography (ECG) evaluations of the patients were performed. Descriptive statistics were used in the detection of findings, and t-test, Pearson-square test and Fisher's exact test were used for differences analysis. Results: 53.8% (N = 56) of the patients were male and 46.2% (N = 48) were female. The mean age was 73.5. MCA was the most common site of vascular involvement in NVAF-dependent strokes. In MCA vascular territory, ischemic infarcts were detected most frequently in the upper and lower divisions. SCA and PCA followed MCA. Approximately 64% of the NVAF-related strokes were anterior circulation infarction (ASE) and 22% were posterior circulation infarct (PSE). There was a significant difference in age and past stroke history factors in favor of ASE (p<0.05). There was no significant difference between ASE and PSE in HT, cardiac history and DM factors (p>0.05). Conclusion: It was emphasized that the area of the vessel that underwent ischemia in the acutely displayed infarcts and the etiological factor for this vessel area could be predicted

Colombia is noteworthy as a biodiversity hotspot, featuring an extraordinary number of en-demic orchids, birds, and butterflies. This exploratory study examines the perceptions of desti-nation image considering the cognitive and affective image in predicting behavioral intentions of ecotourists through symmetric data analysis. Using Partial Least Squares (PLS), the author(s) analyzed 64 survey responses collected of rural areas, including a new 15 statement scale spe-cialized on birdwatching. The findings support the reliability of the model, symmetric analysis presents the higher influence of emotions and affections in increasing intentions of recommen-dation, considering birdwatching as based on personal relationships. Additionally, the cognitive image for the birders despite representing destination attributes or sets of destination resources of a mental picture does not have the same impact on behavioral intentions. Therefore, manag-ers should develop positioning strategies based on the generation of emotions, because bird-watching tourists seek to have more emotional experiences.

Ulcerative colitis (UC) is a chronic inflammatory disease, the incidence of which is increasing worldwide. However, the etiology and pathogenesis of UC remains unclear. The n-butanol extract of pulsatilla decoction (BEPD) of the traditional Chinese medicine herbal formula has been shown to be effective in treating UC. We aimed to explore the molecular mechanism underlying the effects of BEPD on UC, in particular its effects on neutrophil extracellular trap (NET) formation by neutrophils. High-performance liquid chromatography was used to determine the principal compounds of BEPD. UC was induced in mice using dextran sodium sulfate, and mice were treated with 20, 40, or 80 mg/kg BEPD daily for seven days. Colonic inflammation was determined by assessing the disease activity index, histopathology, colonic mucosal damage index, colonic mucosal permeability, and pro- and anti-inflammatory cytokine levels. The infiltration and activation status of neutrophils in the colon were determined by analyzing the levels of chemokine (C-X-C motif) ligand (CXCL)1 and CXCL2, reactive oxygen species, Ly6G, and numerous NET proteins. Our results showed that BEPD improved the disease activity index, histopathology, and colonic mucosal damage index scores of mice with UC, and restored colonic mucosal permeability compared with untreated mice. The expression levels of the pro-inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor-α in colon tissues were significantly decreased, while the expression levels of anti-inflammatory cytokines in colon tissues were significantly increased, exceeding those of control mice. In addition, BEPD reduce the expression of the neutrophil chemokines CXCL1 and CXCL2 in the colon tissue of mice with UC, reduced neutrophil infiltration, reduced reactive oxygen species levels, and significantly reduced the expression of NET proteins. BEPD also significantly reduced NET formation. The results of this study suggest that BEPD exerts therapeutic effects in a murine model of UC by inhibiting neutrophil infiltration and activation in the colon, as well as by inhibiting the expression of key proteins involved in NET formation and reducing NET formation, thereby alleviating local tissue damage and disease manifestations.

The process of developing therapies to treat rare diseases is fraught with financial, regulatory, and logistical challenges that have limited our ability to build effective treatments. Recently, a novel type of therapy called antisense therapy has shown immense potential for the treatment of rare diseases, particularly through single-patient N-of-1 trials. Several N-of-1 antisense therapies have been developed recently for rare diseases, including the landmark study of milasen. In response to the success of N-of-1 antisense therapy, the Food and Drug Administration (FDA) has developed unique guidelines specifically for the development of antisense therapy to treat N-of-1 rare diseases. This policy change establishes a strong foundation for future therapy development, and addresses some of the major limitations that previously hindered the development of therapies for rare diseases.

Since the COVID-19 caused by SARS-CoV-2 break out in Wuhan China from Dec. 2019, it has spread to hundreds of countries up to now. Scientists from all over the world have paid tremendous efforts to research and try to control the disease. Previous studies suggested that some of the wild animals could be intermediate hosts between humans and origination of SARS-CoV-2, and some companion animals of humans can be infected by SARS-CoV-2, which raised our curiosity about cross-infection of SARS-CoV-2 between animals and humans. Thus, we select some kinds of animals that might have contact with humans to estimate the susceptibility to SARS-CoV-2 in different animals by evolutionary analysis of their receptors for SARS-CoV-2. The results show that some companion animals of the Felidae family like the cat has a higher infection possibility while the species of the Rodent family like the rat and mouse having close contact with humans show an opposite result, which consist with recent animal experiments and researches. These should raise concerns about cross-infection between human and companion animals or animals having close contact with humans which might turn animals into depositaries of the coronavirus even after control of SARS-CoV-2 spreading and cause second or more waves of infections after social reopening. Another side of our results stands by the opinion that bioinformatic analysis can be consistent with experiments in some respects so that we can prevent unnecessary sacrifice of laboratory animals in future experiments.

:Peat substrate is made from peat from drained peatlands, which is a limited resource. A realistic estimate is that 50% of the world’s wetlands have been lost. Peat is used in horticulture, especially for the cultivation of vegetables in greenhouses. The consequences of peatland exploitation are an in-crease in the greenhouse effect and a decrease in carbon stocks. Wood fiber can be used as an al-ternative to peat. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the growing container. This study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) variety “Dirigent H” developed in the Netherlands, were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) con-ventional fertilization (CF); (2) N13; (3) N23; (4) N30. The experiment was carried out in three repli-cations. As the amount of wood fiber increased, the humidity and pH of the growing medium in-creased. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in 50/50 and 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat sub-strate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

: Greenhouse plants are usually grown in containers filled with growing media. Peat is the main component of the growing media used in greenhouses. However, peat substrate is made from peat from drained peatlands, which is a limited resource. Wood fiber can be an alternative to use as a growing media for controlled-climate crops. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the vegetative container. Therefore, this study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) conventional fertilization (CF); (2) N13; (3) N23; (4) N30. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in WF/PS 50/50 and WF/PS 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat substrate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

Bats are natural hosts for a wide variety of viruses and could therefore be the reservoir, source and spillover for several mammalian viruses, including adenoviruses. We examined faecal samples from 12 bats (five species of the family Vespertilionidae) from central Russia (Moscow Region) and found that two of them (16%) were positive for mastadenoviruses. One of the identified viruses was isolated from faeces of Nyctalis noctule and named BatAdV/MOW15-Nn19. The genome of the BatAdV/MOW15-Nn19 was 37,915 bp in length. Comparative studies have shown significant divergence of the nucleotide sequence of the BatAdV/MOW15-Nn19 genome from European mastadenoviruses, the highest genome sequence similarity was to isolate WA3301 from an Australian bat. Phylogenetic analysis, as well as a comparative analysis of the protein coding genes to homologous available from public database, showed evidence of novel species within Mastadenovirus genus (preliminary named «K»). Analysis of the short part of the DNA polymerase gene of BatAdV/MOW15-Nn19 reveals few NCBI records from Europe with high identity to the new virus, i.e. mastadenoviruses related to the new species are circulating in European bats. The partial genome of another mastadenovirus from Pipistrellus nathusii was identified, it represented bat adenovirus species B, which is widely distributed in European Vespertilionidae bats. New data on the genetic diversity of bat adenoviruses may help to better understand how they evolved in mammals and spread across Europe.

In large-scale parallel computing and communication systems, an interconnect network structure is usually modeled as a graph, in which vertices and edges correspond to processors and communication links, respectively. In a graph, the vertices and edges are likely to fail, so we must think about the fault tolerance of a graph. Connectivity is an important parameter in the study of faulty tolerance for a graph. In this paper, we study a special class of connectivity: $m$-component connectivity, this is a natural generalization of the classical connectivity of graphs defined in terms of the minimum vertex-cut. Let $F$ is a vertex set of $G$ $(i.e, F\subseteq V(G))$, if the following conditions are satisfied, we say $F$ is a $m$-component cut: $(1)$ $G-F$ is disconnected; $(2)$ the number of components in $G-F$ is greater than or equal to $m$. In another word, the $m$-component connectivity $c\kappa_{m}(G)$ is defined as $min\{|F|~|~F\subseteq V(G)$ and $F$ is a $m$-component cut$\}$. Determining $m$-component connectivity is still unsolved in most interconnection networks even for small $m'$s. Leaf-sort graph is a special Cayley graph, it has many special properties that are different from other Cayley graphs. So we need to pay attention to some of it's special properties when we study it. In this paper, we can get the values: $c\kappa_{3}(CF_{n})=3n-6$ $(n$ is odd$)$ and $c\kappa_{3}(CF_{n})=3n-7$ $(n$ is even$)$ for $n\geq3$; $c\kappa_{4}(CF_{n})=\frac{9n-21}{2}$ $(n$ is odd$)$ and $c\kappa_{4}(CF_{n})=\frac{9n-24}{2}$ $(n$ is even$)$ for $n\geq4$; $c\kappa_{5}(CF_{n})=6n-16$ $(n$ is odd$)$ and $c\kappa_{5}(CF_{n})=6n-18$ $(n$ is even$)$ for $n\geq5$.

Mercury is classified as one of the world’s most toxic and dangerous pollutants. It tends to bio-accumulate and biomagnify within the trophic chain and is persistent. Various approaches are available to remediate Hg-affected sites, including phytoremediation, which includes the use of plants to clean up contaminated environments. Phytoremediation of mercury contamination is at-tracting increasing attention because of its advantages: it is environmentally friendly, inexpensive, simple, and can improve soil fertility. In this report, VOSviewer, and Bibliometrix software were used to analyze 457 and 697 documents published from 2000 to 2023, retrieved from the data-bases WoS and Scopus, respectively. China, India, the United States, and Spain are the top four most productive countries. The largest topic area was environmental sciences, and the Chinese Academy of Sciences was the organization that contributed the most to the overall number of pub-lications. The keywords with the highest frequency, excluding phytoremediation and mercury in WoS, were heavy metals, accumulation, cadmium, soils, and phytoextraction. In Scopus, the most frequent keywords were bioremediation, heavy metals, soil pollution, bioaccumulation, biodeg-radation, and environmental. From the above analysis, we concluded that future research should focus on 1) finding native plants, 2) increasing remediation ability through assisted phytoremedi-ation, 3) studies of molecular mechanisms in plants with phytoremediation potential, and 4) ge-netic engineering applications. This study provides insight into trending themes and serves as a reference for future research.

Reservoir computing is a machine learning method that uses the response of a dynamical system to a certain input in order to solve a task. As the training scheme only involves optimising the weights of the responses of the dynamical system, this method is particularly suited for hardware implementation. Furthermore, the inherent memory of dynamical systems which are suitable for use as reservoirs mean that this method has the potential to perform well on time series prediction tasks, as well as other tasks with time dependence. However, reservoir computing still requires extensive task dependent parameter optimisation in order to achieve good performance. We demonstrate that by including a time-delayed version of the input for various time series prediction tasks, good performance can be achieved with an unoptimised reservoir. Furthermore, we show that by including the appropriate time-delayed input, one unaltered reservoir can perform well on six different time series prediction tasks at a very low computational expense. Our approach is of particular relevance to hardware implemented reservoirs, as one does not necessarily have access to pertinent optimisation parameters in physical systems but the inclusion of an additional input is generally possible.

In this paper, we introduce ResNetMF, a groundbreaking approach that harnesses the power of residual network matrix factorization to revolutionize recommendation systems. ResNetMF integrates residual networks, renowned for their ability to capture intricate patterns and features, with matrix factorization techniques that excel in modelling user-item interactions. This fusion presents a novel solution that surpasses the limitations of traditional recommendation systems. Through comprehensive experimentation and evaluation of diverse datasets, ResNetMF demonstrates remarkable enhancements in recommendation accuracy and efficiency. By effectively capturing both linear and nonlinear relationships in user-item interactions, ResNetMF provides superior recommendation quality. The outcomes from experiments unequivocally highlight the superiority of ResNetMF over existing state-of-the-art recommendation approaches, thereby validating its innovative nature and underscoring its potential to shape the future of recommendation systems. Through the integration of the deep residual network, ResNetMF approach facilitates the training of neural networks, enabling them to explore the underlying data layers more comprehensively. Extensive experimentation and evaluation across various datasets provide compelling evidence for the superiority of ResNetMF. Moreover, the proposed method utilized natural language processing (NLP) techniques for targeted information dissemination in recommendation systems, emphasizing the importance of personalized and relevant recommendations for user satisfaction and engagement.

Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

We have carried out a systematic review of the scientific literature published on PM and, more specifically, on its presence in fish and seafood of interest to the population from Mediterranean area. Given its preference and wide acceptability in the scientific community, we followed the PRISMA. The potential functional and clinical toxicity in humans due to MP in fish must be considered by the chemical composition of the microplastics the presence of PM and its additives, associated contaminants and pathogens in fish and shellfish, as well as the possible effects on human health, requires improving legislation on evaluation and providing a basis for consumer protection.

The existences of the N→C dative bonds in the complexes between N-containing molecules and fullerenes have been verified both theoretically and experimentally. However, finding stable N→C dative bonds is still a highly challenging task. In this work, we investigated computationally the N→C dative bonds in the complexes formed by fullerene C60 with 1,2,5-chalcogenadiazoles, 2,1,3-benzochalcogenadiazoles and 1,2,4,5-chalcogenatriazoles, respectively. It was found that the N→C dative bonds are formed along with the formation of the N–Ch···C (Ch = S, Se, Te) chalcogen bonds. In the gas phase, from S-containing complexes through Se-containing complexes to Te-containing complexes, the intrinsic interaction energies become more and more negative, which indicates that the N–Ch···C chalcogen bonds can facilitate the formation of the N→C dative bonds. The intrinsic interaction energies are compensated by the large deformation energy of fullerene C60. The total interaction energies of Te-containing complexes are negative, while both of the total interaction energies of S-containing complexes and Se-containing complexes are positive. This means that the N→C dative bonds in the Te-containing complexes are more easily observed in experiments in comparison with those in the S-containing complexes and Se-containing complexes. This study provides a new theoretical perspective on the experimental observation of the N→C dative bonds in the complexes involving fullerenes. Further, the formation of stable N→C dative bonds in the complexes involving fullerenes can significantly change the properties of fullerenes, which will greatly simulate and expand the application range of fullerenes.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

Improving photobioreactor performance for microalgae cultivation has attracted many researchers over the past years. One of the primary challenges associated with existing photobioreactors is the light penetration. An effective photobioreactor design should maximize light penetration, ensuring uniform illumination throughout the reactor. This study aims to assess the impact of light intensity on microalgal growth from the perspective of energy efficiency and productivity in two photobioreactors. A novel cactus-like and a cylindrical photobioreactor were designed and fabricated using 3D printing technology. These two photobioreactors were used to cultivate two strains of microalgae. The novel photobioreactor achieved a maximum biomass productivity of 0.99 g/L/d and a maximum energy efficiency of 0.3139 g/d/kWh. The cylindrical photobioreactor reached a maximum biomass productivity of 0.74 g/L/d and 0.2199 g/d/kWh of energy efficiency. The increase in biomass productivity can be linked to enhancements in the photobioreactor's surface-to-volume ratio and better light utilization.

Scientists who hope to obtain a faculty position at a primarily undergraduate institution (PUI) need a distinct skill set and outlook on their future teaching and research career. To obtain a position at a PUI, candidates should 1) design a strategy for obtaining a faculty position that suits each individual’s career goals and aspirations, 2) prepare for the application process, on-campus interview, and contract negotiations, and 3) plan a strategy for the probationary period leading up to tenure and promotion. Given the different types of PUIs, candidates need to consider whether they seek a position that consists of all or mostly all teaching, or both teaching and research. Candidates should educate themselves on the expectations at PUI’s, including current thought, practice, and aspirations for science pedagogy, and gain teaching experience prior to seeking a suitable position. If the candidate’s goal is a position with both teaching and research, it is important to discuss with the current research mentor what projects the candidate can take with them to their new position. The candidate should also consider what types of projects will be successful with undergraduate student researchers in a PUI research environment Importantly, candidates should clearly demonstrate a commitment to diversity and inclusion in their teaching, research, and outreach, and application materials should demonstrate this. On interviews, candidates should be knowledgeable about the mission, values, and resources of the institution and how the candidate will contribute to that mission. Once hired, new faculty should discuss a formal or informal mentoring plan during the probationary period that includes peer evaluations on a regular basis, and maintain communication with the department chair or designated mentor regarding teaching, research, and service activities.

Pigs are a social species and they stablish hierarchies for a better use of resources and to reduce conflicts. However, in pig production, the opportunities for growing can differ in dominant and subordinate animals. In the present study a system was tested to perform a Dominance versus Subordinate test in growing pigs to investigate how the hierarchy affects feeding behaviour, growth and gut microbiota assessed in faeces. 64 animals housed in eight different pens were used, with four castrated males and four females in each one, weighing 18kg at arrival and maintained during the whole growing period, until 140 kg. Three stool samplings were obtained from the animals directly from the anus to avoid contamination of the faeces on 58, 100 and 133 days after the start of the study to investigate the microbiota composition. The dominant animals had higher gains during the growing period that the subordinate. In addition, they were performing more visits to the feeder throughout the day. Differential abundance patterns were observed in five bacterial genera, Oliverpabstia, Peptococcus, and Faecalbacterium being more abundant in dominant animals and Holdemanella and Acetitomaculum being overrepresented in subordinate ones. This microbial biomarker accurately classified dominant versus subordinate groups of samples with an AUC of 0.92.

The research aimed to identify the effect of high-intensity compound exercises for physical performance skills using the means of hypoxia training in some biochemical variables in the blood of fencing players. The researcher used the experimental approach and determined the community, namely the players of Maysan governorate teams in fencing and for the three weapons (fencing sword, shish, Arab sword) the category of applicants over the age of (20) years, and by (4) players for each weapon, which reached the number of society (12) players, and some procedures were adopted to achieve the objectives of the study. The study came out the results of the study recorded a significant impact on the high level of measurement of blood biochemical variables (EPOs, FERSs, Hb, Hct) and improved by high-intensity compound exercises using the training hypoxic mask among members of the research community.

Energy savings have been a major driver for improving building airtightness in the last period. Air infiltration has an important influence on energy efficiency and significantly influences the indoor air quality and pollutant distribution in residential buildings. Pressure difference lead to air permeability through the building envelope via cracks and un-controlled air leaks, which increase not only energy consumption, also cause noise from the outside and entering particles harmful to human health. Therefore, the issue of airtightness of the building envelope has been included in the standards and regulations. Building airtightness is influenced by various design parameters such as window/wall ratio, type of joinery, size of usage area, wall material and the insulation application also the quality of workmanship. In this study, the airtightness performance of 43 different residentials in Balıkesir was deter-mined by the BlowerDoor test measurement and in the context of airtightness the architectural design parameters impact was investigated. The air exchange rate (n50) values of 43 residences were obtained between 1.94 - 49.02 h-1 and compared with the existing standards. In addition, “usage area” was determined as the most effective parameter, followed by the size of the usage area, the transparency rate of the facades, the wall material type and the insulation status.

In this work, PMMA(Poly methyl methacrylate) microfluidic system was used as a micro-reactor for urea hydrolysis by urease enzyme with use conductivity principle and utilize sound level meter(SLM) App in smartphone as a novel detector by considering the peak height in the App as an indicate for urea concentration. the advantage of use small volume and how the reaction carried on in the microfluidic system with simple and low cost are discussed, and the results were analyzed and statically determine. The linearity, detection limit (3×noise )and Correlation Coefficient, 62.5-500 ppm, 31.25 ppm and 0.992 respectively also, recovery studied were between(98.5-100.13%).

Abstract: In this study the essential oils of Salvia officinalis growing in Sudan, were obtained by hydrodistillation and analyzed by Gas chromatography mass spectrometer, forty tow compounds were identified. The essential oil composition of S.officinalis found that it had many important compounds. The detected main compounds were oxygenated monoterpenes followed monohydrocarbone, squiterpenes and other compounds. The main essential oil constituents were α-terpineol (33.07%), camphor (11.57%), α-pinene (8.96%) camphene (5.09%) β-cymen (5.40 %) caryphyllene (3.76%) β-myrcene (3.65%) β-menth1-en-b-ol (3.45%) bomeol (3.38%) β-pinene (2.74%) Epiglobulol (2.59%) 1,8 Cineol (2.24%) and trans-β- terpinyl butanone(2.00% ).