In this work, we try to find a way to describe the physical law of micro-world under the frame of a space-time theory. By introducing the scalar fields $\mathcal{D}\left( x\right)$ and $\zeta\left( x\right) $, we rewrite the action of conventional field theory and the Lagrangian describing the motion of the particle, where a modified space-time relation is obtained. To test the correctness of this attempt, we demonstrate the Klein-Gordon equation by the Hamilton-Jacobi method in four dimensional form and present a time delay for the ground state of hydrogen atom.

Cadherins are a group of membrane proteins responsible for cell adhesion. They are crucial for cell sorting and recognition during the morphogenesis, but also play many other roles such as assuring tissue integrity and resistance to stretching, mechanotransduction, cell signaling, regulation of cell proliferation, apoptosis, survival, carcinogenesis, etc. Within the cadherin superfamily, the E- and N-cadherin have been especially well studied. They are involved in many aspects of sexual development and reproduction, such as germline development and gametogenesis, gonad development and functioning, and fertilization. E-cadherin is expressed in the primordial germ cells, (PGCs) and also participates in PGC migration to the developing gonads where they become enclosed by the N-cadherin-expressing somatic cells. The differential expression of cadherins is also responsible for the establishment of the testis or ovary structure. In the adult testes, the N-cadherin is responsible for the integrity of the seminiferous epithelium, regulation of sperm production, and the establishment of the blood-testis barrier. Sex hormones regulate the expression and turnover of N-cadherin influencing the course of spermatogenesis. In the adult ovaries, E- and N-cadherin assure the integrity of ovarian follicles and the formation of corpora lutea. Cadherins are expressed in the mature gametes, and facilitate the capacitation of sperm in the female reproductive tract, and gamete contact during fertilization. The germ cells and accompanying somatic cells express a series of different cadherins, however, their role in gonads and reproduction is still unknown. In this review, we show what is known and unknown about the role of cadherins in the germline and gonad development, and suggest the topics for future research.

Nowadays, in order to improve asphalt pavement performance, durability and reduce environmental pollution caused by asphalt binder, many researchers are studying to modify asphalt concrete (AC) and find alternative paving materials to extend service life of asphalt pavement. One of the successful materials used in a modification of AC are fibers. Different types of fibers have been reinforced in AC mixture and improvements have been observed. This research studies the performance of glass wool fiber reinforced in a dense-graded asphalt mixture. Generally, glass fibers are known to have excellent mechanical properties such as high tensile modulus, 100% elastic recovery and a very high tolerance to heat. The glass wool fibers are commonly used as a thermal insulation material. In this research to evaluate the performance of glass wool fiber in AC, laboratory tests Marshall mix design test, Indirect tensile strength (IDT), Tensile strength ratio (TSR) and Kim test were conducted to determine a proper mix design, tensile properties, moisture susceptibility, rutting and fatigue behaviors. Results show that addition of glass wool fibers does affect the properties of AC mixture. The use of glass wool fibers showed a positive consistence results, in which it improved the moisture susceptibility and rutting resistance of the AC. Also result showed addition of fiber increased tensile strength and toughness which indicates that fibers have a potential to resist distresses that occur on a surface of the road as a result of heavy traffic loading. The overall results showed that addition of glass wool fiber in AC mixture is beneficial in improving properties of AC pavements.

Roundabouts need capacity and safety improvements compatible with manual-driven, not only with autonomous vehicles. The signaling and control of roundabouts must evolve and incorporate current technologies. For that, we approach roundabouts as synchronous switches of vehicles. This paper describes Synchronous Roundabouts with Rotating Priorities, a roundabout control system based on vehicle platoons arriving at the roundabout at speed identical to the roundabout and within the time slot assigned to their entry, avoiding conflicts and stops, thus increasing roundabout capacity and safety. Signaling is visual for human drivers and also wireless for connected and autonomous vehicles. We evaluate analytically and with simulations roundabouts of different radius for several values of the average distance between vehicles. Average delays are 28,7 % lower, with negligible dispersion. The capacity improvements depend on design parameters: in our set is moderate for small roundabouts but goes up to 70-100 % for short distances and medium and large roundabouts.

Herein, we present a combination of experimental and computational study on the mitochondrial F0F1-ATPase nanotoxicity inhibition induced by single-walled carbon nanotubes (SWCNT-pristine, SWCNT-COOH). To this end, the in vitro inhibition responses in submitochondrial particles (SMP) as F0F1-ATPase enzyme were strongly dependent on the concentration assay (from 3 to 5 µg/ml) for both types of carbon nanotubes. Besides, both SWCNTs show an interaction inhibition pattern like the oligomycin A (the specific mitochondria F0F1-ATPase inhibitor). Furthermore, the best crystallography binding pose obtained for the docking complexes based on the free energy of binding (FEB), fit well with the previous in vitro evidences from the thermodynamics point of view. Following an affinity order as: FEB (oligomycin A/F0-ATPase complex) = -9.8 kcal/mol > FEB (SWCNT-COOH/F0-ATPase complex) = - 6.8 kcal/mol ~ FEB (SWCNT-pristine complex) = -5.9 kcal/mol. With predominance of van der Waals hydrophobic nanointeractions with key F0-ATPase binding site residues (Phe 55 and Phe 64). By the other hand, results on elastic network models, and fractal-surface analysis suggest that SWCNTs induce significant perturbations by triggering abnormal allosteric responses and signals propagation in the inter-residue network which could affect the substrate recognition ligand geometrical specificity of the F0F1-ATPase enzyme in order (SWCNT-pristine > SWCNT-COOH). Besides, the performed Nano-QSTR models for both SWCNTs show that this method may be used for the prediction of the nanotoxicity induced by SWCNT. Overall, the obtained results may open new avenues toward to the better understanding and prediction of new nanotoxicity mechanisms, rational drug-design based nanotechnology, and potential biomedical application in precision nanomedicine.

The Corona Virus (COVID-19) pandemic situation has posed significant effect on tourism industry. Tourism destinations have embraced emergency health care measures and restrictions imposed on human movement around the world. Beaches and resorts are empty, peoples’ movements are stopped and travelling between territories is strictly controlled. The COVID-19 lockdown around the world has imposed negative impact on the livelihood of people and world economy as well. The present study attempts to find out the scopes for sustainable tourism development in near future from the consequences of social, economic, and environment in COVID-19 pandemic situation.

Keywords: Geobacillus thermocatenolatus; lipases; ethanolysis; ionic liquids; kinetic resolution; mandelic acid.

A delayed crosslinked polymer gel was developed for indepth water control in mature oilfields. The thermal gelation behavior of nonionic polyacrylamide (NPAM) and PEI was investigated, and sodium citrate (NaCit) was selected as a new retarder to prolong the gelation time. The gelation performance of NPAM/PEI gel system can be adjusted by the variation of NPAM or PEI concentration, and a quadratic model was developed by statistical analysis, which predict the gelation time of NPAM/PEI gel system. The obtained model showed high significance and good reliability as suggested by the F-ratio of 175.16 and high adjusted R-square value (0.9732). The decrease of the initial pH value of gelling solution leads to the weaker gel viscosity and longer gelation time due to the protonation of amine groups on the PEI chains. Increasing temperature resulted in higher gel viscosity but shorter gelation time. The addition of NaCit showed a good delayed gelation effect on the NPAM/PEI gel system, and the gel system in the presence of NaCit exhibited a good compatibility with injected and formation water. A dense three-dimensional structure was observed in matured NPAM/PEI/NaCit gel, and it could keep stable below 150℃. The gel system could effectively reduce the permeability (>95%) and restricted the flow of water after matured in natural cores.

Mortarless refractory masonry structures are widely used in the steel industry for the linings of many high-temperature industrial applications including steel ladle. The design and the optimization of these components require accurate numerical models that consider the presence of joints as well as joints closure and opening due to cyclic heating and cooling. The present work reports on the formulation, numerical implementation, validation, and application of homogenized numerical models for simulation of refractory masonry structures with dry joints. The validated constitutive model has been used to simulate a steel ladle and to analyze its transient thermomechanical behavior during a typical thermal cycle of steel ladle. 3D solution domain, enhanced thermal and mechanical boundary conditions have been used. Parametric studies to investigate the impact of joints thickness on the thermomechanical response of the ladle have been carried out. The results clearly demonstrate that the thermomechanical behavior of mortarless masonry is orthotropic nonlinear due to gradual closure and reopening of joints with the increase and decrease of temperature. Also, resulting thermal stresses increase with the increase of temperature and decrease with the increase of joints thickness.

Trophoblasts are the first cell-type to be specified during embryogenesis, and they are essential for placental morphogenesis and function. Trophoblast stem (TS) cells are the progenitor cells for all trophoblast lineages; control of TS cell differentiation into distinct trophoblast subtypes is not well understood. Mice lacking the transcription factor OVO-like 2 (OVOL2) fail to produce a functioning placenta, and die around embryonic day 10.5, suggesting that OVOL2 may be critical for trophoblast development. Therefore, our objective was to determine the role of OVOL2 in mouse TS cell fate. We found that OVOL2 was highly expressed in mouse placenta and differentiating TS cells. Placentas and TS cells lacking OVOL2 showed poor trophoblast differentiation potential, including increased expression of stem-state associated genes (Eomes, Esrrb, Id2) and decreased levels of differentiation-associated transcripts (Gcm1, Tpbpa, Prl3b1, Syna). Ectopic OVOL2 expression in TS cells elicited precocious differentiation. OVOL2 bound proximate to the gene encoding inhibitor of differentiation 2 (ID2), a dominant negative helix-loop-helix protein, and directly repressed its activity. Overexpression of ID2 was sufficient to reinforce the TS cell stem state. Our findings reveal a critical role of OVOL2 as a regulator of TS cell differentiation and placental development, in-part by coordinating repression of ID2.

Copper-based nanoparticles were synthesized using the glycine–nitrate process (GNP) by using copper nitrate trihydrate [Cu(NO₃)₂‧3H₂O] as the main starting material and glycine [C₂H₅NO₂] as the complexing and incendiary agent. The as-prepared powders were characterized through X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy, and scanning electron microscopy. Using Cu(NO₃)₂.3H₂O as the oxidizer (N) and glycine as fuel (G), we obtained CuO, mixed-valence copper oxides (CuO + Cu₂O, G/N = 0.3–0.5), and metallic Cu (G/N = 0.7). The XRD and BET results indicated that increasing the glycine concentration (G/N = 0.7) and reducing particle surface area increased the yield of metallic Cu. The effects of varying reaction parameters such as catalyst activity, catalyst dose, and H₂O₂ concentration on nonylphenol-9-polyethoxylate (NP9EO) degradation were assessed. With a copper‐based catalyst in a heterogeneous system, the NP9EO and total organic carbon removal efficiencies were 83.1% and 70.6%, respectively, under optimum operating conditions (pH, 6.0; catalyst dose, 0.3 g/L; H₂O₂ concentration, 0.05 mM). The results suggested that removal efficiency increased with an increase in H₂O₂ concentration but decreased when the H₂O₂ concentration exceeded 0.0.5 mM. Furthermore, the trend of photocatalytic activity was as follows: G/N = 0.5 > G/N = 0.7 > G/N = 0.3. The G/N = 0.5 catalysts showed the highest photocatalytic activity and resulted in 94.6% NP9EO degradation in 600 min.

Synthetic polymer-based gradient foams have considered as promising category of functionally graded materials with unique properties. In this study, the carbon dioxide (CO₂) foaming technology has used for PET-PEN (Polyethylene Terephthalate - Polyethylene Naphthalate) copolymer towards porous functional materials with thermal insulation with reasonable mechanical strength. Through scanning electron microscope based morphological characterization, a potential to fabricate gradient foam structures with micro-pores has identified. It has shown that variation of post-foaming temperature can tune the pore size distribution although the very high post-foaming temperature tends to cause structural instability. Thermal measurement data set the limits of operation, confirmed by simultaneous differential scanning calorimeter and thermo-gravimetric analysis. Mechanical stress and thermal conductivity also has measured to find rationale of thermal insulation with reasonable mechanical strength and to elucidate the actual 3D grid foam of copolymer.

The rates of production of secondary metabolites obtained by employing conventional plant breeding may be low for practical purposes. Thus, innovative approaches for increasing their rates of production are being developed. Here, we propose the use of elicited suspension plant cultured cells (PSCC) with cyclodextrins (CDs) as an alternative method for the production of bioactive compounds from Bryophyllum species. For the purpose, we analyzed the effects of methyl--cyclodextrin and 2-hydroxypropyl--cyclodextrin on cell culture growth and on the intra- and extracellular production of phenols and flavonoids. Results clearly show that CDs enhance the biosynthesis of polyphenols by PSCC favoring their accumulation outside the cells. CDs shift the homeostatic equilibrium by complexing extracellular phenolics, causing stress in cells that respond by increasing the production of intracellular phenolics. We also analyzed the radical scavenging activity of the culture medium extracts against DPPH• radical, which increased with respect to the control samples (no added CDs). Our results suggest that both the increase in the production of polyphenols and their radical scavenging activity are a consequence of their inclusion in the CD cavities. Overall, based on our findings, CDs can be employed as hosts for increasing the production of polyphenols from Bryophyllum species.

This study aimed to examine the vitamin D status of professional volleyball athletes and to determine its correlation with shoulder muscle strength. We finally included 52 healthy male professional volleyball players (23.2 ± 4.5 years), who were categorized by vitamin D status (<20 ng/mL: deficiency, 20-30 ng/mL: insufficiency, and >30 ng/mL: sufficiency). We examined the strength of the internal rotator (IR) and external rotator (ER) muscles of the shoulder by using isokinetic dynamometer. Fourteen players (26.9%) had vitamin D deficiency, 24 players (46.2%) were vitamin D insufficient, and 14 players (26.9%) were vitamin D sufficient. There was no significant correlation between the vitamin D level and shoulder muscle strength at 60°/s (IR, r = 0.159, p = 0.26; ER, r = 0.245, p = 0.08), and at 180°/s (IR, r = - 0.093, p = 0.51; ER, r = - 0.037, p = 0.79). Moreover, the isokinetic shoulder strengths were not significantly different across the three groups in all settings. In conclusion, vitamin D insufficiency was common in elite volleyball players. Though not being associated with isokinetic muscle weakness, vitamin D should be regularly monitored and supplemented in young elite athletes, considering its importance on musculoskeletal health.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer, and is the third leading cause of cancer-related deaths each year. It involves a multi-step progression and is strongly associated with chronic inflammation induced by the intake of environmental toxins and/or viral infections (i.e., hepatitis B and C viruses). Although several genetic dysregulations are considered to be involved in disease progression, the detailed regulatory mechanisms are not well defined. Homeobox (Hox) genes that encode transcription factors with homeodomains control cell growth, differentiation, and morphogenesis in embryonic development. Recently, more aberrant expressions of Hox genes were found in a wide variety of human cancer, including HCC. In this review, we summarize the currently available evidence related to the role of Hox genes in the development of HCC. The objective is to determine the roles of this conserved transcription factor family and its potential use as a therapeutic target in future investigations.

Suppressors of cytokine signaling (SOCS) influence cytokine and growth factor signaling by negatively regulating the JAK-STAT pathway. This maintains homeostasis during host immune response. However, functional characterization of SOCS family members in invertebrates is limited. In this study, we discovered the Type-I subfamily of the SOCS genes in the mealworm beetle, T. molitor. The full-length ORFs of TmSOCS5, TmSOCS6, and TmSOCS7 consisted of 1,389, 897 and 1,458 nucleotides, encoding polypeptides of 462, 297 and 485 amino acids, respectively, The C-terminal region of TmSOCS was highly conserved in the SH2 and SOCS box domains. Phylogenetic analysis revealed that the three SOCS genes clustered within the same sub-family and the highest amino acid identity was with the Tribolium castaneum SOCS genes (TcSOCS). While the expression of TmSOCS5 and TmSOCS6 was low in larval, pupal, and adult stages of the insect, TmSOCS7 showed higher expression. The expression of TmSOCS5 and TmSOCS6 was higher in larval hemocytes and adult ovary. The microbes expressed the three TmSOCS genes to varying degrees. C. albicans elicited the strongest response in the host with highest 15-fold expression in TmSOCS7 3 h post-inoculation. Collectively, these data suggest that the Type I TmSOCS could play a role in eliciting host immunity.

Auxin and ethylene pathways cooperatively regulate a variety of developmental processes in plants. Growth responses to ethylene are largely dependent on auxin, the key regulator of plant morphogenesis. Auxin, in turn, is capable of inducing ethylene biosynthesis and signaling making the interaction of these hormones reciprocal. Recent studies discovered a bunch of molecular events underlying auxin-ethylene crosstalk. In this review, we summarize the results of fine-scale and large-scale experiments on interaction of auxin and ethylene pathways in Arabidopsis. We integrate the knowledge on the molecular crosstalk events, their tissue specificity and associated phenotypic responses to decipher the crosstalk mechanisms at a systems level. We also discuss the prospects of applying systems biology approaches to study the mechanisms of crosstalk between plant hormones.

Additive manufacturing (AM) provides customization of the microstructure and mechanical properties of components. Selective laser melting (SLM) is the commonly used technique for processing high strength Aluminum alloys. Selection of SLM process parameters could control the microstructure of fabricated parts and their mechanical properties. However, process parameter limits and defects inside the as-built parts present obstacles to customized part production. This study is the second part of a comprehensive work that investigates the influence of SLM process parameters on the quality of as-built Al6061 and AlSi10Mg parts. The microstructure of both materials was characterized for different parts processed over a wide range of SLM process parameters. The optimized SLM parameters were investigated to eliminate the internal microstructure defects. Mechanical properties of the parts were illustrated by regression models generated with design of experiment (DOE) analysis. The results reported in this study were compared to previous studies, illustrating how the process parameters and powder characteristics could affect the quality of produced parts.

Additive manufacturing (AM) of high strength Al alloys promises to enhance the performance of critical components related to various aerospace and automotive applications. The key advantage of AM is its ability to generate lightweight, robust, and complex shapes. However, the characteristics of the as-built parts may represent an obstacle to satisfy the part quality requirements. The current study investigates the influence of selective laser melting (SLM) process parameters on the quality of parts fabricated from different Al alloys. A design of experiment (DOE) is used to analyze relative density, porosity, surface roughness, and dimensional accuracy according to the interaction effect between the SLM process parameters. The results show a range of energy densities and SLM process parameters for the AlSi10Mg and Al6061 alloys needed to achieve “optimum” values for each performance characteristic. A process map is developed for each material by combining the optimized range of SLM process parameters for each characteristic to ensure good quality of the as-built parts. The second part of this study investigates the effect of SLM process parameters on the microstructure and mechanical properties of the same Al alloys. This comprehensive study is also aimed at reducing the amount of post-processing needed.

Marine algae have been considered as abundant source of bioactive compounds with cosmeceutical potential. Recently, a great deal of interest has focused on the health-promoting effects of marine bioactive compounds. Carbohydrate is a major and abundant constitute of marine algae that have been utilized in cosmetic formulations, such as moisturizing and thickening agents. In addition, marine carbohydrates have been suggested as promising bioactive biomaterials for various skin beneficial properties, such as anti-oxidant, anti-melanogenic and anti-skin aging. Therefore, marine algae carbohydrates have potential of skin health benefits for value-added cosmeceutical application. The present review focused on the various biological capacities and potential skin health benefits of bioactive marine carbohydrates.

Considering the high potential of hydrogen (H₂) as a clean energy carrier, the implementation of high performance and cost-effective biohydrogen (bioH₂) purification techniques is of vital importance, particularly in fuel cell applications. In this context, membrane technology is a potentially energy-saving solution to obtain high-quality biohydrogen. The most promising poly(ionic liquid) (PIL) - ionic liquid (IL) composite membranes previously studied by our group for CO₂/N₂ separation, containing pyrrolidinium-based PILs with fluorinated or cyano-functionalized anions, were chosen as starting point to explore the potential of PIL–IL membranes for CO₂/H₂ separation. The CO₂ and H₂ permeation properties at the typical conditions of biohydrogen production (T =308 K and 100 kPa of feed pressure) were measured and discussed. PIL–IL composites prepared with [C(CN)₃]^– anion showed higher CO₂/H₂ selectivities and H₂ diffusivities compared to those containing [NTf₂]^– anion. All the membranes revealed CO₂/H₂ separation performances above the upper bound for this specific separation, highlighting the composite incorporating 60 wt% of [C₂mim][C(CN)₃] IL.

Antimicrobial peptides and structurally related peptoids offer potential for the development of new antibiotics. However, progress has been hindered by challenges presented by poor in vivo stability (peptides) or lack of selectivity (peptoids). Herein, we have developed a process to prepare novel hybrid antibacterial agents that combine both linear peptoids (increased in vivo stability compared to peptides) and a nisin fragment (lipid II targeting domain). The hybrid nisin-peptoids prepared were shown to have low µM activity (comparable to natural nisin) against methicillin-resistant Staphylococcus aureus.

2017 was an excellent year in terms of new drugs (chemical entities and biologics) approved by the FDA, with a total of forty-six. In turn, one of the highlights was the number of peptides (six) included in this list. Here, the six peptides are analysed in terms of chemical structure, synthetic strategy used for their production, source, biological target, and mode of action.

Biofilter application for treatment of stormwater containing de-icing chemicals commonly applied in airports, propylene glycol and potassium formate, was investigated. Lab-scale adsorption tests using filter media made of crushed clay (Filtralite) and granular activated carbon showed that adsorption was unsuitable for removal of propylene glycol and potassium formate. Column filtration experiment testing two different crushed clay size ranges was conducted. The results showed that DOC removal was dependent on a number of factors. This study investigated the impact of filter depth, nutrients addition, and filtration rate. DOC removal suggested that DOC degradation occurred on the top filter layer. It was shown that the most active separation occurred in the first ~20 cm of filter depth. This was confirmed by results from water quality analysis (i.e. DOC removal and ATP measurement) and calculations based on a filtration performance analysis (Iwasaki model) and filter hydraulic evaluation (Lindquist diagram). It was shown that for the highest C:N:P ratio tested (molar ratio of 24:7:1), 50-60% DOC removal was achieved. Addition of nutrients was found important and determining the biofilter performance.

In this work, we develop a self-consistent physical model of bubbles in a gas solid two-phase flow. Using the Peng-Robonson state equation and a detailed specific heat ratio equation of bubbles, we obtain the kinetic equations of the bubbles on the basis of the Ergun equation, thermodynamic equations, and kinetic equations. It is found that the specific heat ratio of bubbles in such systems strongly depends on bubble pressures and temperatures, which play an important role in the characteristics of the bubbles. The theoretical studies show that with increasing height in the systems, the gas flow rate shows a downward trend. Moreover, the larger particles in the gas solid flows are, the greater the gas velocity is. The bubble sizes increase with the increasing heights of the gas solid systems, and then decrease. The bubble velocity is affected by the gas velocity and the bubble size, which gradually increase and eventually quasi-stabilize. This shows that gas and solid phases in a gas solid two-phase flow interact with each other and a self-consistent system comes into being. The theoretical results have exhibited important value as a guide for understanding the properties and effects of bubbles in gas solid two-phase flows.

While referral-level medicine is important in the veterinary curriculum, students also need a solid base knowledge of clinically relevant routine surgery and diagnostic skills. Veterinary hospitals must maintain a steady caseload that provides wellness cases and commonly encountered conditions. Shelter Medicine programs can create the opportunities to meet these challenges. Students can gain quantifiable surgical experience in spay/neuter with measured growth in surgical efficiency and competency while providing needed community service for animal shelters. Students can directly interact with shelter animals by performing examinations, diagnostic testing, and development of treatment protocols and recommendations for commonly encountered problems. Furthermore, students can obtain a working knowledge of biosecurity on a population level to minimize risk of infectious diseases spreading to healthy populations.

Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, we apply the GRA theory to the HFSs and interval-valued hesitant fuzzy sets (IVHFS) domain. We propose the HFSs grey relational degree, HFSs slope grey relational degree, HFSs synthetic grey relational degree and IVHFSs grey relational degree, which describe the closeness, the variation tendency and both the closeness and variation tendency of HFSs and closeness of IVHFSs, respectively, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs and IVHFSs MADM problems. Finally, combined with two practical MADM examples about energy policy selection with HFSs information and emergency management evaluation with IVHFSs information, we obtain the most desirable decision results, and compared with the previous methods, the validity, effectiveness and accuracy of the proposed grey relational degree for HFSs and IVHFSs are demonstrated in detail.

Background: Diabetic retinopathy (DR) is one of the most prominent pathological microvascular complications in diabetes. A series of studies reported that vitamin D deficiency was associated with increased prevalence of retinopathy in diabetic patients but the results were inconsistent. In this study we focused on evaluating the relationship between vitamin D deficiency and DR by conducting a meta-analysis of observational studies. Methods: Systematic computerized searches were performed in PubMed, MEDLINE, and the Cochrane Library for relevant original articles till November 20, 2016. The pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated to assess the associated value of vitamin D deficiency to the risk of DR. 9 studies including 6332 participants were subjected to final analysis. Results: The results indicated that vitamin D deficiency increases the risk of DR (OR = 1.57, 95% CI 1.32-1.87) with a little heterogeneity (I2 = 23%). In addition, the subgroup analysis demonstrated that there were obvious heterogeneities in T2DM (I2 = 47.8%). Sensitivity analysis showed that the results were relatively stable and reliable. Conclusion: our meta-analysis demonstrated that vitamin D deficiency could increase the risk of DR.

In this paper, we present an approach which examines whether there are persistent abnormal returns around the periods of index rebalancing, using a factor-based framework. By employing this methodology, we observe the yield of normal returns around these events, although the detected abnormal returns may not usually be statistically significant. Therefore, we conclude the study by addressing how one such supposed strategy for rebalance trading is systematic constructive by supervision of some predictive model for the candidates based on all available in the TSX universe for inclusion into the S&P Capped TSX Composite Index in about a month. Trade signals were constructed using a logistic binary classifier based on the same factors used by the index committee to determine the qualifications for inclusion in the index. The problem of a very low probability of out of context security selection for addition to the index is solved at the expense of random over-sampling. In the end, these trade signals were then used to create a hypothetical trading strategy that outperformed the back-test period.

We offer a generalization of the conventionally used dead-time correction formulas, provided by Dytlewski, for neutron multiplicity counting. This aims to take into account the conditional effects of gate opening and in-gate neutron losses, and thus, extends to correlated pulse streams. The provided formulas are simple and include explicitly corrected rates obtained with the conventional method. In the limit of weakly correlated pulses with low count rates the generalized formulas reduce to Dytlewski’s expressions. We also performed the numerical validation of the method by simulating pulse-trains sets, evaluating the generalized dead-time correction accuracy and comparing it to the conventional one.

In 1935, Einstein and Rosen (ER), in their seminal paper "Particle Problem in General Relativity" proposed that "a particle in the physical Universe has to be described by mathematical bridges connecting two sheets of spacetime" in order to achieve a consistent understanding of quantum fields in curved spacetime. We discuss similar conclusions independently arrived at by Schr\"{o}dinger in 1956 and 't Hooft in 2016 in the context of cosmological and black hole spacetimes. Quantum effects at gravitational horizons involve inverse harmonic oscillators. We demonstrate that an analogous ER proposal of a mathematical bridge is envisioned by Berry and Keating for the description of a quantum inverse harmonic oscillator that has horizons in its phase space. Recently proposed direct-sum quantum theory reconciles the ER's vision by expressing a single quantum state in the physical space as a direct-sum of two components in the parity conjugate regions with opposite arrows of time. We discuss the implications of this framework for offering a new understanding of the ER bridges, promising a unitarity description of quantum fields in curved spacetime along with observer complementarity. Furthermore, we present compelling evidence for our new understanding of ER bridges in the form of large-scale parity asymmetric features in the cosmic microwave background. We finally discuss the implications of this new understanding for our endeavors in combining gravity and quantum mechanics.

Copper (Cu)-based fungicides are widely used in agriculture, but excessive Cu accumulation in soils threatens crop performance, particularly in perennial fruit crops like apples. This study investigated the effects of varying Cu concentrations on the physiological responses of three apple varieties—Braeburn, Fuji, and Cripps Pink—using a callus-media system. Callus cultures were exposed to Cu concentrations ranging from 0 to 20 mg Cu kg⁻¹ to assess traits such as growth, fresh and dry weight, copper accumulation, and bioconcentration factor (BCF). Results revealed that media Cu concentration had a stronger effect than variety on most traits, especially above 10 mg Cu kg⁻¹, where copper stress reduced genetic variability. At lower Cu concentrations, varietal differences were more apparent, with Cripps Pink showing greater copper tolerance. These findings suggest that high Cu levels suppress varietal differences, leading to a uniform stress response. This study provides valuable insights into copper toxicity in apple varieties and highlights the need to maintain soil Cu levels below critical thresholds to preserve varietal performance, with potential implications for soil-plant systems.

e Magnetic Ion Modulation (MIM) Theory presents a unified and groundbreaking mathematical framework for controlling and predicting ion behavior in both biological and non-biological systems using external magnetic fields. Central to the theory is the **Ion Modulation Constant** (Tn), a context-specific scaling factor that quantifies the number of ions modulated under specific conditions. This constant, although not universal, allows for accurate modeling of ion modulation in systems ranging from neuronal ion channels to plasma physics and quantum computing. The MIM equation incorporates ion properties such as magnetic moment and permeability, providing insights into neuromodulation for treating chronic pain and epilepsy, plasma confinement in fusion research, and stabilization of ion qubits in quantum computing. This paper includes detailed derivations of the Ion Modulation Constant, examples of its application to specific ions, and a comprehensive exploration of potential experimental validations.

The advent of the digital age has introduced unprecedented opportunities for communication and connectivity, but it has also given rise to new forms of harassment, collectively termed cyber harassment. This research article provides an in-depth exploration of cyber harassment, examining its prevalence, the profound impact it has on victims, and potential solutions to mitigate its effects.The study is structured around three primary research objectives. Firstly, it investigates the psychological impact of cyber harassment on victims, highlighting the severe emotional and mental health consequences that can arise from such abuse. Secondly, the article scrutinizes the role of social media platforms in both facilitating and combating cyber harassment, analyzing how these platforms can act as both enablers of harassment and as venues for intervention. Thirdly, the research evaluates the current legal frameworks and responses to cyber harassment, considering their effectiveness and suggesting possible improvements. Recent research findings and diverse methodologies are integrated to provide a comprehensive understanding of the multi-faceted nature of cyber harassment. By addressing these key areas, the article aims to contribute to the development of more effective strategies to prevent and respond to cyber harassment, ultimately fostering a safer online environment.

This paper introduces an open-source active high-precision signal amplifier designed for enhancing biodata acquisition, specifically focusing on EEG signals. The compact device, with a diameter of 18 mm, seamlessly integrates electronics, signal processing, and meticulous design considerations. Incorporated within the single board are circuits for low-noise amplification, an analog interface equipped with bandpass filters, and an integrated ADC for precise digitization. A comprehensive evaluation of signal quality has been conducted, encompassing aspects such as noise levels, electrode bias tolerance, and common mode rejection ratio. To facilitate this evaluation, the widely recognized Silver Chloride electrode (Ag/AgCl) has been employed. Additionally, this paper delves into an extensive discussion concerning diverse sources of noise, along with strategies to curtail input noise and minimize noise originating from electrodes and amplifiers. Leveraging the substantial advancements achieved in the design of dry contact electrodes, this specific device is poised to carve a notable niche in the realm of brain-computer interface.

The United Nations Global Sustainability Agenda 2030 introduces a transformative framework through its Sustainable Development Goals (SDGs), which are designed to achieve equitable, prosperous, and sustainable development globally. Unlike the incremental Millennium Development Goals (MDGs), the SDGs aim for systemic changes across economic, social, and environmental dimensions, ensuring that no one is left behind. This research paper provides a comprehensive examination of Pakistan's progress towards achieving the SDGs under the UN Global Sustainability Agenda 2030. Specifically, it includes an analysis of the prioritization of SDGs in Pakistan, highlights federal and institutional initiatives aimed at promoting sustainable development, and explores the role of the China-Pakistan Economic Corridor (CPEC) in advancing these goals. Additionally, the paper critically analyzes the SDGs in Pakistan’s annual status report, identifies the key challenges faced by the nation in implementing these goals, and offers recommendations for enhancing the effectiveness of SDG implementation. Overall, the focus is primarily on the detailed analysis of the annual status report, the challenges encountered, and strategic recommendations for achieving excellence in SDGs in Pakistan.

The learning system is primarily based on teaching, and teaching through digital resources is referred to as e-learning. As the world progresses towards success day by day, the use of technology, digital devices, and modern techniques is becoming increasingly prevalent. The global shift from traditional paperwork to digital learning is one of the most significant changes in the education sector. However, many factors have created numerous hurdles during the online setup. The Covid-19 pandemic has led to serious problems all over the world, with the education sector being one of the most affected. One of the greatest challenges students face during online education is the lack of digital infrastructure, especially in remote areas of Pakistan. The biggest challenge is connecting students with teachers due to limited internet access. Without proper internet connectivity, both students and teachers cannot access educational materials. In this context, the government plays a crucial role in providing adequate facilities to students, particularly in primary schools. If proper infrastructure is not made available during this pandemic, students will be deprived of a good quality education. Therefore, good infrastructure is essential for effective online education. With the proper resources in place, students will be able to receive a quality education.

As with all new fields of discovery, work on the biological role of G-quadruplexes (GQ) has produced a number of results that at first glance are quite baffling, sometimes because they do not fit well together, but mostly because they are different from commonly held expectations. Like other classes of flipons, those that form G-quadruplexes have a repeat sequence motif that enables the fold. The canonical DNA motif (G3N1-7)3G3, where N is any nucleotide and G is guanine, a feature that is under active selection in avian and mammalian genomes. The involvement of G-flipons in genome maintenance traces back to the invertebrate Caenorhabditis elegans and to ancient DNA repair pathways. A role for GQ in transcription is supported by the observation that yeast Rap1 protein binds both B-DNA, in a sequence-specific manner, and GQ, in a structure-specific manner, through the same helix. Other sequence-specific transcription factors (TF) also engage both conformations to actuate cellular transactions. Noncoding RNAs can also modulate GQ formation in a sequence-specific manner and engage the same cellular machinery as localized by TF, linking the ancient RNA world with the modern protein world. The coevolution of noncoding RNAs and sequence-specific proteins is supported by studies of early embryonic development, where the transient formation of G-quadruplexes coordinates the epigenetic specification of cell fate.

Pipelines are regularly trenched and then forgotten, just allowed to run till failure and producing an overall incredibly poorly run system that is ripe for improvements. One of the most needed areas for improvement are proactive methods for condition assessment of existing pipelines. This can be divided into two main categories: proactive condition assessment technologies and nonstructural proactive condition improvement technologies. The objective of this paper is to identify the best option available on the market for both these areas of proactive condition assessment for existing pipelines. The compared proactive condition assessment technologies include Acoustic Resonance Testing, Ultrasonic Thickness Measurement Testing, Phased Array Ultrasonic Testing, Pulsed Eddy Current Testing, and the Multisensor ROV. The technologies compared for nonstructural proactive condition improvement were Jetting, Pigging and also included the main requirements for a proper catalog of pipe information that can be used to produce a ranked system for assessing which pipes are at highest risk for failure and can be used to efficiently direct resources for pipe maintenance. The final conclusion was that Acoustic Resonance Testing and the Multisensor ROV are the two best products available for the proactive condition assessment of existing pipelines available on the market from their versatility of application and amount of information gathered during pipe inspection. The best option available in the group of nonstructural proactive condition improvement technologies was pigging for its incredibly low risk and low social impact as well as potential for improvement in the near future. It was also concluded that every agency would be better off with a catalog of the pipe material, age, length, diameter, and burial depth to know the location of every pipe an agency owns as well as to rank every pipe in terms of risk of failure and impact of said failure to most efficiently direct resources.

CpG islands typically occur at or near the transcription start site of genes, particularly housekeeping genes, invertebrates. Normally a C (cytosine) base followed immediately by a G (guanine) base (a CpG) is rare in vertebrate DNA because the cytosines in such an arrangement tend to be methylated. Described DNA methylation mediated gene silencing occurs by direct inhibition of transcription factor binding to their relative sites and by recruitment of methyl binding domain proteins. The present study aims at predicting the CpG islands using Perl and R environment codes. The results indicated that the average length of the CpG islands in the X-chromosomes is comparable, however, the number of CpG islands is three times in swine (13539), as compared to that of rats (4465). The average CpG percent and the Average Guanine+Cytosine percent are also similar in the X-Chromosomes of both species. Similar results were evident for Y-Chromosome. The results obtained need validation through wet-lab experimentation.

Within the research of pressure pipeline inspection methods there is an industry that is constantly growing and becoming more efficient. The purpose of inspection methods on pressure pipelines comes back to the issue of resolving leaks, corrosion, and inability of a pipeline to function (eventually). Evidently, these issues can hurt the environment, the public using the material being carried out by these pressure pipelines such as natural gas or petroleum and can hurt the pockets of pipeline companies that did not react quick enough to their pipeline solely for the reason that they may have not noticed there was an issue with their pressure pipeline. In-line inspection methods are continuously growing and have already made an impact to prevent the catastrophes that occur when a pipeline is not maintained. Technology such as smart pigs, MFLs, and ultrasounds are the future of pressure pipeline inspection. This research paper explains their pros and cons and how they’re overall more efficient and preferred as the primary inspection method for a pipeline. Older, more traditional methods such as aerial inspection, by-foot inspection, hydrostatic pressure testing, and Direct Assessment does not cover every base of inspection like in-line inspection technology does and this research explains why that is and the areas of where in-line inspection technology can be improved and deemed not as useful. This is where trenchless renewal and replacement methods come into play with inspection methods and determining the characteristics of a pipeline that matches with which inspection method and which trenchless method to use. The future of inspection methods for pressure pipelines is attainable and is somewhat already here, this research discusses the new emerging technologies and how designing in-line inspection technology to be cheaper and more versatile with pipeline characteristics can make everyone a winner in the future. A winner as far the environment being safe, neighborhoods near pressure pipelines being safe, companies being able to install in-line inspection technology at a fraction of the cost of today and the efficiency of pipelines by monitoring the characteristics with this new technology.

In the field of music education, the incorporation of technology originally designed for professionals presents both significant opportunities and challenges. These technologies, although advanced and powerful, are often not adapted to meet the specific needs of the educational envi-ronment. Therefore, this study details the design and implementation process of a system con-sisting of a hardware device called "Play Box" an associated software, "Imaginary Play Box". The Design Sciences Research Methodology (DSRM) specifically adapted to software development was used to structure the project. The three phases shown in this study ranged from the conception of an initial prototype to the realisation of a working software. During the design phase, a questionnaire was developed to evaluate various aspects of the soft-ware, such as the visual interface, the programming of components and the sound interactivity provided by the Play Box. The technique of panels of experts in music pedagogy and program-ming in MAX-MSP was used to obtain critical feedback. This expert evaluation was crucial to it-erate and polish the software, culminating in a beta version optimised for the creation of electro-acoustic music for music education.

High-Performance Liquid Chromatography (HPLC) is an advanced analytical technique employed to separate, identify, and quantify components in complex mixtures. The method operates based on the differential affinities of sample molecules for the mobile and stationary phases within a chromatographic column. HPLC is recognized for its high resolution, accuracy, and efficiency, making it indispensable across various fields including pharmaceuticals, biotechnology, environmental analysis, and forensic science. The technique's adaptability to different detectors such as UV-visible, fluorescence, and mass spectrometry enhances its versatility and precision in analyzing a wide array of substances. Despite its advantages, HPLC presents challenges such as high operational costs, the need for specialized expertise, and susceptibility to contamination.Nonetheless, its role in modern analytical chemistry is pivotal, providing crucial insights and supporting developments in diverse scientific and industrial domains. This abstract encapsulates the core aspects of the article, highlighting the significance and applications of HPLC while also acknowledging its limitations.

This paper gives a brief insight of project requirements for “Wireline” method of Horizontal Directional Drilling (HDD). In any drilling project, it is extremely important to know the precise location of existing lines, know the precise location of the advancing drill bit and know the precise location of the newly installed line. The wireline method is mainly used to accurately steer during medium (Midi-HDD), and large (Maxi-HDD). Today, there are two methods of HDD wireline steering: magnetic and gyro. The magnetic steering tool uses a surface tracking system to verify the tool’s precise underground position. Sensors located within the down-hole provide constant updates of Inclination, Azimuth and Tool Face orientation to the surface via a wireline. The data is processed utilizing computers from the surface and specialized Steering software to provide information on depth, course length and distance off the predetermined azimuth. In addition to a great steering method, HDD projects require the presence of well-trained and experienced steering technicians. Those people are specifically trained to operate the machinery, and it would be counterproductive to work with such great equipment without the help of the correct operators. In conclusion, the wireline method of HDD has a unique capability to track the location of the cutterhead and steer it during the drilling process. The result is a greater capability in placing the necessary utilities in difficult underground conditions.

Pipes have been utilized since ancient times and have seen significant renewal, modification, and replacement to improve their effectiveness and efficiency in the modern era. As early as 4000 BC, Egyptians used clay pipes for drainage systems. The U.S. has the largest network of energy pipelines in the world. The ASCE 2017 Infrastructure Report Card assigned grades of D and D+ to water and wastewater pipelines, highlighting a substantial need for improvement. The paper investigates the infrastructure required for the sustainability of pipeline systems, as well as the construction of underground systems using both open-trench and trenchless technologies, along with the associated risks in the US. It concludes that trenchless methods are increasingly preferred for pipeline construction due to technological advancements, reduced surface disruptions, shorter construction times, and lower social costs. Tackling this challenge will necessitate strategic investment, decisive leadership, thorough planning, and meticulous preparation for future demands. Enhancing pipeline infrastructure can stimulate the U.S. economy, whereas postponing action will lead to higher costs.

This work aims to assess the impact of the COVID-19 pandemic on mortality and incidence of complications in patients with bacteremia due to Staphylococcus aureus (BSA). All episodes of BSA at the Costa del Sol University Hospital (Marbella, Spain) were recorded during the acute phase of the COVID-19 pandemic (March 2020 - March 2022), compared with a previous period (February 2018 - February 2020). Demographic, clinical and prognostic variables were recorded. The outcome was measured as 14 and 30-day mortality and the incidence of complications-death. Mortality during the pandemic was 28.7% at 14 days and 35% at 30 days, while in the pre-pandemic group it was 18.9% and 23.3%, respectively. In overall complication-death, the incidence rate is higher in the pandemic group with 42.7%. No significant differences were obtained between groups. 17 patients with COVID-19 were identified, with a mortality rate of 64.7% and 70.6% at 14 and 30 days. Multivariate analysis established the presence of sepsis at diagnosis as a predictor of mortality, but not BSA during the pandemic phase. In conclusion, BSA is a disease with high mortality, slightly higher during the pandemic phase. No differences were found in adherence to the bundle in our centre.

The electronics industry is a significant contributor to environmental challenges, generating approximately 50 million tons of electronic waste annually and high levels of carbon dioxide emissions throughout the production and disposal of devices. This paper investigates the interplay between reliability and sustainability by analyzing how degraded components affect the environmental footprint of electronic products. Using a board with 215 components as a baseline, we calculate the mean time between failures (MTBF) and compare it to scenarios involving degraded components. Our findings demonstrate that degraded components can reduce MTBF by up to 50%, resulting in higher failure rates, increased electronic waste, and up to 30% more CO2 emissions due to shortened product lifespans. This study underscores the crucial importance of component quality control in the production process to improve both reliability and sustainability. Additionally, the broader economic and environmental impacts of using unchecked components are highlighted, showing their contribution to elevated failure rates, shortened product lifespans, and an estimated 20% increase in e-waste. By adopting a 100% inspection protocol, leveraging advanced technologies, and enforcing stringent material quality controls, manufacturers can significantly enhance the reliability of electronic products while reducing their environmental impact, thus fostering a more sustainable electronics industry.

This paper examines the utility and exploitation of non-obvious "alien" AI constructions, artificial intelligence solutions that significantly deviate from human intuition and traditional problem-solving approaches. It explores recent revelations, key characteristics, applications across various domains, and far-reaching implications for scientific research and innovation. Particular attention is given to developments in mathematical reasoning, drug discovery, and healthcare. The paper also discusses challenges in implementation, ethical considerations, and future directions, including meta-learning algorithms and human-AI collaboration frameworks. By synthesizing current research and identifying emerging trends, this paper aims to provide a basic understanding of the transformative potential of non-obvious AI solutions in reshaping scientific discovery and biomedical innovation.

Trenchless technologies are utilized for installing new pipes or repairing and replacing old ones, categorized into construction and rehabilitation/replacement methods. With rapid urbanization, new pipe networks must be established in proportion to population growth. Additionally, due to issues like corrosion and aging, a significant portion of storm sewers, waste sewers, gas, and water pipes need annual replacement or rehabilitation. Traditional open-cut methods are no longer viable due to traffic disruption, safety concerns, environmental impacts, and high costs. Trenchless construction methods address these issues effectively. Construction trenchless methods include horizontal earth boring (no worker entry), pipe jacking, and utility tunneling (worker entry). Horizontal earth boring is further divided into horizontal auger boring, horizontal directional drilling, pipe ramming, microtunneling, pilot tube microtunneling, and compaction methods. The first part of the current study reviews and discusses the design criteria for horizontal auger boring, horizontal directional drilling, pipe jacking, pipe ramming, and microtunneling. Based on these unique project requirements, the optimal trenchless technology can be proposed. In the second part of the research, a hierarchical algorithm is proposed, based on literature concepts, to serve as a decision-making tool for selecting the optimal trenchless construction method. Sometimes, multiple methods may be proposed, with the best one chosen based on equipment availability, skilled teams, budget, and sustainability principles. Although trenchless renewal methods are not the focus of this study, their design criteria are provided in the appendices to offer a comprehensive collection of design requirements for all trenchless technologies.

Large language models have recently made significant progress in natural language processing, and there is observation that these models exhibit reasoning abilities when they are sufficiently large. This has sparked considerable research interest since reasoning is a hallmark of human intelligence that is widely considered missed in artificial intelligence systems. Due to large size of these models, evaluation of LLMs’ reasoning ability is largely empirical. Creating datasets to evaluate the reasoning ability of LLMs is therefore an important area of LLM research. A key open question is whether LLMs reason or simply recite memorized texts they have encountered during their training phase. This work conducts simple experiments using Cheryl’s Birthday Puzzle and Cheryl’s Age Puzzle and their variants created in this work to investigate whether LLMs recite or reason and discovers that LLMs tend to recite memorized answers for well-known questions, which appear more frequently on the internet, even though such answers may not be sensible for the modified versions of the questions. When presented with less well-known questions, it is observed that LLMs answer with correct reasoning more frequently. A possible inference is that LLMs tend to reason on less well-known questions but recite memorized answers on popular questions. As a result, to accurately evaluate the reasoning ability of LLMs, it is essential to create new datasets to ensure that LLMs are elicited to truly use their reasoning ability to generate responses to the presented questions. In view of the finding, this work proposes a new dataset comprising of unseen questions requiring semantic and deductive logical reasoning skills to elicit reasoning ability from LLMs. The proposed evaluation framework is based on the intuition that some questions or puzzles can only be answered through the mastery of reasoning needed for situational awareness, and the dataset consists of 84 logical reasoning questions on room assignment subject to constraints. The proposed evaluation framework has several desirable properties, including resilience to training data contamination, ease of response verification, extensibility, usefulness and automated test case generation. This work then applies the proposed dataset to evaluate the reasoning ability of state-of-the-art LLMs, including GPT-3, GPT-4, Llama-3.1, Gemini-1.5 and Claude-3.5, and compare their performance with the performance of human intelligence on the dataset.

The present paper explored the possibility of discriminating between different malignant degrees of Chondrosarcoma (CS), a diffused bone tumor, and Enchondroma (EC), its benign version, through an approach based on the coupling between Confocal Raman Microscopy (CRM) and Machine Learning (ML) techniques. Recently, Raman Spectroscopy has proven to be a powerful tool for a complete grading of CS by distinguishing between grade 1, 2 and 3, and to distinguish CS from EC. In this paper, we tested some models, belonging either to ML or to the sub-type called Deep Learning (DL), showing excellent classification performances, especially the DL algorithms, with classification accuracy approaching to 100%, making the models promising for future implementations of Raman spectroscopy when applied to oncology diagnosis. In turn, we highlighted how some proper ML models result in worse classification performances but better resolution of specific chemical target compounds, possible candidate to become malignant markers, with relevant implication for a correct diagnosis.

The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness in several settings. The EU's regulatory framework advise for deploying one air quality monitoring unit per roughly 170,000 people or 15 square kilometers which is insufficient for capturing high spatio-temporal variance in complex urban scenarios. Often these settings are characterized by distributed emissions in small roads subjected to intense cars traffic, house heating driven emissions and frequently subjected to canyon effects. The Air Heritage project in Portici, funded by the EU's Urban Innovative Actions (UIA) program, addressed these challenges by integrating low-cost sensors with traditional monitoring systems and engaging the community in pervasive measurement strategies. The project highlights the importance of individualized sensor calibration and frequent recalibrations to maintain accuracy. It also showcases the benefits of citizen science approaches, IoT infrastructures, AI components, and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements. This paper reports on the lessons learned and experiences from the Air Heritage project, aiming to guide future implementations in similar contexts. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, public authorities, and citizens, about effective strategies for deploying and utilizing LCAQMS to enhance air quality monitoring and public awareness.

The research article provides an in-depth analysis of the European Medicines Agency (EMA) and the Directorate General of Drug Administration (DGDA), focusing on their historical development, organizational structures, and functional roles in ensuring the quality and safety of pharmaceuticals. The study highlights the origins of drug regulation, tracing back to the early 19th century in the United States with the establishment of the Food and Drug Administration (FDA), and discusses the evolution and significance of drug regulatory bodies worldwide. The EMA and DGDA are scrutinized for their efforts in maintaining high standards for drug approval, monitoring clinical trials, and managing post-marketing surveillance to prevent adverse drug reactions (ADRs). The EMA’s role in coordinating with EU member states on pharmacovigilance and the DGDA’s initiatives in Bangladesh, including the implementation of a nationwide drug database and pharmacovigilance system, are explored in detail. The article concludes by emphasizing the essential role of these regulatory bodies in safeguarding public health through stringent regulation and continuous monitoring of pharmaceuticals, thereby ensuring that only safe and effective medicines are available to consumers . It also provides an in-depth analysis of the roles, structures, and historical contexts of the European Medicines Agency (EMA) and the Directorate General of Drug Administration (DGDA). It outlines how these regulatory bodies ensure the safety, efficacy, and quality of medicinal products. The EMA, serving the European Union, and the DGDA, operating in Bangladesh, play critical roles in drug approval processes, pharmacovigilance, and maintaining public health standards. By setting rigorous guidelines and monitoring compliance, these agencies help safeguard the health of millions, ensuring that only safe and effective medications are available in the market. The paper underscores the importance of these regulatory bodies in promoting public health and supporting the pharmaceutical industry's development and innovation.

The Blue Economy represents a sustainable development model emphasizing the responsible use of ocean resources to foster economic growth while preserving marine ecosystems. This approach aims to balance economic prosperity with environmental conservation, recognizing the oceans' crucial role in supporting life on Earth. Key sectors within the Blue Economy include fisheries, tourism, renewable energy, maritime transportation, and aquaculture. As global populations rise and climate change impacts intensify, the Blue Economy is increasingly seen as essential for addressing global challenges and promoting sustainable development. Responsible fisheries management, such as implementing fishing quotas and creating marine protected areas, is crucial to combat overfishing and ensure food security. Sustainable aquaculture practices further alleviate pressure on wild fish stocks. Marine tourism, or ecotourism, promotes responsible practices that benefit local communities and the marine environment. Activities like beach clean-ups, wildlife conservation, and responsible diving practices are integral to this sector, supporting local economies and conservation initiatives. The Blue Economy significantly impacts the global economy, with the potential to double its contribution to the world's GDP by 2030. Sustainable marine sectors create jobs, drive economic growth, and contribute to energy security by harnessing renewable ocean-based energy sources. Additionally, the Blue Economy fosters innovation and technological advancements, enhancing competitiveness across various industries. Despite its potential, the Blue Economy faces challenges like overfishing, pollution, and climate change, which threaten marine biodiversity and ecosystems. Addressing these issues requires international cooperation, effective governance, and public awareness to promote sustainable practices and protect marine resource.

This study introduces a novel method for early prediction of Kimchi cabbage (Brassica rapa subsp. pekinensis (Lour.) Hanelt) height, utilizing drone imagery and a long short-term memory (LSTM) model. The research was conducted on a testbed at the National Institute of Agricultural Sciences (NAS) in South Korea, encompassing two distinct soil types (loam and sandy loam) to investigate their impact on growth. High-resolution drone images were captured throughout the growing season to generate a canopy height model (CHM) for estimating plant height at various stages. Missing height data were interpolated using a logistic growth curve, and an LSTM model was trained on this data to predict the final height of Kimchi cabbage at harvest. Three LSTM models were developed using time-series data collected at 29, 36, and 44 days after planting (DAP). The model trained on data from DAP 44 demonstrated the highest accuracy with a coefficient of determination (R²) of 0.83, a mean absolute error (MAE) of 2.48 cm, and a root mean square error (RMSE) of 3.26 cm, outperforming models trained on earlier data. Color-coded maps were generated to visualize the spatial distribution of predicted Kimchi cabbage heights, revealing variations in growth patterns across the testbed and confirming the model's potential for site-specific management. Considering the trade-off between accuracy and prediction timing, the model trained on DAP 36 data (MAE = 2.77 cm) was deemed optimal for informing cultivation management decisions. This research demonstrates the feasibility and effectiveness of integrating drone imagery, logistic growth curves, and LSTM models for early and accurate prediction of Kimchi cabbage height. The proposed technology enables data-driven decision-making for farmers, facilitating timely interventions based on predicted growth patterns. This could lead to improved crop yields, resource optimization, and a more sustainable agricultural future. Future research will focus on refining the model's accuracy and exploring its applicability to other crops, further expanding the potential of precision agriculture technologies.

Leptospirosis is a zoonosis with global public health impact, particularly in poor socio-economic settings of tropical regions. Transmitted through urine-contaminated water or soil from rodents, dogs, and livestock, leptospirosis causes over a million clinical cases annually. Risk factors include outdoor activities, livestock production, and substandard housing that foster high densities of animal reservoirs. This One Health study in southern Chile examined Leptospira serological evi-dence of exposure people from urban slums, semi-rural, and farm settings, using the Extreme Gradient Boosting algorithm to identify key influencing factors. In urban slums, age, shrub terrain, distance to Leptospira-positive households, and neighborhood housing density were contributing factors. Human exposure in semi-rural communities was linked to environmental factors (tree, shrub, and lower vegetation terrain) and animal variables (Leptospira-positive dogs and rodents, and proximity to Leptospira-positive households). On farms, dog counts, animal Leptospira preva-lence, and proximity to Leptospira-contaminated water samples were significant drivers. The study underscores that disease dynamics vary across landscapes, with distinct drivers in each community setting. This case study demonstrates how the integration of machine learning with comprehensive cross-sectional epidemiological and geospatial data provides valuable insights into leptospirosis eco-epidemiology. These insights are crucial for informing targeted public health strategies and for generating hypotheses for future research.

The transition to renewable energy sources is pivotal in addressing the escalating challenges of climate change and environmental degradation. Solar energy, particularly photovoltaic (PV) technology, stands out as a prominent solution due to its potential for clean and sustainable electricity generation with minimal greenhouse gas emissions. However, accurately assessing the carbon footprint of PV modules is essential for guiding policy, industry practices, and research. This paper reviews the state of current literature and highlights the difficulties in estimating the carbon footprint of PV modules manufactured in China. It emphasizes the inherent limitations of Process-Based Life Cycle Assessment (PLCA), including data collection challenges, dynamic environmental changes, and subjective methodological choices. The study underscores the need for improved transparency, standardization, and reproducibility in Life Cycle Assessments (LCAs) to provide more accurate and reliable environmental impact evaluations.

This paper presents a hybrid modelling approach that combines physics-based electromigration modelling (PEM) and statistical methods to evaluate the electromigration (EM) limits of nano-interconnects in mesh networks. The approach, which is also compatible with standard Place and Route (P&R) tools and practices, takes into account the positive impact of network redundancy on EM current limits. The study shows that conventional methods underestimate the EM current limits of a power delivery network (PDN) unit-cell by 80% due to their lack of consideration for redundancy. Additionally, the time-to-failure (TTF) distributions of a PDN unit-cell adhered to a lognormal distribution, where the lognormal sigma, σlogn, exhibits a 55% reduction compared to that of the single constituent interconnects. The study also found the negative voltage (i.e. ground or Vss) grid to be more susceptible to EM than the positive voltage, i.e. Vdd grid. In the examined grid unit-cell design, both the number of interconnect sites prone to voiding and also the magnitude of the peak tensile stress within the nano-interconnects were found to be 2-folds as high in the Vss case compared to Vdd. lognormal sigma of TFF for the grid unit-cells, σ_(logn-tile), show a marked reduction compared to the lognormal sigma of the constituent single interconnects, σ_logn, with a 50% and 66% decrease compared to single interconnects, for downstream (Vss) and upstream (Vdd), respectively. In addition, σ_(logn-tile) was 3-folds higher for downstream (Vss) compared to upstream (Vdd), whilst, in contrast this difference was only 2-folds at single interconnect level. 4.13-folds higher TTF50% was observed at grid unit-cell level for upstream compared to downstream operation which was also more pronounced than in the single interconnect level where the difference was only 2-folds. This research provides valuable insights into EM aging of nano-interconnects in mesh networks and could pragmatically enhance the accuracy of EM compliance evaluation methods.

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the MVM operation involving a 32x32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs.

Objective: This study aims to establish a link between primary healthcare service accessibility among rural populations and the principle of territorial equity, a pivotal aspect of regional development strategies. Methods: We conducted a comprehensive analysis of primary healthcare service accessibility in rural Quebec, integrating theoretical frameworks and empirical evidence on territorial, regional, and community development. Through this approach, we sought to comprehend the nuanced dynamics and mechanisms contributing to territorial equity enhancement. Results: Our findings indicate that refining developmental strategies through community-driven approaches and regional initiatives can foster territorial equity. Moreover, employing sophisticated methodologies to measure primary healthcare service accessibility can promote territorial equity, emphasizing community development. Conclusion: Enhancing access to primary healthcare services and employing advanced assessment methodologies are essential for advancing territorial equity and supporting regional development initiatives. This underscores the critical importance of prioritizing healthcare accessibility in rural areas to achieve equitable development outcomes.

We argue that several potentials proposed recently for the analysis of the vibrational-rotational spectra of diatomic molecules and their thermodynamic properties exhibit a flaw. One can easily show that the parameters $D_e $ and $r_e$ in those potentials are not the dissociation energy and equilibrium bond length, respectively, as the proposers believe. We show how to overcome the mistake in a simple and quite general way.

RNA-seq faces persistent challenges due to the ongoing expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Shannon entropy serves as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, employing RPKM and median normalization on paired samples of 475 TCGA RNA-seq datasets spanning eight different cancer types with 5-year overall survival rates ranging from 30% to 98%. Our analysis revealed that the RPKM normalization coupled with a threshold of log2 fold change ≥1 for indentifying differentially expressed genes, yielded the best results with a correlation coefficient of 0.91. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows.

We overview the main equations of the Rayleigh-Ritz variational method and discuss their connection with the problem of simultaneous diagonalization of two Hermitian matrices.

This concept paper explores possible collective identities for a future wildland fire workforce. Taking inspiration from the work of futurists who foresee an end to the dominant fire exclusion/suppression paradigm, and assuming an emerging fire restoration/resilience paradigm shift replaces it, the paper engages in speculative explorations of the process and product of this paradigm shift on future collective identities for a workforce doing ecological fire management. Social constructionist assumptions from symbolic interactionist sociological theory, Gramscian political theory's concept of hegemony, and New-Social-Movement theory's concept of collective identity all provide the intellectual foundations for the discussion. This concept paper argues that in order to actualize a paradigm shift, more than advances in scientific research or reforms of government policies will be required--the wildland fire community will need to become (or join) a social movement engaged in collective actions. An imaginary social movement, the "Greenfire revolution," is invented to help illustrate how the selected theories and concepts might apply in the social construction of ecological fire management and the collective identities of its future workforce.

This study explores innovative strategies to enhance hands-on learning experiences in a Database Management Systems (DBMS) course while addressing challenges related to software installation complexities and financial barriers. The investigation focuses on an online course format catering to students majoring in information systems, healthcare administration, business administration, and marketing. Traditional software installation hurdles, especially for complex systems like Microsoft Access and MySQL, can impede students' engagement and access. To overcome these challenges, the study proposes leveraging cloud-based solutions and clientless remote desktop gateways like Apache Guacamole. Results indicate that these approaches effectively eliminate software installation obstacles, ensuring seamless access to essential tools for all students. The study underscores the importance of innovative technological solutions in promoting inclusive and impactful learning environments in higher education.

This study investigates the impact of integrating ChatGPT on the academic writing performance and engagement of English as a Foreign Language (EFL) undergraduate students in Delhi, India, during the first semester of the academic year 2024/2025. It addresses the challenges within the Indian education system by exploring the effectiveness of AI-driven writing tools in enhancing writing skills and motivation among EFL learners. Employing a mixed-methods approach, the research evaluates ChatGPT's influence on 32 EFL Indian undergraduate students through draft revisions, questionnaires, and interviews. The findings highlight ChatGPT's positive impact on writing quality, engagement levels, and immediate feedback appreciation, emphasizing its potential in improving writing instruction and student outcomes in EFL contexts. Recommendations are provided for practitioners to integrate ChatGPT in writing exercises and for researchers to conduct longitudinal studies and explore ethical considerations in AI use for educational purposes, ultimately contributing to enhanced EFL education and technology-mediated learning.

Gabapentin (GBP) was originally developed as a potential agonist for Gamma-Amino-Butyric-Acid (GABA) receptors, aiming to inhibit the activation of pain-signaling neurons. Contrary to initial expectations, it does not bind to GABA receptors. Instead, it exhibits several distinct pharmacological activities, including: (1) binding to the alpha-2-delta protein subunit of voltage-gated calcium channels in the central nervous system, thereby blocking the excitatory influx of calcium; (2) reducing the expression and phosphorylation of CaMKII via modulation of ERK1/2 phosphorylation; (3) inhibiting glutamate release and interfering with the activation of NMDA receptors; (4) enhancing GABA synthesis; (5) increasing cell-surface expression of δGABA_A receptors, contributing to its antinociceptive, anticonvulsant, and anxiolytic-like effects. Additionally, GBP displays (6) inhibition of NF-kB activation and subsequent production of inflammatory cytokines, and (7) stimulation of the purinergic adenosine A1 receptor, which supports its anti-inflammatory and wound-healing properties. Initially approved for treating seizures and postherpetic neuralgia, GBP is now broadly used for various conditions, including psychiatric disorders, acute and chronic neuropathic pain, and sleep disturbances. Recently, as an eye drop formulation, it has also been explored as a therapeutic option for ocular surface discomfort in conditions such as dry eye, neurotrophic keratitis, corneal ulcers, and neuropathic ocular pain. This review aims to summarize the evidence supporting the molecular effects of GBP, with a special emphasis on its applications in ocular surface diseases.

In areas like commercial and policy decisions—it's important to know how different treatments affect things and how well they work. However, treatments affect things on average—but now—with fancy computer methods and big sets of data, interest lies in figuring out how treatments might work differently for different people. For instance, let's say instead of just looking at what works for most people, researchers want to know which treatment is best for each person. This would help doctors to decide the right treatment for each patient. This idea isn't just for healthcare—it can help in other areas too, like deciding how to govern employees or making government policies. There are some ways people have been trying to do this already, but they struggle when there are lots of different factors to consider. New computer methods, though, are good at handling lots of factors, but they need a ton of data to work well. Therefore, this study looks at three computer methods that are—Virtual Twin Random Forest (VTRF), Causal Forest (CF), and Causal Net (CN) using real-world data about encouraging people to do manual labour. One problem this study is trying to solve is something called the "winner's curse", where a treatment might seem better than it really is because of how it's predicted by the computer. We are also testing some ideas to see if we can fix this problem and make the predictions more accurate.

Dengue, a perilous fever-type illness transmitted by mosquitoes, remains a significant global health concern. The incidence of dengue outbreaks is primarily influenced by climate factors, contributing to fluctuating dengue cases. Therefore, this study aims to develop predictive models for dengue outbreaks employing Machine Learning (ML) techniques. Four distinct ML models, namely K-Nearest Neighbor (KNN), Random Forest (RF), Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR), were employed in this study. Prior to model analysis, thorough data preprocessing was conducted. In some instances, certain attributes exhibiting sparse correlations with dengue occurrence were eliminated based on correlation analysis. Upon finalizing the models, performance evaluation was executed through comparison based on Mean Absolute Error (MAE) metrics. The findings of this comparative analysis revealed that the KNN model exhibited significantly superior performance compared to the other three models. This outcome underscores the potential of KNN in enhancing the accuracy of dengue outbreak predictions.

The emission of sulphur dioxide (SO2) from mining activities presents a substantial risk to public health, especially in populations located near mine industrial regions. This study investigated the potential correlation between exposure to sulphur dioxide (SO2) and its effects on respiratory health in Kankoyo Township, Zambia. A variety of methodologies were employed in this study, encompassing community participation, expert interviews, spatial analysis, and a retrospective examination of health and SO2 data for Kankoyo spanning 15 years. The results of our research indicated a worrisome correlation between the community and the presence of SO2, which has had a significant impact on their lives. The expert interviews also emphasized the effects of SO2, with respiratory cases accounting for approximately 75% of the reported cases. Additionally, the clinic officer observed that asthma cases have decreased following the implementation of a monitoring station in the community. Furthermore, overall emissions of SO2 have decreased since the upgrade of the smelter operation. A probable association was identified in the retrospective analysis between exposure to SO2 and the occurrence of asthma, respiratory non-pneumonia, and pneumonia infections. The findings of the retrospective research revealed a substantial association between SO2 concentrations and the susceptibility of individuals aged 5 years and older to asthma, respiratory non-pneumonia, and pneumonia infections. The results of the spatial study indicated that Kankoyo exhibited a significant level of SO2 pollution, above the established limitations set by the Zambian Environmental Management Agency (ZEMA) by an alarming margin of 1713%. In response to the challenges identified, this study proposed several measures. These measures encompassed the implementation of a requirement for regulators such as ZEMA and local communities to have access to real-time pollution data from mines, to enhance transparency. Additionally, the deployment of affordable air quality sensors, the resolution of medication shortages, the establishment of specialized respiratory health clinics, the initiation of IT-driven public awareness campaigns, and the expansion of research to investigate additional pollutants and confounding factors were also recommended.

We present contrast information, a novel application of some specific cases of relative entropy measures, designed to be useful for cognitive modelling of sequential perception of continuous signals. We explain the relevance of entropy in cognitive modelling of music and language. Then, as a first step to demonstrating the utility of constrast information for that purpose, we show empirically that its discrete case correlates well with existing successful cognitive models in the literature. We explain some interesting properties of constrast information. Finally we propose future work towards a cognitive architecture that uses it.

Machine safety is not only a prerequisite for successful production, but also the foundation for sustainability and growth of any manufacturing organisation. The latest approaches in this rapidly developing field are the integration of effective risk management tools and strategies into occupational health and safety (OHS) systems. In this article, using a specific example from practice, we will show how using multi-criteria decision making (AHP) support Machinery Safety Decision Making (MSDM) from the point of reducing losses. Using Classification and Regression Tree Analysis (CART), we estimated the efficiency, cost-effectiveness and thus the sustainability level of the relevant safety measures. These were proposed risk reduction measures that typically raised uncertainty among managers regarding the estimation of cost-effectiveness. The advantage of application decision trees approach is possibility to identify and establish relatively homogeneous groups of undesirable events and their impact on the organisation's objectives. A comprehensive model has been developed to support management decision making in manufacturing organizations in implementing and improving safety measures in line with manufacturing sustainability goals.

Social surveys are conducted to determine how annoyed people are in a certain noise situation. The results are typically presented as exposure-response curves showing the percentage of the area population that are highly annoyed as a function of the noise exposure level. It is a well-known fact that the survey results are not only dependent on the accumulated noise exposure, DNL, DENL, or similar, but also on various other factors such as maximum levels, exposure patterns, noise spectra, etc. A re-analysis of previously reported surveys shows that the results are also to a large extent dependent on survey-specific factors like wording of the annoyance questions, how the questionnaires are presented, response scales, methods of scoring highly annoyed, etc. This paper discusses and quantifies the influence of such factors and suggests ways of comparing results from surveys that have been conducted according to different protocols and different analysis methods.

Liver is structurally organized into zonation where LSECs endothelial cells play a crucial role during chronic liver injury and early stages of fibrosis. Fibrosis can be reversed if diagnosed early at molecular level in zonation before progressing to advanced stages like bridging fibrosis. This study identified zonation marker genes using scRNA-seq and spatial transcriptomics molecular profiling technologies in normal and diseased fibrotic human liver. DGE analysis is performed over LSECs and identified the top 20 expressed genes in periportal, perivenous, and intermediate acinar zones. Multi-omics and scRNA-seq analysis over Visium images and ECs liver cells figured out OIT3, DNASE1L3, CLEC4G, LYVE1, FCN2, CRHBP as commonly expressed mid-lobular zonation-specific genes. Also, this study detected STAB2, F8, AQP1, TEK, TIMP3, TIE1, CTSL genes as expressed in DILI and NASH ECs populations. The connection between LSECs marker genes in zone 2 and liver fibrosis holds significant promise for advancing our understanding in developing new therapeutic strategies for fibrosis reversal and designing computational molecular biomarkers in NASH and DILI fibrotic liver diseases.

Ion channels serve many cellular functions including ion homeostasis, volume regulation, signaling, nutrient acquisition, and developmental progression. Although the complex lifecycles of malaria parasites necessitate ion and solute flux across membranes, whole genome sequencing of the human pathogen, Plasmodium falciparum, revealed remarkably few orthologs of known ion channel genes. Contrasting with this, biochemical studies have implicated channel-mediated flux of ions and nutritive solutes across several membranes in infected erythrocytes. Here, I review advances in the cellular and molecular biology of ion channels in malaria parasites. These studies have implicated novel parasite genes in the formation of at least two ion channels, with additional ion channels likely present at various membranes and parasite stages. Computational approaches that rely on homology to known channel genes from higher organisms will not be very helpful in identifying the molecular determinants of these activities. Given their unusual properties, novel molecular and structural features, and essential roles in pathogen survival and development, parasite channels should be promising targets for therapy development.

Artificial intelligence (AI) agents are widely used in the retail and distribution industry, often in-corporating human-like elements such as possessing names and genders. This paper examines the influence of AI agent gender and brand concepts on trust and grounding within virtual brand spaces; exploring the correlation between user identification with AI agents and subsequent brand recommendations. The study revealed that in virtual brand spaces centered around a functional concept, male AI agents generated higher levels of trust than female AI agents, whereas, when focused on an experiential concept, female AI agents induced higher levels of grounding than male AI agents. Furthermore, this research indicates that the association between customers’ iden-tification with AI agents and recommendations for actual brand purchases is mediated by trust and grounding. These findings support the idea that users who strongly identify with AI agents are more inclined to recommend brand products after engaging in conversations within the virtu-al brand space.

The malaria parasite resides within erythrocytes during one stage of its life cycle. During this intraerythrocytic period, the parasite ingests the erythrocyte cytoplasm and digests approximately two-thirds of the host cell hemoglobin. This digestion occurs within a lysosome-like organelle called the digestive vacuole. Several proteases are localized to the digestive vacuole and these proteases sequentially breakdown hemoglobin into small peptides, dipeptides, and amino acids. The peptides are exported into the host cytoplasm via the chloroquine-resistance transporter and an amino acid transporter has also been identified on the digestive vacuole membrane. The environment of the digestive vacuole also provides appropriate conditions for the biocrystallization of toxic heme into non-toxic hemozoin by a poorly understood process. Hemozoin formation is an attribute of Plasmodium and Haemoproteus and is not exhibited by other intraerythrocytic protozoan parasites. The efficient degradation of hemoglobin and detoxification of heme likely plays a major role in the high level of replication exhibited by malaria parasites within erythrocytes. Unique features of the digestive vacuole and the critical importance of nutrient acquisition provide therapeutic targets for the treatment of malaria.

Based on recent interest and on the importance of the ongoing climate change catastrophe, this article provides the basics of global carbon cycle modelling as required for the assessment of the degree of carbon neutrality of biomass energy, and its underlying dynamics. It is aimed at clari-fying the question “Are biomass fuels carbon neutral?”. The "Combined Energy and Biosphere Model" (CEBM) computes annual carbon flows including growth and decay of plants on 2.52.5° grid elements of the continents’ surface and offers detailed results on the changes of after implementation of large-scale biomass energy strategies world-wide. The main (and possibly unexpected) effect is the long-term depletion of the soil organic compartment after extraction of biomass fuels. When comparing CEBM model runs using (i) biomass energy sources and (ii) carbon-free energy sources (such as solar or wind), it becomes quantitatively clear already on the theoretical level (i.e., even without taking into account effi-ciency losses) that biomass is only “half as carbon neutral” as ideally assumed, to express a rule of thumb – mainly because of soil carbon depletion. Still, biomass energy will play an important role when fighting global warming, even if efforts to lower energy demand are preferable as a fundamental strategy.

This study employs molecular docking simulations using Autodock Vina with the Pyrx program to investigate the binding interactions between Human prostate-specific antigen (PSA) and natural compounds, namely Amentoflavone, Ginketin, Rutin, and Hypericin. The evaluation reveals excellent binding energy values, averaging around -10 kcal/mol, suggesting robust and favorable interactions between the selected compounds and PSA. The results provide valuable insights into the potential therapeutic applications of these natural compounds in the context of prostate cancer treatment or management. Further experimental validation is warranted to confirm these findings and explore the viability of these compounds as promising candidates for innovative therapeutic strategies. This research contributes to the growing body of knowledge in the field of molecular docking and its applications in drug discovery and bioinformatics.

We delve into the axion-dilaton model within the supergravity framework, with a specific focus on the intricacies of domain wall construction and stability. Employing holographic vitrification, we unravel the dynamics of domain wall formation in gauge theories featuring periodic vacuum structures. Our model, incorporating a QCD-like axion term and a stabilizing dilaton, undergoes scrutiny for conductivity variations under weak disorder. The investigation reveals the model's resilience, manifesting near-perfect conductivity under mild disorder conditions. However, the rigorous mathematical motivation for the holographic setup demands further elucidation. The scattered nature of our results prompts the necessity for a more systematic interpretation of QCD phenomena and conductivity transitions. This study contributes to the mathematical understanding of the axion-dilaton model's behavior, highlighting the imperative for a refined holographic framework and a more coherent interpretation of observed phenomena.

This study explores the potential of natural compounds, including Daidzin, Luteolin, and Silibinin, as inhibitors of human monoamine oxidase B (MAO-B) for the treatment of Parkinson's disease. Docking simulations were performed using Autodock Vina with Pyrx program to evaluate the binding affinities of these compounds with MAO-B. Results indicate that Daidzin, Luteolin, and Silibinin exhibit promising binding affinities with MAO-B, with Daidzin demonstrating the highest affinity. Toxicity parameters were further predicted using the PkCSM Server, confirming the low toxicity of these compounds. Overall, the findings suggest that Daidzin, Luteolin, and Silibinin have the potential to be effective and safe treatments for Parkinson's disease through their inhibition of MAO-B. Further experimental validation is warranted to support their therapeutic efficacy in clinical settings.

In my paper, a divisibility rule named the Queen function is de- scribed, which has been generalized for every integer and encompasses all pre- viously established divisibility rules. Subsequently, the paper discusses other areas where this function is instrumental. These include simplifying ratios, generating prime numbers, and more. Towards the end of the paper, a set of hypotheses is also presented. Among these, the most significant is the novel approach involving the application of the Queen function for prime number generation.

Therapies targeting amyloid, such as monoclonal antibodies like Lecanemab, Aducanumab, and Donanemab, have garnered FDA approval but remain controversial due to limited clinical benefits and significant side effects against Alzheimer. The present theorical work utilized Virtual Screening and Docking techniques to explore potential small natural molecules' interactions with the KIBRA protein, a promising target for drug development. Kibra protein is considered a biomarker for synaptic dysfunction and cognitive decline. Employing Autodock Vina and Pyrx software, on several natural compounds and found Hypericin to exhibit the lowest binding energy of approximately -9 kcal/mol. Previous studies have highlighted Hypericin's strong affinity for Alzheimer's Disease-associated targets like ABAD and BACE1. These findings suggest Hypericin could be as a potential therapeutic agent for Alzheimer's Disease. Further research is warranted to validate its efficacy and safety for clinical use.

The study focused on Molecular Docking simulations using Autodock Vina in conjunction with the Pyrx program to investigate potential drugs and natural compounds against the Bcr-Abl oncoprotein. From initial virtual screening of 200 compounds, 11 potential candidates were selected for further evaluation. Additional investigations included toxicity prediction using the pKCSM server. Among the compounds, Diosmin and Hesperidin showed high maximum tolerated doses in humans and low toxicity. Conversely, only Eltrombopag among the selected drugs exhibited excellent parameters, albeit with a potential risk of liver damage at high dosages. These findings underscore the need for comprehensive evaluation of efficacy and safety in the development of potential treatments targeting the Bcr-Abl oncoprotein.

Cloud computing transformed IT organizations with its on-demand model, notably Infrastructure as a Service (IaaS). Cloud providers manage extensive physical devices, consuming substantial energy and bandwidth for data traffic during virtual machine deployment. Balancing energy and bandwidth are critical. This thesis presents BOHGOA integrated with ACO to optimize virtual machine placement in clouds, simultaneously considering bandwidth and energy. It yields Pareto-optimal solutions for this trade-off. Using CloudSim, BOHGOA outperformed GA, ACO, and FFD algorithms, reducing bandwidth consumption by 54.14%, 32.11%, 57.47% (240 VMs) and 38.12%, 22.76%, 47.05% (500 VMs) respectively. Additionally, it decreased physical machine energy usage by 37.70%, 34.01%, 40.14% (240 VMs) and 27.50%, 22.28%, 30.52% (500 VMs) respectively. These results underscore BOHGOA's effectiveness in optimizing cloud VM placement.

It is commonly recognized that a ship’s ability to maintain stability is dependent upon the way its loads are distributed. This means making sure the center of gravity is sufficiently low and evenly distributed. Yet when a ship encounters turbulent water with extremely large wave amplitudes, load distribution is a critical factor in determining how stressed the ship becomes. In particular, this article examines several methods for increasing the ship's longitudinal strength to prevent ship structural damage during hogging and sagging. This research presents a number of proposed techniques to enhance the longitudinal strength of cargo ships in order to guarantee minimal stress and deformation during sagging and hogging. The first method is the stern-to-bow use of curved support structures to increase the longitudinal strength of a cargo ship. And another way to stiffen the lateral plate is the proposed use of different designs of the side plate, such as wavy curves, stars, etc. To further boost the strength, the lateral plate upper part is suggested to curve upward. A numerical simulation using ANSYS of the stiffened plate when subjected to uniform load distribution and fixed support on either end shows that there is a decrease in deformation of the plate when we use wavy curved plates compared with those of the other plate stiffening methods used, and furthermore, curving the plate on top increases its strength during sagging as well as hogging. Finally, the use of a curved support structure further enhanced the overall longitudinal strength of the vessel.

Evolutionary algorithms find applicability in reinforcement learning of neural networks due to their independence from gradient-based methods. To achieve successful training of neural networks using evolutionary algorithms, careful considerations must be made to select appropriate algorithms due to the availability of various algorithmic variations. In Part1 and Part2, the author previously reported experimental evaluations on Genetic Algorithm and Evolution Strategy for reinforcement learning of neural networks, utilizing the Acrobot control task. This article constitutes Part3 of the series of comparative research. In this study, Differential Evolution is adopted as the third instance of major evolutionary algorithms. The experimental results show a statistically significant superiority of DE over both GA and ES (p < .01). In addition, DE exhibits its robustness to variations in hyperparameter configurations (the number of offsprings and generations). In the previous experiments, both ES and GA showed significant performance differences depending on the configurations, whereas in the experiment reported in this article, such differences are not detected for DE.

The normal ageing process significantly affects resistance arteries, leading to various biological and physiological consequences. Systolic hypertension is a common occurrence in ageing individuals, accompanied by increased large artery stiffening, heightened pulsatility, small artery remodeling, and damage to critical microvascular structures. Starting from young adulthood, there is a progressive elevation in mean arterial pressure, supported by clinical and epidemiological evidence as well as findings from animal models. The myogenic response, a protective mechanism for the microcirculation, may face disruptions during ageing. Dysregulation of calcium entry channels (T-type, L-type, TRP channels), dysfunction in intracellular calcium storage and extrusion mechanisms, altered expression of potassium channels, and a change in smooth muscle calcium sensitization may contribute to age-related dysregulation of myogenic tone. Flow-mediated vasodilatation, a hallmark of endothelial function, is compromised in ageing. This result of endothelial dysfunction is related to oxidative stress, lower nitric oxide bioavailability and a low-grade inflammatory response, further exacerbating vascular dysfunction. Resistance artery remodeling in ageing emerges as a hypertrophic response of the vessel wall, often seen in conjunction with outward remodeling (in normotension), but can also present as inward hypertrophic remodeling (in hypertension). The remodeling process involves oxidative stress, inflammation, reorganization of extracellular matrix fiber proteins and actin cytoskeletal components. Reactive oxygen species (ROS) signaling and chronic low-grade inflammation, often referred to as "inflammaging”, play substantial roles in age-related vascular dysfunction. Due to its role in regulation of vascular tone as well as structural proteins, the RhoA/Rho-kinase pathway becomes a new target in age-related vascular dysfunction and associated diseases. Understanding the intricate interplay of these factors is crucial for developing targeted interventions to mitigate the consequences of ageing on resistance arteries and enhance overall vascular health.

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses the relationship between stability and the Gaussian curvature, as well as the connections between queueing theory, information geometry, , Riemannian geometry, and the Theory of Relativity.

Transporting water from one side of a valley or gorge to the other requires construction of an aqueduct bridge or elevated aqueduct. These features are striking elements on cultural landscapes. Unlike previous research that emphasized architecture or design and relied on documentary sources and published works, this study focuses on details of construction and first-hand observation. Roman and Medieval elevated aqueducts in Spain were subjected to rigorous field examination. Marked variations were found to exist between structures of each age. No two aqueduct bridges are alike indicating the absence of standard designs. Locally available materials were used. Construction seems to have been overseen and carried out by individuals who possessed inconsistent degrees of skill. Roman treatises discussed aqueduct bridges, but not how to build them. Many palaces were clearly designed and built by highly skilled personnel during Medieval times, but more mundane public works projects such as aqueducts appear to have been carried out by less-skilled individuals. These findings have implications regarding the construction of elevated aqueducts by Spaniards in the Americas during the 16th century.

This study focused on the investigation of myeloperoxidase through a Molecular Docking approach with various natural compounds to identify potential substances for cardiovascular research. Recent research has linked elevated myeloperoxidase levels to the severity of coronary artery disease. The results of the docking analysis revealed Polydatin, Daidzin, Astringin, Ginkgetin, and Amentoflavone as promising compounds with excellent binding capacity. To complement this, toxicity prediction studies were conducted using pkCSM. Overall, all four investigated molecules (Amentoflavone, Daidzin, Ginkgetin, and Astringin) were found to be non-toxic, exhibiting high maximum tolerated doses (human) and favorable values for Oral Rat Acute Toxicity and Oral Rat Chronic Toxicity. Moreover, they showed non-AMES toxicity and non-hepatotoxicity. Astringin, in particular, stood out with the highest positive effects, including a high maximum tolerated dose (human) and favorable values for Oral Rat Chronic Toxicity, along with dual inhibition of hERG II and hERG I. These findings suggest the potential utility of these compounds in cardiovascular research with minimized unwanted effects.

Although there is a vast body of neuroscientific research on cognitive behavioral therapy (CBT), many therapists are confused about how to incorporate the evidence into their clinical practice. This narrative review translates neuroscientific research on CBT for depression into a therapist-friendly formulation model. Four brain networks that are particularly relevant to depression, including the Central Executive Network, Default mode Network, Salience Network, and Affective Network, were identified based on their interactions and described in relation to depressive symptoms. Additionally, it clarified how each CBT technique works on a brain map. Assessment, intervention selection, and patient psychoeducation based on this model will facilitate the clinical application of neuroscience in CBT.

The purpose of this study is to assess the solid waste management status and practice in Sendafa town, Oromia regional state residents. In order to achieve this goal, the researcher intends to employ both primary and secondary data from the Sendafa town municipality. With the aid of multi-cluster sampling and a purposive sampling method, the researchers chose a sample size of 398 people and 10 interview responders. To utilize a systematic sampling technique at intervals of residences, individual samples were chosen. Quantitative data was cleaned and analysed using STATA software. A multiple linear regression model and logistic regression other descriptive statistics methods were then used to change the results. The qualitative data were imported, coded, and thematised using ATLAS.ti.9 in order to prepare respondents' interviews for analysis. The findings indicate that residents' poor solid waste management practices are a result of a lack of awareness, low family income transportation issues, issues with waste collectors, a lack of a sense of responsibility and belonging, and a failure to enforce current solid waste management laws. Solid waste accumulates near roads, bridges, and residential areas that are close to landfills, contaminating the area and leading to diseases like TB and Asthma (and other related health issues in children and adults who live there). Thus, researcher recommends that to have sustainable solid waste management the town administrators should have plan to develop awareness creation symposium or panel of discussion, resolve transportation issues, monitor and guide the routine activities of waste collectors, develop sense of belongingness for themselves and for the community, develop integrated solid waste land fill projects and working with all stakeholders like NGO and health institution will minimize the adverse effect of improper solid waste management. Keywords: Solid Waste, Status of Solid Waste Management, Land fill site suitability

Feedback from the earthquake zone in Kahramanmaraş, Turkey has established that the emerging field of Crisis Translation and Interpreting (CTInt) requires a free smartphone application, to enable Crisis Translators and Interpreters (CTIs) to access multilingual terminology resources on-/offline when assisting Search and Rescue (SAR) teams responding to man-made and/or natural disasters.The aim is to design not only a multilingual compilation of Crisis Terminology (CTerm), downloadable to smartphones enabling access when there is a failure in the internet connection, but also a unified search tool which will browse and redirect the user to existing termbanks when the internet is accessible. Nevertheless, terminological records available in the domain of CTerm are inadequate and dispersed, with different interfaces and language combinations, requiring enhancement and harmonisation. Furthermore, automated translation and interpreting software/systems supported by the multilingual compilation of the crisis terminology portal (CTermPort) ideally need to be developed or, alternatively, existing ones integrated into the crisis termbank (CTermBank) collection for those who would lack the support of CTIs.The design of the CTermPort will significantly impact civil societies by providing a lifesaving tool for CTIs who need a reliable terminological reference point and automated translation options, and those unable to be assisted. In this respect, the project also promises strong prospects of sustainability past the project duration, as the tool to be developed will serve international SAR teams working closely with CInts during response times, but also medical staff in field hospitals collaborating with CTIs in rehabilitation and recovery phases, and beyond.

This paper provides a first-time ever unification of information theory, semi-group theory with the theory of uncertain reasoning, through functional perspective. Fundamentally, the threshold theorems for the inference functional were devised. Furthermore, numerical experiments are illustrated. The complex proofs in our paper are original results which emphasizes the credibility of the class of Rényi Generalized Entropies as measures of information, and that the field is open to extend an enhanced methodology regarding queuing networks with heavy tails.

The theories of Evolution and Big Bang have brought a major impact upon the scientific and societal perception upon the origins, abilities and roles of mankind on Earth. It is conclusively evident that Mother Nature and the physical realm is autonomous and all phenomena in the world occur without an imposition against the “free will” of such events and patterns. Nevertheless, this extent of freedom does not imply that life on Earth represents an accident and has no purpose. By careful analysis of ancient religious texts, it can be suggested even otherwise, that it is especially free will that is offered as a gift from outside of the physical dimensions of existence, with the purpose of a continuous edification and improvement of the overall life conditions and of the human perception. It may be that the multi-generational focus on improvement and progress have been misattributed as a long-term evolution of species, that humans came from animal ancestors and that there is a blurred line associating humans with animals. Furthermore, it may be that scientists based their suggestions that no outside Creator would have brought the Earth into existence on physical perspectives, when the extra-dimensional process of Creation implies that all elements of the physical existence undergo a process of Creation from the outside, where time, space and physical matter do not exist, in spite of such elements possibly reflecting unseen elements of the meta-physical world. Finally, there is the following example that deserves attention within the scientific community; just because all living cells - human, animal and plant - contain DNA chromosomes, ribosomes, mitochondria and a plasma membrane, it does not indicate that humans are animals, just as this does not indicate that plants are animals. In Science, there is a golden statement, that correlation does not imply causation. This example is in complete agreement with the verses of the Book of Genesis in the Holy Scriptures regarding the origins of life; namely, that animals could have been created by an Author of all life on Earth so that man would experience companionship. Another major accordance with the teachings of the Holy Scriptures is the fact that life emerged from the water, and not from the soil, although the soil constituted the second principal means of the commencement and extension of life. Namely, after life first emerged in the seas and the oceans from bacteria, a few bacteria were passed from the marine water into the nearby soil on islands and surrounding land through the circulatory air above the sea level. Afterward, the first life forms emerged from the soil, via the transferred bacteria. Eastern Orthodox Christianity regards water as the principal environment of both physical and spiritual birth. Overall, an improved scientific perception of the timeline of life on Earth may be reached via an approach that combines molecular biology with quantum physics, given that the three layers of Science - Biology, Chemistry and Physics - together with their foundational layer of Mathematics, are in fact situated in a relationship of complete harmony.

We show that one of the two important uncertainty principles derived by Maccone and Pati \textit{[Phys. Rev. Lett., 2014]} can be derived for arbitrary maps defined on subsets of $\mathcal{L}^p$ spaces for $1< p<\infty$. Our main tool is the Clarkson inequalities. We also derive a nonlinear uncertainty principle for weak parallelogram spaces and Type-p Banach spaces.

Based on a very fast numerical procedure for the determination of the subsurface stress field beneath frictional contacts of axisymmetric elastic bodies under arbitrary 2D oblique loading, the contact mechanical influences of loading parameters and contact profile geometry on the Smith-Watson-Topper (SWT) fatigue crack initiation parameter in elastic fretting contacts with superimposed normal and tangential oscillations are studied in detail. The efficiency of the stress calculation allows for a comprehensive physical analysis of the multi-dimensional parameter space of influencing variables. It is found that a superimposed normal oscillation of the contact can significantly increase or decrease the SWT parameter, depending on the initial phase difference and frequency ratio between the normal and tangential oscillation. Written in proper non-dimensional variables, the rounded flat punch always exhibits smaller values of the SWT parameter, compared to a full paraboloid with the same curvature, while the truncated paraboloid exhibits larger values. A small superimposed profile waviness also significantly increased or decreased the SWT parameter, depending on the amplitude and wave length of the waviness. While both the load protocol and the profile geometry can significantly alter the SWT parameter, the coupling between both influencing factors is weak.

The catalytic parameters describing enzyme catalysis are discussed in the context of the design of de novo enzymes. It is shown that high values of the catalytic efficiency may in some cases reflect tight substrate binding and lead to an immediate levelling-off of rates to reach a low plateau, an undesirable scenario for many industrial applications. It is argued that increasing the catalytic rate constant should be a main target in de novo enzyme engineering.