Remote sensing technologies may play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and to quantify the land-use changes in open-cast mines in the Carajás region situated in the eastern Amazon. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and Ikonos), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, and the NDVI and NDWI indices and LiDAR digital ground and slope models. The overall accuracy was higher than 90%, and the Kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded; for that, canga and forest vegetation was converted to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

The production of biodiesel through transesterification routes generates large amounts of glycerol, approximately 10 m3 for every 90 m3 of the biodiesel produced. Taking into account this scenario, the valorization of glycerol using chemical routes that could be operated in biodiesel industry constitutes a promising approach to achieve added-value products. An interesting option is the production of ethers, which can be used as fuel additives in diesel engines to improve the combustion efficiency, reducing soot emission and increasing cetane index. In this study, a purification route was applied to crude glycerol and its valorization by etherification was evaluated. The glycerol contents of purified samples were above 98% wt. The purified and commercial glycerol was used to obtain ethers. Etherification reactions were carried out with different alcohols (ethanol, isopropanol and 3-methyl-1-butanol) into a batch reactor, using small amount of Amberlyst 15 as a catalyst, at autogenous pressure and solvent-free conditions. The glycerol conversion, selectivity and yield to ethers were evaluated. A glycerol conversion of 97% wt. with selectivity of 80% to monoether was obtained when using ethanol. For isopropanol, the glycerol conversion was up to 95% (76% of monoether and 22% of diether). However, the selectivity to ethers for 3-methyl-1-butanol was negligible (<3% wt.). A process simulation for purification and etherification steps integrated with a biodiesel production was assessed in terms of productivity and energy consumption, considering different scenarios of glycerol/alcohol molar ratios.

Background and Objectives: Wilson disease (WD) is a disorder of copper metabolism caused by genetic muta-tions in the ATP7B gene which lead to the accumulation of copper in the body. The aim of the present study is to investigate the severity of WD in patients in Romania. Materials and Methods: This study was conducted us-ing an online questionnaire consisting of 32 questions in a group of patients suffering from Wilson disease. Results: The study included 67 people aged 7 to 56 with WD. The most common symptoms of the participants were hepatic and neurological in 22 cases (32.8%). The most common neurological symptom in the assessed cases was muscle stiffness (49.5%), followed by tremor (45%), and speech disorders (40.5%). The Kay-ser-Fleischer ring was present in 50.7% of the participants. The most commonly used drug treatment in the participants was D-penicillamine (77.61%). Conclusions: The severity of WD is based on many aspects, the most important being early diagnosis and access to treatment throughout the year. The prognosis is favorable with early diagnosis and treatment, but it is crucial to diagnose individuals before they develop major symp-toms. Therefore, advances in WD screening can lead to an earlier diagnosis and better results.

Keywords: Lightning; Land Cover and Land Use; Topographic Effects, Itacaiúnas River Hydrographic Basin

Sado island in Niigata prefecture is among the first GIAHS designated sites in Japan and among developed countries worldwide. Recent studies have pointed out the need to incorporate culture and farmer opinions to further strengthen GIAHS inclusivity in rural farming. In connection to this, the study explored whether farmer visibility, which is highlighted by GIAHS designation, actually translates to farmers’ actual perception of GIAHS involvement. A survey was conducted among Sado island farmers to determine their knowledge and perception of their GIAHS involvement, in connection to their perspectives on youth involvement, Sado island branding, and tourism management. Results showed that 56.3% of Sado island farmers feel uninvolved or unsure towards GIAHS, which is in stark contrast with the prevalent farming method in the area which is special farming (complies with GIAHS regulations). Further analyses revealed that farmers who feel that GIAHS does not promote youth involvement, Sado island branding, and tourism management have higher predisposition to perceive themselves as uninvolved towards GIAHS. This study highlights the need for careful reevaluation and integration of farmer insights and needs to the current GIAHS implementation in Sado island and in other GIAHS as well.

Sado Island in Niigata prefecture, Japan is one of the first Globally Important Agricultural Heritage Systems (GIAHS) among developed countries and has since been involved in environmental conservation agriculture (ECA). While ECA is still in its early stage in Japan, it has proven to be effective in mitigating climate change in the agricultural sector; hence, this study analyzed the factors which could contribute to the ECA continuation among Sado Island farmers. The data revealed the prevalence of farmers’ cognitive dissonance between ECA and its mitigating effects on climate change. Exploratory factor analysis and ordinal regression confirmed the importance of perceived GIAHS involvement in the continuation of ECA. In addition, other identified factors affecting ECA continuation fall either on a macro-level (i.e., farmers’ awareness of their role in improving their environment) or micro-level (i.e., farmers’ differing farm optimizations). These perspectives highlighted the altruistic nature of the Sado Island ECA farmers by valuing the improvement of their local and global environment as their main reason to continue ECA, whereas their various farm management optimizations support this observed farmer altruism by providing avenues to increase yield with only a moderate paddy land area. This study thereby highlights the need to continuously develop sustainable strategies to maintain and improve a positive farmer mindset towards ECA.

Bioenergetics, genetic coding, and catalysis are all difficult to imagine emerging without pre-existing historical context. That context is often posed as a “Chicken and Egg” problem; its resolution is concisely described by de Grasse Tyson: “the egg was laid by a bird that was not a chicken”. The concision and generality of that answer furnish no details—only an appropriate framework from which to examine detailed paradigms that might illuminate paradoxes underlying these three life-defining biomolecular processes. We examine experimental aspects here of five examples that all conform to the same paradigm. The paradox in each example is resolved by coupling if, and only if, conditions for two related transitions between levels. One drives, and each restricts fluxes through, or “gates” the other. That reciprocally-coupled gating, in which two gated processes constrain one another, maps onto the formal structure of “strange loops”. That mapping may help unite the axiomatic foundations of genetics, bioenergetics, and catalysis. As a physical analog for Gödel’s logic, biomolecular strange-loops provide a natural metaphor around which to organize these data, linking biology to the physics of information, free energy, and the second law of thermodynamics.

This report presents a framework for analysing the risk of alien taxa under South Africa's National Environmental Management: Biodiversity Act of 2004, and the Alien and Invasive Species Regulations of 2014. While the report was initially designed to meet a specific South Africa need, the risk analysis processes developed can, we believe, be transferred to any specified geographic region. In outlining a series of questions related to a taxon’s likelihood of invasion and the consequences thereof, i.e. the potential impacts, the report provides a structure for collating data relevant to the process of listing taxa as well as a process for developing recommendations that is both mathematically sound, transparent, and that explicitly takes uncertainty into account. The framework is based on collating information according to international standards in biological invasions (specifically the IUCN Environmental Impact Classification of Alien Taxa Scheme, the CBD's scheme for classifying invasion pathways, and the Unified Framework for Biological Invasions proposed by Blackburn et al. 2011). The risk analysis framework is currently being implemented in South Africa in an effort to underpin national regulatory lists of invasive species.

Objective: Physical inactivity is linked to chronic illnesses and disabilities among workers, especially those in high demanding jobs like teachers. Despite the global prominence of sedentary behaviour research, studies drawing the relationships between physical inactivity and multimorbidity among working teacher populations in low-and middle-countries remain untapped. This study assessed the sedentariness and health status of primary school teachers in Cape Coast Metropolis in Ghana. Method: This cross-sectional survey employed 1109 primary school teachers from the Cape Coast Metropolis in the Central Region of Ghana, using convenient sampling method. Results: Generally, the teachers were highly sedentary and reported poor health status. Other results showed no difference in sedentariness across gender, t (1107) = -0.32, p > .05. However, female teachers suffer more pain and discomfort, [t (1103.51) = - 3.07, p < .05, anxiety and depression, [t (1099.56) = - 2.85, p < .000,)], and poor health status [t (1107) = 2.14, p < .05, than their male counterparts. Also, pain and discomfort, anxiety and depression, health status and years of work significantly predicted sedentariness among the teachers, F (4, 1104) = 5.966, p=.00, R = .145, R2 = .029, adjusted R2 = .018. Conclusion: The findings suggest that individualized or personalized interventions are urgently needed to promote regular physical activity to improve the health status and reduce associated complications on the health and well-being, especially among the female primary school teachers. Given the health risks of sedentary lifestyle, behavioral interventions at the person-level (i.e., individualized- routine weekly physical activity programmes) and built environmental restructuring (e.g., creation of walkways to encourage regular walking) could be done to physical activity behavior among teachers within the Cape Coast Metropolis, and perhaps beyond.

This article is about a framework for determining the degree of realism of any given 1 passenger ride motion discomfort measurement formula. After providing some context and reviewing 2 evidence of deficiency in currently popular ride motion discomfort measurement formulas, the article 3 outlines the research program that needs to be carried out in order to establish such a framework. 4 The research begins with gathering recordings of uncomfortable ride motion episodes encountered in 5 a chosen type of passenger transport service. It then has test subjects compare the episodes via a ride 6 motion simulator and adjust their amplitudes pair wise until they cause equal discomfort. It explains 7 how to take the pair wise amplitude adjustments and determine amplitude adjustments that bring all 8 of the motion episode recordings to a common level of discomfort so that they form a normalized set. 9 Then, the lower the scatter of the scores assigned by any given discomfort measurement formula to 10 the members of that set, the more realistic that formula will be for the chosen service.

The description of the electron-electron interactions in two-dimensional materials has a dimensional mismatch, where electrons live in (2+1)D while photons propagate in (3+1)D. In order to define an action in (2+1)D, one may perform a dimensional reduction of quantum electrodynamics in (3+1)D (QED4) into Pseudo quantum electrodynamics (PQED). The main difference between this model and QED4 is the presence of a pseudo-differential operator in the Maxwell term. However, besides the Coulomb repulsion, electrons in a material are subjected to several microscopic interactions, which are inherent in a many-body system. These are expected to reduce the range of the Coulomb potential, leading to a short-range interaction. Here, we consider the coupling to a scalar field in PQED for explaining such mechanism, which resembles the spontanoues symmetry breaking (SSB) in Abelian gauge theories. In order to do so, we consider two cases: (i) By coupling the gauge field to a Higgs field in scalar quantum electrodynamics in (3+1)D and, thereafter, performing the dimensional reduction and; (ii) By coupling a Higgs field to the gauge field in PQED and subsequently calculating its effective potential. In case (i), we obtain a model describing electrons interacting through the Yukawa potential and, in case (ii), we show that SSB does not occur at one-loop approximation. The relevance of the model for describing electronic interactions in two-dimensional materials is also adressed.

Upland lakes (ULs) of the Carajás, southeastern Amazonia, have been intensively studied to their evolution during the Quaternary, as well as the development of the associated biota. In this review, several classical and modern approaches from structural geology to the pollen rain and sedimentary data which cover an area of around 41,300 km² were compiled. Multi-elemental geochemistry indicates that the detrital sediments derived from weathered crusts and soils, while the sedimentary organic matter represent autochthonous (siliceous sponge spicules, algae, macrophytes) and allochthonous (C3 plants and freshwater DOC) sources. Modern pollen rain suggests that even small lakes and canga areas can reflect forest signal, which depends on the topographic control and prevailing wind direction on pollen deposition. Integrated data of the sedimentary cores indicate that the active lakes never dried up during the last 50 ka cal BP. However, subaerial exposure occurs on filled lakes such as ST02 Lake during the LGM, LB3 and R2 lakes at the mid-Holocene due to drier paleoclimate conditions. Considering the organic proxies, only LB3 Lake presents expansion of C4 canga (montane savanna) plants since ULs of the Serra da Bocaína does not present siderites. Siderite formation on ULs deposits also points to drier paleoenviromental conditions, interrupting predominantly wet conditions. However, there is no evidence for widespread expansion of savanna into Southeastern Amazonia during the late Pleistocene and Holocene.

A Brewer Spent Grain (BSG), the most abundant by-product of the brewing process, is mainly used in animal feed and biogas production. The aim of the present work is BSG valorization by yeast fermentation to produce carotenoids. R. mucilaginosa CBS316 was cultured on BSG syrups, supplemented or not with YE and PEP (s-Fsa and Fsa). The biomass and carotenoid production were optimized in flasks and then scaled-up in bioreactor. In flask tests, the maximum biomass concentration was 5.3 and 6.2 g/L for Fsa and s-Fsa cultures, respectively. The maximum carotenoid production was 833 μg/L in Fsa and 1159 μg/L in s-FSA. Considering that the highest specific productivity value (P 7.16 μg/g*h) was obtained with Fsa syrup, this medium was selected for the process scale-up. In bioreactor tests, the maximum concentrations of biomass (4.29 g/L) and carotenoid (396 ug/L) was reached at 72 hours of fer-mentation, 24 h later than in flask. The total carotenoid produced was 524 and 150 ug in bioreactor and flask cultures, respectively. The carotenoids production by R. mucilaginosa was obtained both in Fsa and s-Fsa syrups. The results confirm the possibility to use the syrup as it is, Fsa, thus limiting the process costs.

For the better part of a century researchers across disciplines have sought to explain the crystallography of the elemental transition metals: hexagonal close packed, body centered cubic, and face centered cubic in a form similar to that used to rationalize the structure of organic molecules and inorganic complexes. Pauling himself tried with limited success to address the origins of transition metal stability. These early investigators were handicapped, however, by incomplete knowledge regarding the structure of metallic charge density. Here we exploit modern approaches to charge analysis to first comprehensively describe transition metal charge density. Then, we use topological partitioning and quantum mechanically rigorous treatments of kinetic energy to account for the structure of the density as arising from the interactions between metallic tetrahedra. We argue that the crystallography of the early transition metals results from charge transfer from the so called “octahedral” to “tetrahedral holes” while the face centered cubic structure of the late transition metals is a consequence of antibonding interactions that increase octahedral hole kinetic energy.

Polymerase chain reaction (PCR) technique is one of the molecular methods in amplifying DNA for the detection of malaria. However, the limitations of PCR especially when used for routine clinical practice can hamper its sensitivity and specificity. With that, this study focuses on designing a microfluidic device that will mimic the function of a conventional genus-specific PCR based on 18S rRNA gene to detect malaria parasites (Plasmodium falciparum) at low grade parasitemia. The design was drawn and simulated using ANSYS 14.5 Computational Fluid Dynamics (CFD). The simulation shows that adding loops to the design increases its relative deviation but to a minimal extent as compared to having only a straight path design, which indicates that looping is acceptable in designing a microfluidic device to minimize chip length. Also, increasing the cross-sectional area of the fluid path decreases the efficiency of the design, thus, the design with a relatively smaller cross-sectional area is favored. And lastly, among the three materials utilized, the chip made of polypropylene is the most efficient with a relative deviation of 0.94 as compared to polycarbonate and polydimethylsiloxane which have relative deviations of 2.78 and 1.92, respectively.

The present study aimed to investigate influence of genotypic differences to zinc and iron agronomic biofortification responses among yield of finger millet. A field experiment was conducted over two seasons in farmers’ fields in Ethiopia (2019, 2020). The experimental design had 15 treatment combinations comprising 3 finger millet varieties and application of different combinations of zinc and iron mineral fertilizers. 5 soil-applied fertilizer treatments (20 kg h-1 FeSO4 + 25 kg h-1 ZnSO4 + NPKS, 25 kg h-1 ZnSO4 + NPKS, 20 kg h-1 FeSO4 + NPKS, NPKS, and 30% NPKS), at 2 locations (Gojjam and Arsi Negelle, Ethiopia), and two 2 slope positions (Foot and hill), replicated four times in a randomized complete block design. Grain yield and biomass were evaluated on plot basis. Plant height, total and productive tiller number, finger length of the longest spike and number of fingers per main ear were measured at maturity stage. The combined soil application of FeSO47H2O and ZnSO47H2O increased yield to Meba variety by 51.6%. Also, ZnSO47H2O fertilizer application increased yield to Urji variety by 27.6%. About 18.3% of yield enhancement of Diga-01 variety was achieved due to the FeSO47H2O fertilizers application. The findings of the present study suggests that the influence of Zn and Fe agronomic biofortification on yield of finger millet could be affected by genotype differences and environmental conditions.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

Castor oil may be differentiated from other non-edible vegetable oils because of its main composition of hydroxylated fatty acids. Ricinoleic acid comprises 80–90% wt. of fatty acids in castor oil (Ricinus communis). In this study, the thermo-oxidative stability and tribological behavior of bio-based lubricant samples synthesized from castor oil using isoamyl alcohol were evaluated. Initially, the compositional and physicochemical properties of the obtained samples were assessed using 1H NMR, FTIR, and ASTM methods. Oxidative stability of the samples was evaluated using Rancimat method at 110 °C under air flow. The final biolubricant sample (BL2), obtained after esterification, epoxidation, and oxirane rings opening reactions, presented an oxidation stability time (OST) of 14.3 h. The thermal stability was also evaluated by thermogravimetry (TG) from the mass variations under inert and oxidative atmosphere. BL2 showed higher thermal stability compared to the other samples, demonstrating higher decomposition temperatures in both inert (339.04 °C) and oxidative (338.47 °C) atmospheres, for a mass loss of 50%. The tribological properties of the samples were evaluated using a four-ball tribometer configuration. The BL1 and BL2 samples exhibited lower friction coefficients than the mineral oil sample (MOS) by 21.5% and 43.1%, respectively. Regarding wear, the observed wear scar diameter (WSD) was also lower in BL1 and BL2 compared to MOS by 5.2% and 40.4%, respectively. The results of the tribological evaluation suggest that both samples obtained in this study have promising potential for applications in lubricating machines and mechanical systems.

Background: Elevated respiratory rates (RR) have been described in several disease states, such as pneumonia, asthma and bronchiolitis. Despite this, there are few studies defining the range of RR found in healthy children. Available age percentiles for RR have been generated using methods that have the potential themselves to alter the rate. Aim: The aim of this study was to develop accurate percentile charts of RR specific for age in healthy children for potential use in pre-hospital care (first-aid), clinical medicine and for reference in respiratory research. Method: A newly developed optical respiratory sensor was used to measure RR which placed no restrictions on respiratory excursion. This technique enabled recording in awake children without the artefact of the observer’s presence on the subject’s RR. A cross-sectional sample of healthy children was obtained from maternity wards, childcare centres and schools in Brisbane, Queensland, Australia. Results: RR were observed in 560 awake and 103 sleeping children of which data from 343 awake and 94 sleeping children was used to create reference ranges for healthy children from newborn to 13 years of age. The recorded rates were significantly higher when children were awake compared to asleep. During quiet sleep, RR decreased from 40 (interquartile range 7) bpm at one month to 20 (interquartile range 3) in children aged 3 years. In awake children, RR ranged from a median of 40 bpm (interquartile range 18) at 1 year to 12 bpm (interquartile range 11) at 13 years respectively. Conclusion: The optical sensor was found to be an appropriate respiratory transducer, capable of measuring RR and reducing artefact by the subjective responses of alert children. The centile charts will be helpful as an aid to detecting abnormal RR in children and will contribute to further systematic reviews related to this vital sign.

The Rev. Martin Luther King Jr. and Nelson Mandela were two of the world's most iconic civil (political) (human) rights advocates and leaders of all time. Both advocated for, and to varying degrees, applied elements of peaceful protests to the achievement of their goals. Both spent time in jail, often concurrently, but eventually forced their respective countries to extend the same rights that white populations had denied Africans and African Americans. For the US, civil rights, voting rights, right to education, housing and housing loans suggested that equality had been achieved, capped in South Africa by the election of Nelson Mandela as the first majority-rule president, and in the US, by Barack Obama’s election to the presidency. Yet the historical over-policing, police mistreatment and more generally, the judicial system’s inordinate ‘targeting’ of African Americans, with egregious cases running from Emmett Till to Rodney King to Walter Scott to Breonna Taylor to George Floyd to Rayshard Brooks and thousands of others shows the danger of such magical thinking. The now-persistent global wave pursuing human rights, civil rights and the right to be treated equally, primarily driven by the loosely-organized Black Lives Matter (BLM) movement, has become the leading voice in pursuit of equality. Riots such as those in LA, protests in Ferguson and everywhere in summer 2020 has ushered new civil rights campaign. In the US and elsewhere, it has morphed to include historical issues such as monuments to colonialism, the US civil war, slavery and slave owners and traders, institutions, companies and people whose wealth and existence has links to slavery. Instructively, the protests persisted even as COVID-19, the hundred-year plague, continues to ravage the world. Lost in the moment is the absence of central leadership and leaders such as MLK or Mandela. Their charisma and effectiveness has been lacking for 50 years. This paper evaluates whether this has led to inconsistent civil and human rights pursuit for equality, or whether perchance, Mandela and MLK were extraordinary, once-in-a-lifetime transformative leaders uniquely selected by history for their time.

Adenine and thymine homopolymer strings of at least 8 nucleotides (AT 8+mers) were characterized in Salmonella entericasubspecies I. The motif differed between cother taxonomic classes but not between Salmonella enterica serovars. The motif in plasmids was associated with serovar. Approximately 12.3% of the S. enterica motif loci had mutations. Mutability of AT 8+mers suggests that genomes undergo frequent repair to maintain optimal gene content, and that the motif facilitates self-recognition; in addition, serovar diversity is associated with plasmid content. A theory that genome regeneration accounts for both persistence of predominant Salmonella serovars and serovar diversity provides a new framework for investigating root causes of foodborne illness.

Nine crossbred finishing barrows randomly assigned to 3 dietary treatments were used to investigate the effects of dietary lysine on muscle growth related metabolic and signaling pathways. Muscle samples were collected from the longissimus dorsi of individual pigs after feeding the lysine-deficient, lysine-adequate, or lysine-excess diet for 5 weeks, and the total RNA was extracted afterwards. Affymetrix Porcine Gene 1.0 ST Array was used to quantify the expression levels of 19,211 genes. A total of 674 transcripts were differentially expressed (P ≤ 0.05); 60 out of 131 transcripts (P ≤ 0.01) were annotated in the NetAffx database. Ingenuity pathway analysis showed that dietary lysine deficiency may lead to (1) increased muscle protein degradation via the ubiquitination pathway as indicated by the up-regulated DNAJA1, HSP90AB1 and UBE2B mRNA, (2) reduced muscle protein synthesis via the up-regulated RND3 and ZIC1 mRNA, (3) increased serine and glycine synthesis via the up-regulated PHGDH and PSPH mRNA, and (4) increased lipid accumulation via the up-regulated ME1, SCD, and CIDEC mRNA. Dietary lysine excess may lead to (1) decreased muscle protein degradation via the down-regulated DNAJA1, HSP90AA1, HSPH1, and UBE2D3 mRNA, and (2) reduced lipid biosynthesis via the down-regulated CFD and ME1 mRNA.

Loss-of-function mutations of the spermine synthase gene (SMS) result in Snyder-Robinson Syndrome (SRS), a recessive X-linked syndrome characterized by intellectual disability, osteoporosis, hypotonia, speech abnormalities, kyphoscoliosis, and seizures. As SMS catalyzes the biosynthesis of the polyamine spermine from its precursor spermidine, SMS deficiency causes a lack of spermine with an accumulation of spermidine. As polyamines, spermine and spermidine play essential cellular roles that require tight homeostatic control to ensure normal cell growth, differentiation, and survival. Using patient-derived lymphoblast cell lines, we sought to comprehensively investigate the effects of SMS deficiency on polyamine homeostatic mechanisms including polyamine biosynthetic and catabolic enzymes, derivatives of the natural polyamines, and polyamine transport activity. In addition to decreased spermine and increased spermidine in SRS cells, ornithine decarboxylase activity and its product putrescine were significantly decreased. Treatment of SRS cells with exogenous spermine revealed that polyamine transport was active, as the cells accumulated spermine, decreased their spermidine level, and established a spermidine-to-spermine ratio within the range of wild type cells. SRS cells also demonstrated elevated levels of tissue transglutaminase, a change associated with certain neurodegenerative diseases. These studies form a basis for further investigations into the leading biochemical changes and properties of SMS-mutant cells that potentially represent therapeutic targets for the treatment of Snyder-Robinson Syndrome.

In this paper, we classify the function space of all real-valued functions on R denoted as F(R,R) into 28 distinct blocks. Each block contains elements that share common features in terms of the cardinality of their sets of continuity and differentiability. Alongside this classification, we introduce the concept of the Connection, which reveals a special relationship structure between four well-known real-valued functions in real analysis: the Cantor function, Dirichlet function, the Thomae function, and the Weierstrass function. Despite the significance of this field, several perspectives remain unexplored.

Since its introduction, the Triangulation number has been the most successful and ubiquitous scheme for classifying spherical viruses. However, despite its many successes, it fails to describe the relative angular orientations of proteins, as well as their radial mass distribution within the capsid. It also fails to provide any insight into critical sites of stability, modifications or possible mutations. We show how classifying spherical viruses using icosahedral point arrays, introduced by Keef and Twarock, unveils new geometric rules and constraints for understanding virus stability and key locations for exterior and interior modifications. We present a modified fitness measure which classifies viruses in an unambiguous and rigorous manner, irrespective of local surface chemistry, steric hinderance, solvent accessibility or triangulation number. We then utilize these point arrays to explain the immutable surface loops of bacteriophage MS2, the relative reactivity of surface lysines in CPMV and the non-quasiequivalent flexibility of the HBV dimers. We explain how using sister and double point arrays can function as predictive tools for site directed modifications in other systems. This success builds on our previous work showing that viruses place their protruding features along the great circles of the asymmetric unit, demonstrating that viruses indeed adhere to these geometric constraints.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

To assess the efficacy of washing cloth masks, we simulated SARS-CoV-2 contamination in tricoline fabric and tested decontaminants to reduce viral particles. Viral suspensions using two variants (B.1.1.28 and P.1) were inoculated in these fabrics, and the inactivation kinetics were evaluated after washing with various household disinfection products (Soap powder, Lysoform®, Hypochlorite sodium and 70% Alcohol), rinse numbers, and exposure times. Afterward, the fabrics were washed in sterile water, viral RNA extracted and amplified using RT-qPCR. Finally, viral replication in cell cultures was examined. Our findings show that all biocidal treatments successfully disinfected the tissue tested. Some products showed less reduction in viral loads, Soap powder (1.60 x 104, 1.04 x 103), Soap powder and Lysoform® (1.60 x 104, 1.04 x 103) and Alcohol 70% (1.02 x 103, 5.91 x 101) respectively. However, when sodium hypochlorite was used, this reduction was significantly increased (viral inactivation in 100% of the washes). After the first wash, the reduction of viral particles was greater for the P.1 variant than for the B.1.1.28 variant (W = 51759, p 0.05). In conclusion the sodium hypochlorite role on cloth masks disinfection may also have implications for future health emergencies as well as recommended by WHO.

Equilibrium climate sensitivity (ECS) is the change in global mean temperature expected to result from doubling atmospheric CO2 concentration from pre-industrial levels. Extensive research during the past 40 years has not reduced the uncertainty associated with ECS. Sherwood et al. [1] applied Bayesian statistics to evidence from climate-process physics, historical observations and earlier proxies to reduce the range of ECS from 1.5 – 4.5 K to 2.6 – 4.1 K. This paper examines their methods and many of the assumptions they made. It also evaluates two additional periods in the Holocene to show that factors other than CO2 drove recent climate change. It identifies potential systematic errors resulting from adding non-equilibrium short-term adjustments to the radiative forcing of greenhouse gases and from underestimating the effects of solar irradiance, ocean currents and aerosols. These factors have resulted in estimates of the forcing by CO2 that far exceed the apparent effects in paleoclimate data.

This note applies the Logistic model approximation to determine the suitable start and end dates for the observed epidemic curves in the total number of cases for different countries. The Logistic model is presented and explicit relations for the beginning and end dates are obtained together with the total epidemic duration. Using data from Brazil, Germany, Italy, and South Korea, the extreme dates are calculated. Since the epidemic onset time is found, a fair comparison of the epidemic curve for these countries is obtained. The result does not depend on the poor statistics available in the early phase of the epidemic when the initial number of infectives is unknown. In fact, the total duration depends only on the characteristic time parameter of the LM model.

Plants have developed unique mechanisms to cope with the harsh environmental conditions to compensate for their lack of mobility. A key part of their coping mechanisms is the synthesis of secondary metabolites. In addition to their role in plants’ defense against pathogens, they also possess therapeutic properties against diseases, and their use by humans predates written history. Viruses are a unique class of submicroscopic agents, incapable of independent existence outside a living host. Pathogenic viruses continue to pose a significant threat on global health, leading to unprecedented fatalities on a yearly basis. The use of medicinal plants as a natural source for an-tiviral agents has been widely reported in literature in the past decades. Metabolomics is a powerful research tool for the identification of plant metabolites with antiviral potentials and can be used to isolate compounds with antiviral activities in plants and study the biosynthetic pathways involved in viral disease progression. This review discusses the use of medicinal plants as antiviral agents, with a special focus on the metabolomics evidence supporting their efficacy. Additionally, suggestions are made for the optimization of various metabolomics methods for characterizing the bio-active compounds in plants and subsequent understanding of the mechanism of their operation.

: Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America, and to enhance the utility of drought monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impacts information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and the colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and the warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and indicators are changing over time as the climate warms, and by recommending ways to strengthen the use of indices and indicators in drought decision-making.

The second external cause of death from unintentional injuries is falls in people over 60, a worldwide public health problem. Associated factors are identified early in Primary Health Care. Thus, we analyze professional narratives about older adults/old age and the organization of services in the presence of fall-inducing frailty. A structured narrative was applied under the following stages: understanding the context; setting/plot/character analysis; and interpretive synthesis. Data were collected from August to November 2022, distributing 21 health professionals in three Narrative Focus Groups. In the analyses, the collective conceptions dialogued with Bourdieu’s Epistemology of field, habitus, and capital. Among the results, technical and common sense representations of older adults were simultaneously observed, along with the belief of old age as a problematic life stage. Care is centered on the installed disease/ailment. Encouraging autonomy and self-care emerges in integrative health practices, which older adults underestimate. Professionals access the lives of older adults according to their habitus, which, in turn, is structured (structuring) in the disputes for installed capital. Thus, the care provided disregards subjectivities and symbolic systems associated with falls.

This work presents significant results obtained by the application of global optimization techniques to the design of finite, normal form games with mixed strategies. To that end, the Fuzzy ASA global optimization method is applied to several design examples of strategic games, demonstrating its effectiveness in obtaining payoff functions whose corresponding games present a previously established Nash equilibrium. In other words, the game designer becomes able to choose a convenient Nash equilibrium for a generic finite state strategic game and the proposed method computes payoff functions that will realize the desired equilibrium, making it possible for the players to reach the favorable conditions represented by the chosen equilibrium. Considering that game theory is a very significant approach for modeling interactions between competing agents, and Nash equilibrium represents a powerful solution concept, portraying situations in which joint strategies are optimal in the sense that players cannot benefit from individually modifying their current strategies provided that other players do not change their strategies as well, it is natural to infer that the proposed method may be very useful for strategists in general. In summary, it is a genuine instance of artificial inference of payoff functions after a process of global machine learning, applied to their numerical components.

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data is for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. It is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial-mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, and response to hypoxia via HIF1A targets (↑in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

In recent years, news media has been greatly disrupted by the potential of technologically driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has demonstrated the different approaches that can be achieved using AI. We analyzed the news industry’s AI adoption based on the seven subfields of AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being developed more in the news media: machine learning, computer vision, as well as planning, scheduling, and optimization. Other areas have not been fully deployed in the journalistic field. Most AI news projects rely on funds from tech companies such as Google. This limits AI’s potential to a small number of players in the news industry. We make conclusions by providing examples of how these subfields are being developed in journalism and present an agenda for future research.

Background: SARS-CoV-2 continues to impact human health globally, with airborne transmission being a significant mode for transmission. In addition to tools like vaccination and testing, counter-measures that reduce viral spread in indoor settings are critical. This study aims to assess the efficacy of UV-C light, utilizing the Violett sterilization device, as a countermeasure against airborne transmission of SARS-CoV-2 in the highly susceptible Golden Syrian hamster model. Methods: Two cohorts of naïve hamsters were subjected to airborne transmission from experimentally infected hamsters; one cohort was exposed to air treated with UV-C sterilization, while the other cohort was exposed to un-treated air. Results: Treatment of air with UV-C light prevented the airborne transmission of SARS-CoV-2 from experimentally exposed hamster to naïve hamsters. Notably, this protection was sustained over a muti-day exposure period during peak viral shedding from hamsters. Conclusion: These findings demonstrate the efficacy of the UV-C light to mitigate airborne SARS-CoV-2 transmission. As variants continue to emerge, UV-C light holds promise as a tool to reduce infections in diverse indoor settings, ranging from healthcare facilities to households. This study reinforces the urgency of implementing innovative methods to reduce airborne disease transmission and safeguard public health against emerging biological threats.

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

Some peptide-based drugs including oxytocin, vasopressin, ziconotide, pramlintide, nesiritide, and octreotide, contain one intramolecular disulfide bonds. A novel and reusable monodispersed silica nanosphere-supported Pt(IV) complex (SiO2@TPEA@Pt(IV)) was synthesized via a four-step procedure and used for formation of intramolecular disulfide bonds in peptides. TEM and chemical mapping results for the Pt(II) intermediates and for SiO2@TPEA@Pt(IV) show that the silica nanospheres possess a monodisperse spherical structure and contain uniformly distributed Si, O, C, N, Cl, and Pt. The valence state of Pt on the silica nanospheres was characterized by XPS. The Pt(IV) loaded on SiO2@TPEA@Pt(IV) was 0.15 mmol/g, as determined by UV-vis spectrometry. Formation of intramolecular disulfides in six dithiol-containing peptides of variable lengths by use of SiO2@TPEA@Pt(IV) was investigated and the relative oxidation yields were determined by HPLC. In addition, peptide 1 (Ac-CPFC-NH2) was utilized to study the reusability of SiO2@TPEA@Pt(IV). No significant decrease in the relative oxidation yield was observed after ten reaction cycles. Moreover, the structure of SiO2@TPEA@Pt(IV) after being used ten cycles was determined to be similar to its initial one, demonstrating the cycling stability of the complex.

Ebola virus disease (EVD) represents a global health threat. The etiological agents of EVD are 6 species of Orthoebolaviruses, with Orthoebolavirus zairense (EBOV) having the greatest public health and medical significance. EVD disease pathogenesis occurs as a result of broad cellular tropism of the virus, robust viral replication and a potent and dysregulated production of cytokines. In vivo, tissue macrophages are some of the earliest cells infected and contribute significantly to virus load and cytokine production. While EBOV is known to infect macrophages and to generate high titer virus in the liver, EBOV infection of liver macrophages, Kupffer cells, has not previously been examined in tissue culture or experimentally manipulated in vivo. Here, we employed primary murine Kupffer cells (KC) and an immortalized murine Kupffer cell line (ImKC) to assess EBOV-eGFP replication in liver macrophages. KCs and ImKCs were highly permissive for EBOV infection and IFN-γ polarization of these cells suppressed their permissiveness to infection. The kinetics of IFN-γ-elicited antiviral responses were examined using a biologically-contained model of EBOV infection termed EBOV ΔVP30. The antiviral activity of IFN-γ was transient, but a modest ~3-fold reduction of infection persisted for as long as 6 days post treatment. To assess the interferon stimulated gene products (ISGs) responsible for protection, the efficacy of secreted ISGs induced by IFN-γ were evaluated. Secreted ISGs blocked recombinant VSV expressing EBOV GP (rVSV/EBOV GP) infection, but failed to block EBOV ΔVP30. Our studies define new cellular tools for the study of EBOV infection that can potentially aid the development of new antiviral therapies. Furthermore, our data underscore the importance of macrophages in EVD pathogenesis and those IFN-γ-elicited ISGs that help to control EBOV infection.

Polycystic ovary syndrome (PCOS) is a prevalent condition characterized by manifestations that can influence self-image and potentially result in psychological distress; however, data from literature on sexual function (SF) in PCOS women are contradictory. We aimed to evaluate sexual dysfunction (SD) in PCOS women by carrying out a systematic review and meta-analysis, using the gold-standard assessment tool SD-diagnosis (Female Sexual Function Index:FSFI). Seven databases were analyzed until August-2023; study quality was assessed by risk of bias and Newcastle Ottawa Scale. Our analysis encompassed 25 case-control studies (9933 women). PCOS group presented significantly lower scores in arousal (MD= -0.36 CI95%-0.60;-0.11), lubrication (MD= -0.52 CI95%-0.75;-0.28), orgasm (MD= -0.39 CI95%-0.57;-0.20), satisfaction (MD= -0.32 CI95%-0.50;-0.14) and pain subdomains (MD= -0.46 CI95%-0.75;-0.16), as in overall FSFI score (MD= -2.27 CI95%-3.23;-1.31). Overweight/obese (OW/O) patients exhibited significantly higher overall FSFI than OW/O controls (MD=1.98 CI95%0.68;3.27), particularly in lubrication (MD= -0.34), orgasm (MD= -0.26) and satisfaction (MD= -0.25) subdomains. These findings offer insights regarding SD in PCOS women and emphasize the need to incorporate SF assessment into multidisciplinary care. By this way, PCOS can be also considered a gateway diagnosis to other long-term consequences. Further research should focus on controlling variables, as ethnicity, culture, religion and economic disparities.

Biomechanics is a branch of biophysics that deals with mechanics applied to biology. The biomechanics of the cornea plays a significant role in managing patients with glaucoma. While evidence suggests a higher risk of glaucoma in patients with thin and stiffer corneas, it also affects the measurement of intraocular pressure (IOP). We reviewed the pertinent literature to help the understanding of corneal biomechanics and how it can help optimize clinical and surgical treatments and a better approach to diagnosing and managing patients with glaucoma.

Zika virus (ZIKV) co-circulates with several closely related flaviviruses which exhibit similar clinical manifestations thus, clinicians rely on molecular and serological techniques for diagnosis. Cross-reactivity of patient specimens to flaviviruses is a significant impediment to serological diagnosis in areas where multiple flaviviruses co-circulate. Furthermore, patient exposure history to any of these viruses could complicate serological response patterns which could result in over and/or underdiagnosis of ZIKV infection. Three strains of ZIKV, dengue serotypes 1-4, West Nile virus, Japanese Encephalitis virus, and Yellow Fever virus were evaluated for neutralizing properties against 3 monoclonal antibodies, 4 ZIKV-naïve patients with flavivirus exposure history, 5 patients with verified ZIKV exposure and unknown flavivirus exposure history, and 5 flavivirus-naive patients with ZIKV-only exposure. Patients naïve for ZIKV exposure effectively neutralized multiple strains of ZIKV. Overall, the prototype ZIKV isolate MR-766 did not behave like the other ZIKV isolated used in this study. MR-766 was neutralized more completely by polyclonal patient serum than recent ZIKV isolates. MR-766 was neutralized better than dengue virus in ZIKV-naïve patients with prior dengue exposure. MR-766 was neutralized significantly less than recent ZIKV isolates when treated with monoclonal antibodies. The data herein show that without RT-PCR, serological diagnosis may not be possible in areas where multiple flaviviruses are endemic.

Mass transfer restrictions of scaffolds are currently hindering the development of three-dimensional (3D), clinically viable, and tissue engineered constructs. For this situation, a 3D poly(lactide-co-glycolide)/hydroxyapatite porous scaffold, which was much favorable for transfer of nutrients to and waste products from the cells in the pores, was developed in this study. The 3D scaffold had an innovative structure, including macropores with diameters of 300−450 μm for cell ingrowth and microchannels with diameters of 2−4 μm for nutrition and waste exchange. The mechanical strength in wet state was strong enough to offer the structural support. The typical structure was more beneficial for the attachment, proliferation, and differentiation of rabbit bone marrow mesenchymal stem cells (rBMSCs). The alkaline phosphatase (ALP) activity and calcium (Ca) deposition were evaluated on the differentiation of rBMSCs, and the results indicated that the microchannel structure was very favorable for differentiating rBMSCs into maturing osteoblasts. For repairing rabbit radius defects in vivo, there was rapid healing in the defects treated with the 3D porous scaffold with microchannels, where the bridging by a large bony callus was observed at 12 weeks post-surgery. Based on the results, the 3D porous scaffold with microchannels was a promising candidate for bone defect repair.

Abstract: The worldwide spread of SARS-CoV-2 has led to a significant economic and social burden on a global scale. Even though the pandemic has concluded, there remains apprehension regarding the emergence of highly transmissible variants capable of evading immunity induced by either vaccination or prior infection. The success of viral penetration is the specific amino acid residues of the Receptor Binding Motif (RBM) involved in viral attachment. This region interacts with the cellular receptor ACE2, triggering a neutralizing antibody (nAb) response. In this study, we have evaluated the immunogenicity of serum from individuals who received either a single dose or a combination of different vaccines against the original SARS-CoV-2 strain and mutated linear RBM. Despite a modest antibody response to the wild-type SARS-CoV-2 RBM, the Omicron variants exhibit four mutations in the RBM (S477N, T478K, E484A, F486V) that result in even lower antibody titers. The primary immune responses observed were directed towards IgA and IgG. While nAbs typically target the RBD, our investigation has unveiled a reduced seroreactivity within the RBD's crucial subregion, the RBM. This deficiency may have implications for the generation of protective nAbs. Evaluation of S1WT and S2WT RBM peptides binding to nAbs using microscale thermophoresis revealed a higher affinity (35 nM) for the S2WT sequence (GSTPCNGVEGFNCYF), which includes the FNCY patch. Our findings suggest that the linear RBM of SARS-CoV-2 is not an immunodominant region in vaccinated individuals. Comprehending the intricate dynamics of the humoral response, its interplay with viral evolution, and host genetics is crucial for formulating effective vaccination strategies, not only targeting SARS-CoV-2 but also anticipating potential future coronaviruses.

Soccer is the leading cause of all sports-related ocular injuries in Europe and Israel and leads to blindness at a disproportionately high rate, especially among children (Thompson et al., 2019). With soccer being the most popular sport in the world, it is surprising the only solution to ocular injuries are sports glasses which can cause direct damage to the eye and impair peripheral vision by 15%, calling for an alternative (Smith & Jones, 2020). This work, based on an imported facial model, focuses on both the qualitative and quantitative aspects of building a personalized, low-cost (through optimizing material needed), superior apparatus to conventional sports glasses. The quantitative side examines a modified and model-validated (through a SRS of thirty unique extrapolated points) multivariate linear regression equation, based on horizontal and vertical rotation angles (n=60) trained with residual and computer simulation data, that can accurately extrapolate and quantify ocular impact from all horizontal and vertical rotation angles and a modified Hertzian Contact Stress Equation to determine the thickness of the apparatus using the elasticity modulus, impact force, and geometrical facial and soccer-ball features. The qualitative side examines where firstly, ocular impact is most prevalent, and secondly, where most impact is seen from rotating the ball horizontally and vertically through analysis of Pearson’s Correlation Coefficient at the supraorbital, medial canthus, infraorbital, and lateral canthus regions from both regression equations as well as a cost-benefit analysis for comparison with conventional sports glasses. The findings discovered in this work lay the groundwork for future research to build a customized low-cost ocular injury prevention device which can simultaneously ensure complete ocular safety while enhancing athletic performance for over 250,000,000 players (Johnson & Garcia, 2022).

Periodontitis is a chronic inflammatory disease affecting the tissues that surround and support the teeth. In the U. S., approximately 65 million people are affected by this condition. Its occurrence is also associated with many important systemic diseases such as cardiovascular disease, rheumatoid arthritis, and Alzheimer’s disease. Among the most important etiologies of periodontitis is Porphyromonas gingivalis, a keystone bacterial pathogen. Keystone pathogens can orchestrate inflammatory disease by remodeling a normally benign microbiota causing imbalance between normal and pathogenic microbiota (dysbiosis). The important characteristics of P. gingivalis causing dysbiosis are its virulence factors that cause effective subversion of host defenses to its advantage [1], allowing other pathogens to grow. However, the mechanisms involving these processes are poorly understood. However, various microbial strategies target host sialoglycoproteins for immune dysregulation. In addition, the enzymes that break down sialoglycoproteins/sialoglycans are the “sialoglycoproteases”, resulting in exposed terminal sialic acid. This process could lead to pathogen-toll like receptor (TLR) interactions mediated through sialic acid receptor–ligand mechanisms. By assessing the function of P. gingivalis sialoglycoproteases, could pave the way to designing carbohydrate analogues and sialic acid mimetics to serve as drug targets.

Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically, which becomes along with huge computational times and efforts. This situation becomes even much more harder and complicated in the mixture Regular vine models. Incorporating truncation method with mixture Regular vine models will reduce the computation difficulty for the mixture based models. In this paper, tree-by-tree estimation mixture model is joined with the truncation method, in order to reduce the computational time and the number of the parameters that need to be estimated in the mixture vine copula models. A simulation study and a real data applications illustrated the performance of the method. In addition, the real data applications show the affect of the mixture components on the truncation level.

Apex predators were extirpated from the UK hundreds of years ago. Practitioners have recently advocated for reintroductions of predators in the UK given their role as keystone species. For a reintroduction to take place, a survey of public desirability needs to be conducted. We aimed to understand the perspectives of people across the United Kingdom on the reintroduction of Eurasian lynxes, grey wolves, and brown bears. We collected data via questionnaires from 78 key stakeholders, such as farmers, general public, nature conservationists, and those in environmental sectors, with these areas being seen as the most affected by these reintroductions. It was organizations which front these stakeholder groups which mainly distributed the survey, as well as social media groups. We ran a path analysis, which highlighted that there was a negative correlation between respondents viewing the species as a danger towards livestock and humans, and the respondent seeing it being good to have that species in their region. Overall, participants who stated that rewilding their region was a priority also stated that it would be good to have Eurasian lynx in their region. That said, 70% of farmers strongly disagreed with the reintroduction of Eurasian lynx. These findings showed that much of the United Kingdom would welcome the reintroduction of Eurasian lynx, but both farmers and the public would fear the loss of livestock that may come along with these species. Support can be gained through education and knowledge, a necessary step needed especially targeting farmers before any reintroduction plans can be made.

The travel-goods industry is an essential part of the larger travel and tourism sector, but it creates significant environmental impacts due to resource and energy consumption. This study investigates the feasibility and sustainability potential of servitisation concepts within the travel-goods industry, and the Product-Service System (PSS) models, in particular, to identify steps towards a more sus-tainable travel industry in the future. It explores the sustainability-related drivers within the luggage industry and identifies barriers to the adoption of servitisation models, and opportunities for value creation for both consumers and commercial organisations. Business models are mapped into a ty-pology to highlight different pathways to PSS adoption, underpinned with empirical data collected via a consumer sentiment survey and semi-structured interviews with industry experts. Even though the analysis revealed shifting consumer attitudes towards servitisation concepts within the travel-goods market, with a significant level of interest emerging for specific PSS models, at present, the widespread adoption of PSS is hindered. This is due to the fragmented nature of global supply chains and entrenched ownership values. Addressing supply chain issues regarding end-of-life systems to sustainably manage products beyond functional obsolescence is critical. In parallel, product-oriented PSS models are more likely to increase, driven by a burgeoning resale market and supported by digi-tal technologies, which in turn can lead to greater prospects for use-oriented PSS adoption and even-tually, reduced environmental impacts.

Data from environmental satellites are underutilized in many branches of operational oceanography. Several challenges exist for potential users of satellite data that may impede or preclude employing satellite products in their work. Users outside of the satellite community often encounter difficulty in discovering the types of satellite measurements that are available, and determining which satellite products are best for operational activities. In addition, the large choice of satellite data providers, each with their own data access protocols and formats, can make data access confusing and inefficient. NOAA’s CoastWatch Program is designed to be a Value Added Provider, whose mission is to help make satellite data easier for users to access. With this objective the West Coast Node of CoastWatch developed the NOAA Ocean Satellite Course, which introduces scientists and resource managers to ocean satellite products, and provides them tools to facilitate data access when using ArcGIS or R software. These tools leverage upon the data services provided by ERDDAP, a data distribution system designed to make data access easier for both humans and machines. The course has been offered annually since 2006, and over 350 participants have taken it. Results of post-course surveys are analyzed to measure course effectiveness. Lessons learned from conducting these courses are summarized.

In a continuation and extension of an earlier publication, the calculation of the refractivity and polarizability of organic molecules at standard conditions is presented, applying a commonly applicable computer algorithm based on an atom-group additivity method, where the molecules are broken down into their constituting atoms, these again being further characterized by their immediate neighbor atoms. The calculation of their group contributions, carried out by means of a fast Gauss–Seidel fitting calculus, used the experimental data of 5988 molecules from literature. An immediate subsequent ten-fold cross-validation test confirmed the extraordinary accuracy of the prediction of the molar refractivity, indicated by a correlation coefficient R^2 and a cross-validated analog Q^2 of 0.9997, a standard deviation σ of 0.38, a cross-validated analog S of 0.41, and a mean absolute deviation of 0.76%. The high reliability of the predictions has been exemplified with three classes of molecules: ionic liquids, silicon- and boron-containing compounds. The corresponding molecular polarizabilities have been calculated indirectly from the refractivity using the inverse Lorentz-Lorenz relation. In addition, it could be shown that there is a close relationship between the "true" volume and the refractivity of a molecule, revealing an excellent correlation coefficient R^2 of 0.9645 and a mean absolute deviation of 7.53%.

The digital economy, driven by information and communication technologies (ICT), has profoundly transformed in recent decades. The digitalization of society has given rise to an economic environment in which information, connectivity, and innovation play fundamental roles. In this context, a technology that has emerged as a fundamental pillar of the digital economy is the chain of blocks, commonly known as blockchain. Blockchain is a technology that has revolutionized the way online data and transactions are managed and shared. Through its ability to create secure, transparent, and decentralized ledgers, blockchain has paved the way for the digital economy, facilitating trust in digital transactions and enabling various applications ranging from cryptocurrencies to supply chain management and intellectual property. This study will delve into blockchain and its influence on the digital economy. It will explore how this technology has reshaped how companies interact, how consumers access services, and how new business models are developed in a constantly evolving digital environment. Additionally, the challenges and opportunities that blockchain presents in the context of the digital economy will be analyzed, and how it is helping to shape the future of business and society in general. As the exploration of blockchain and its impact on the digital economy progresses, it becomes evident how these two forces converge, generating a promising digital landscape full of significant opportunities and transformations. This phenomenon is consistently supported by a growing body of research and analysis, which underlines the growing influence of blockchain on the global economy (Smith, 2020; Johnson, 2019). The dynamic interplay between these two spheres, blockchain and the digital economy, constantly evolves and offers an exciting glimpse into the future regarding innovation and disruption across various sectors (Jones, 2021; Brown, 2018). As a result, significant opportunities are looming for those seeking to understand and capitalize on these emerging trends (García, 2022). Throughout this study, the current trends and most intriguing perspectives that shape this landscape will be broken down, offering a deeper insight into how blockchain and the digital economy are shaping an extraordinary digital future

Background: The Davidson Airway Function &amp; Nasal Evaluation (DAFNE) Scoring System was developed as an intuitive and research-based scoring system that could be validated through beta testing and easily introduced to healthcare providers of several subspecialties who treat nasal obstruction and breathing disorders (MDs, PAs, PTs, APRNs, DDSs, and DCs). This scoring system was shown to increase the knowledge of airway function, nasal measurement parameters, and identification of proper treatment options for sleep and breathing disorders. The basis for the DAFNE score was developed from a systematic review of nasal measurement data. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were used to identify studies validating nasal function measurement parameters to create the algorithm for the DAFNE Score™. The systematic review was accomplished using the 2020 ‘Preferred Reporting Items for Systematic Reviews’ (PRISMA) guidelines. Results: Twenty studies met the inclusion criteria for systematic review. Primary outcomes measurements demonstrated reliability, repeatability and validity of the DAFNE measurement technologies, data and output. Conclusions: The data analysis and systematic review uncovered a need and framework to develop and validate a web-based software algorithm for global access to improve the understanding of data interpretation of nasal measurements from three nasal measurement technologies. DAFNE Scoring should be used as an adjunct tool in routine clinical practice and research to further understand the technology data output and how to collaborate with other healthcare providers to improve patient outcomes.

The calculation of the standard enthalpies of vaporization, sublimation and solvation of organic molecules is presented using a common computer algorithm on the basis of a group-additivity method. The same algorithm is also shown to enable the calculation of their entropy of fusion as well as the total phase-change entropy of liquid crystals. The present method is based on the complete break-down of the molecules into their constituting atoms and their immediate neighbourhood; the respective calculations of the contribution of the atomic groups by means of the Gauss-Seidel fitting method is based on experimental data collected from literature. The feasibility of the calculations for each of the mentioned descriptors was verified by means of a 10-fold cross-validation procedure proving the good to high quality of the predicted values for the three mentioned enthalpies and for the entropy of fusion, whereas the predictive quality for the total phase-change entropy of liquid crystals was poor. The goodness of fit (Q²) and the standard deviation (σ) of the cross-validation calculations for the five descriptors was as follows: 0.9641 and 4.56 kJ/mol (N=3386 test molecules) for the enthalpy of vaporization, 0.8657 and 11.39 kJ/mol (N=1791) for the enthalpy of sublimation, 0.9546 and 4.34 kJ/mol (N=373) for the enthalpy of solvation, 0.8727 and 17.93 J/mol/K (N=2637) for the entropy of fusion and 0.5804 and 32.79 J/mol/K (N=2643) for the total phase-change entropy of liquid crystals. The large discrepancy between the results of the two closely related entropies is discussed in detail. Molecules, for which both the standard enthalpies of vaporization and sublimation were calculable, enabled the estimation of their standard enthalpy of fusion by simple subtraction of the former from the latter enthalpy. For 990 of them the experimental enthalpy-of-fusion values are also known, allowing their comparison with predictions, yielding a correlation coefficient R² of 0.6066.

The calculation of the vapour pressure of organic molecules at 298.15K is presented using a commonly applicable computer algorithm based on the group-additivity method. The basic principle of this method rests on the complete breakdown of the molecules into their constituting atoms, further characterized by their immediate neighbour atoms. The group contributions are calculated by means of a fast Gauss-Seidel fitting algorithm using the experimental data of 2036 molecules from literature. A ten-fold cross-validation procedure has been carried out to test the applicability of this method, which confirmed excellent quality for the prediction of the vapour pressure, expressed in log(pa), with a cross-validated correlation coefficient Q2 of 0.9938 and a standard deviation  of 0.26. Based on these data, the molecules' standard Gibbs free energy G°vap has been calculated. Furthermore, using their enthalpies of vaporization, predicted by an analogous group-additivity approach published earlier, the standard entropy of vaporization S°vap has been determined and compared with experimental data of 1129 molecules, exhibiting excellent conformance with a correlation coefficient R2 of 0.9598, a standard error  of 8.14 J/mol/K and a medium absolute deviation of 4.68%.

As non-operative management (NOM) of esophageal and rectal cancer is becoming more prevalent, blood-biomarkers such as circulating tumor DNA (ctDNA) may provide clinical information in addition to endoscopy and imaging to aid in treatment decisions following chemotherapy and radiation therapy. In this feasibility study, we prospectively collected plasma samples from locally advanced esophageal (n=3) and rectal cancer (n=2) patients undergoing multimodal neoadjuvant therapy to assess the feasibility of serial ctDNA monitoring throughout neoadjuvant therapy. Using the DIDA-Seq error-correction method, we serially interrogated plasma cell-free DNA at 28-41 tumor-specific genomic loci throughout therapy and in surveillance with an average limit of detection of 0.016% mutant allele frequency. In both rectal cancer patients, ctDNA levels were persistently elevated following total neoadjuvant therapy with eventual detection of clinical recurrence prior to salvage surgery. Among the esophageal cancer patients, ctDNA levels closely correlated with tumor burden throughout and following neoadjuvant therapy, which was associated with a pathologic complete response in one patient. In this feasibility study, patient and tumor-specific ctDNA levels correlated with clinical outcomes throughout multi-modality therapy suggesting that serial monitoring of patient ctDNA has the potential to serve as a highly sensitive and specific biomarker to risk-stratify esophageal and rectal cancer patients eligible for NOM. Further prospective investigation is warranted.

Abstract: Background: The diagnosis of nasal airway disorders relies on questionnaires, subjective data, and objective data. Interpretation of objective data obtained from measurement technology is not well understood by providers and researchers who use the equipment to test nasal airway function, justifying the need to cre-ate a new clinical tool. The Davidson Airway Function & Nasal Evaluation (DAFNE) Scoring System is a web-based scoring system that allows healthcare providers (MDs, PAs, PTs, APRNs, DMDs, DDSs, SLPs, and DCs) and researchers who treat nasal obstruction and breathing disorders to make more accurate diagnostic decisions, select the appropriate treatment for individualized patient care, monitor treatment progression and outcomes, and show how to approach a collaborative care model with other healthcare professionals. The current technologies, such as 4-phase rhinomanometry, use a simple approach that relies on a measurement tracing intersecting a color-coded y-axis on a four-quadrant graph with diagnostic numeric data output de-scribing nasal airflow and resistance. This is a good source of biofeedback demonstrating abnormal nasal breathing patterns but lacks interpretation guidelines to describe the severity of disease. The more sophisti-cated proprietary DAFNE approach uses multiple parameters which include airflow restriction, speed, vol-ume, and patient characteristics to identify patients’ disease progression much more accurately. Additionally, it explains how to segregate patients into appropriate treatment options which minimizes risks and compli-cations associated with sleep and breathing disorders while improving patient outcomes. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were necessary to identify studies which determined the ranges of nasal function measurement parameters among three airway measurement technologies used in writing the DAFNE Score algorithm. The performance of DAFNE was evaluated compared to the research data and patient demographics used in previous studies. Results: By using primary outcome measurements from the literature, we were able to create a reliable, re-peatable, and validated tool to facilitate patient identification, treatment stratification, and collaboration for sleep and nasal breathing dysfunction. Subsequently, we found DAFNE could be used to identify the appro-priateness of a sleep study. Conclusions: DAFNE Scoring System has demonstrated the ability to detect high risk patients in the pediatric and adult populations susceptible of sleep apnea and breathing dysfunction needing a sleep study and treatment to improve nasal airway function and sleep. DAFNE Scoring System should be used as an adjunct tool in routine clinical practice and research to further understand the technol-ogy data output, identify patients at risk, stratify treatment options, progress, and stabilization after treatment, and how to collaborate with other healthcare providers to improve patient outcomes.

The oral administration of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate, allows inducing a beneficial level of blood ketone bodies without the adverse effects due to the adhesion to a ketogenic diet. Several studies documented the therapeutic effectiveness of the (R)-3-hydroxybutyl (R)-3-hydroxybutyrate in treating neurodegenerative diseases as well as its boosting activity of athletic and cognitive performances during prolonged physical exercises. Further studies considering this ketone body ester for therapy of other pathologies are also underway. In the present work, we describe the synthesis of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate through the enantioselective transesterification of racemic ethyl 3-hydroxybutyrate with (R)-1,3-butanediol catalyzed by immobilized Candida antarctica lipase B (CAL-B). The enantiopure (R)-1,3-butanediol was in turn obtained from the kinetic resolution of the racemate by CAL-B catalyzed acetylation with vinyl acetate. The economy of the synthetic procedure has been improved by recycling the unreacted (S) enantiomers of the ethyl 3-hydroxybutyrate and 1,3-buatnediol after stereochemical inversion achieved by tosylation and SN2 with ammonium acetate. The overall procedure allows to incorporate up to 70% of the starting racemic reagents into the final product.

Sleep disorders have become a public health problem for many reasons. The aim of this systematic review is to describe social, economic, and environmental determinants of sleep disturbances in Australia and New Zealand. A total of 22 studies, 14 from Australia and 8 from New Zealand involving children, adolescents and adults are included in the review. In summary, we found that sleep health disparities among children and adolescents in both countries are strongly associated to parental SES. Overall, lower family SES such as low parental income, low parental education, low SES area index are associated with higher sleep disturbances among children and adolescents. In adults, results revealed that SES determinants such as low income, lower education, unemployment, and night work were associated with sleep disturbances. Specifically, unemployment was associated with poor sleep quality, insomnia, and increased likelihood of suboptimal sleep efficiency. Low income and lower education were associated with high risk of OSA, longer sleep duration, insomnia, higher odds of suboptimal sleep duration and sleep onset latency.

This study presents a novel polyurethane-activated carbon composite (PACC) as an effective and sustainable adsorbent for treating lead-ion-contaminated waters. The PACC was characterized using SEM-EDX, FTIR, BET, XRD, and TGA to evaluate its physicochemical and thermal properties. Furthermore, the PACC was employed in an experimental column adsorption setup to investigate its adsorption performance and to develop a dynamic method suitable for industrial implementation. Parameters such as bed height (50, 100, 150 mm), flow rate (4, 6, 8 mL min-1), pH (2, 4, 6), and initial metal ion concentrations (10, 50, 100 mg L-1) were examined. The experimental data exhibited strong agreement with the Thomas and Yoon-Nelson models (R2 ≥ 0.96), indicating efficient adsorption mechanisms. Remarkably, the depleted adsorbent has the potential for facile regeneration without substantial loss in capacity. The PACC demonstrated excellent adsorption performance for lead ions in aqueous solutions in a fixed-bed column system. Thus, the novel PACC material holds potential for scalable application in industrial settings to address water pollution challenges, especially in regions with uncontrolled effluent discharge.

The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. It has been shown that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on way to an endemic form, however the threat of the virus is more for susceptible (older people and immunocompromised) people. The human body has more bacterial cells than its own, thus making us more bacterial than humans. As a consequence, the bacteriomes in the human body heavily influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. in major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. that have a positive effect on the functionality of the immune system and human health. These select bacterial spp. could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. that could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacy.

Drainage systems are usually dimensioned for design storms based on intensity-duration-frequency (IDF) curves of extreme precipitation. For each location, different IDF curves are established based on local hydrological conditions. Recent research shows that these curves also vary with time, and should be updated with recent data. The purpose of this study is to evaluate IDF curves obtained from precipitation simulations from the Eta RCM, comparing them with IDF curves obtained from data of a rainfall station. Climate models can be a useful tool for assessing the impacts of climate changes on drainage systems, referring precipitation forecasts. In this study, the Eta RCM was forced by two global climate models: HadGEM2-ES and MIROC5. The bias of the precipitation data, generated by RCM models, was corrected using a Gamma distribution. The Juqueriquerê River Basin, in the cities of Caraguatatuba and São Sebastião, São Paulo State, Brazil, was chosen as a case study. The results show a good correlation between the IDF curves of simulated and observed rainfall for the control period (1960-2005), indicating the strong possibility of using the Eta RCM precipitation forecasts for 2007 - 2099 to establish future IDFs thereby, taking into account climate changes in urban drainage design.

Toxoplasma gondii (T. gondii) is one of the most common parasites that infect humans. The parasite exists in approximately 40 million people in the United States. Latent infections are frequently associated with tissue cysts of T. gondii in the skeletal muscle and brain tissue that can lead to mental disorders, congenital disorders, and vision dysfunction. Furthermore, self-directed violence, impulsivity, and aggression are associated with T. gondii infection. Dopamine is associated with human behavior including pleasure, aggression, memory, and substance use disorder; however, the result of the studies on the association of T. gondii infection and drugs of abuse are not well understood. The frequency of substance use may be associated with substance-induced modification of dopamine-receptor densities and basal dopaminergic activity. Likewise, T. gondii can directly or indirectly influence dopaminergic activity in infected cells. Based on this hypothesis, the current paper aimed to systematically review all published literature on the association between drugs of abuse and T. gondii infection. Systematic review of controlled studies on T. gondii infection and substance use effects in adults were searched on the electronic databases. Studies have shown that individuals infected with T. gondii display increased risky behavior, such as excessive alcohol consumption. Furthermore, it was observed that T. gondii seropositive subjects had a reduced likelihood of self-reported substance use compared to T. gondii seronegative subjects. This study confirms that SUD is a potential risk factor for behavioral and psychiatric complications associated with T. gondii infection. Ultimately T. gondii infection in the context of drug dependence and the development of SUD remain to be elucidated. Therefore, it is necessary to conduct further research characterizing the mechanisms associated with dopamine metabolism of drug dependence and withdrawal in the context of a T. gondii infection, evaluating the role of inflammation, and identifying potential drug-and-sex specific underpinnings of these associations.

Kamchatka berries (Lonicera caerulea L.) are known for their high content of phenolic compounds or vitamins, which is reflected in their antibacterial, detoxifying and anti-inflammatory properties. They are used in the production of jams, juices, wines and as natural dye. A bioferment was prepared from the pomace of the Kamchatka berry varieties Aurora and Indigo Gem and the strains Saccharomyces cerevisiae and Lacticaseibacillus paracasei, which was used to prepare a cosmetic preparation with a concentration of 5% in accordance with the guidelines of the COSMOS certification body. Conducted physico-chemical and organoleptic analyses and bioactive profile characterisation (UHPLC-DAD and UHPLC-ESI-MS/MS). The results showed that the presence of caffeic acid 4.47 ± 0.07 mg/100g was detected after fermentation of Kamchatka berry pomace. Vitamin C content increased by 141% after fermentation of Kamchatka berry pomace. The results of stability tests showed that in the process of physicochemical analysis of cosmetic preparation with bioferment of Kamchatka berry pomace the pH should oscillate in the range of 4.38-4.76 ± 0.01. Stability tests showed that the cosmetic should be protected from high temperatures and UV radiation and proved that the product is stable under changing conditions, resulting in lower transport and storage costs.

The conservation of coastal wetland ecosystems, like mangrove forests and salt marshes, represents a critical strategy for mitigating atmospheric emissions and climate change in the 21st century. Yet the existence of these environments is threatened by human-induced disturbances, namely deforestation and accelerated sea-level rise. Coastal systems maintain surface elevation in response to sea-level rise through a combination of physical and biological processes both above and below the ground surface. The quantification and relative contribution of belowground process controls (e.g., seasonal water content, organic matter decomposition) on surface elevation change is largely unexplored but crucial for informing coastal ecosystem sustainability. To address this knowledge deficit, we integrated measurements of surface elevation change of the live root zone (0.5 to 1 m depth) with geotechnical data from co-located sediment cores in the Sundarbans mangrove forest (SMF) of southwest Bangladesh. Core data reveal that the primary belowground controls on surface elevation change include seasonal fluctuations in pore-water content and the relative abundance of fine-grained sediments capable of volumetric expansion and contraction, supporting an elevation gain of ~2.42 ± 0.26 cm yr⁻¹. In contrast to many mangrove environments, the soils of the SMF contain little organic matter and are dominantly composed (>90%) of inorganic clastic sediments. The mineral-rich soil texture likely leads to less compaction-induced subsidence as compared to organic-rich substrates and facilitates surface equilibrium in response to sea level rise. Despite a relatively high soil bulk density, soil carbon (C) density of the SMF is very low owing to the dearth of preserved organic content. However, rates of C accumulation are balanced out by locally high accretion rates, rendering the SMF a greater sink of terrestrial C than the worldwide mangrove average. The findings of this study demonstrate that C accumulation in the SMF, and possibly other alluvial mangrove forests, is highly dependent on the continued delivery of sediment to the mangrove platform and associated settings.

Background: Extremametly lean athletes could have difficulty for adaptive eating (intuitively or consciously) during ad libitum refeed. Aims: we verificate if there is a relation between adaptive eating and coping strategies with energy intake in a model of refeed proposed for bodybuilders. Methods: Fourteen male bodybuilders (29.6±3.1yrs; 85.6±6.8kg, ≥6 competitions) completed the 4-week each consisting of a 5 days of energy restriction following 2 days of refeed. Dietary assessment, body composition (ultrasound), Recovery stress questionnaire (REST-Q) and BRUMS (Brunel mood scale) were accessed pre and post; Coping Function Questionnaire (CFQ), Mindful Eating Scale version 2 (MES 2) and the Intuitive Eating Scale-2 (IES-2) was used at 4th week. Results: The refeed day resulted in a daily caloric increment of ~44% compared to the average energy intake on the energy restriction days, culminating in a weekly calorie deficit of ~27% and a drop in body mass of 3.1±1.4% with relation to initial values. The most reduced body fat and preserved or gained lean mass. The energy consumption during refeed maintained an inverse relationship with the perception of satiety (r=-0.9; p<0.01), total scores of IES 2 (r=-0.82; p<0.01), as well as with the confidence in hunger and satiety cues (r=-0.62; p=0.02) and congruence in food-body choice (r=-0.56; p=0.04) dimensions. Coping based in emotions maintained a relationship with the total scores of IES 2 (r=0.54; p<0.05) and an inverse relationship with energy intake during refeed (r=-0.42; p<0.05). Conclusion: Our results suggest that a higher perception of internal hunger and satiety signals and higher scores in intuitive eating may contribute to energy intake adequate, even when high scores of coping based in emotions are present.

In this study, we successfully obtained a 2Mg-Fe mixture through mechanical alloying (MA) and processed it via accumulative roll bonding (ARB) (MA+ARB). Our primary focus was to analyze the impact of ambient air exposure while also evaluating the processing route. Some powder samples were exposed to air for 12 months before undergoing ARB processing. The Mg samples obtained after ARB processing exhibited a (002)-type texture. Our results demonstrate that all samples, including those processed via ARB, could rapidly absorb hydrogen within a matter of minutes, despite considerable differences in surface area between powders and rolled samples. ARB-processed samples reached approximately 60% of their maximum acquired capacity within just 24 minutes, compared to powders stored for a year which took 36 minutes. Also, the desorption temperatures were lower than those of MgH2. The absorption and desorption kinetics remained fast even after prolonged exposure to air. Although there were minor variations in capacities, our overall findings are promising since scalable techniques such as ARB have the potential to produce hydrogen storage materials that are both safe and cost-effective in a highly competitive market.

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava-Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS conjecture can be made independent of $R$ is by considering a power law of the form $f(R)\sim R^{\gamma}$. The conjecture and the consistency of the theory puts restrictions on $\gamma$ to be greater but close to $1$. For the $F(\bar{R})$ theories described by its two parameters $\lambda$ and $\mu$ we use the equations of motion to construct the function starting with an ansatz for the scale factor in the Jordan frame of the power law form. By doing a conformal transformation on the three metric to the Einstein frame we can obtain an action of gravity plus a scalar filed by relating the parameters of the theory. The non-projectable and projectable cases are studied and the differences are outlined. The $F(\bar{R})$ function obtained consists of terms of the form $\bar{R}^{\gamma}$ with the possibility of having negative power terms. The dS conjecture leads to inequalities for the $\lambda$ parameter, in both versions it gets restricted to be greater but close to $1/3$. For the general case in which $\mu$ and $\lambda$ are considered as independent, the action contains an extra term but we propose that the conjecture is still applicable. Once again the non-projectable and projectable cases are studied. The $F$ function obtained has the same form as before, the consistency of the theory and the dS conjecture lead to a set of inequalities on both parameters that are studied numerically. In all cases $\lambda$ is restricted by $\mu$ around $1/3$ and we obtain $\lambda\to1/3$ if $\mu\to0$. Finally we consider the $f(R)$ limit $\mu,\lambda\to1$ and we obtain consistent results.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

The work proposes a new approach for evolutionary global optimization which, in simple terms, may be described as a fusion of quantum and simulated annealing. This becomes possible by using basic concepts from Homotopy Theory, conjugated to the already existing Fuzzy Adaptive Simulated Annealing paradigm and other components. In this fashion, it occurs a temporal and nonlinear superposition of the two types of annealing, provoking interesting effects in runtime, including the so-called quantum tunneling, when there is a sudden transition between attraction basins of different minima without "climbing" potential barriers. In addition, the proposal includes a generalization of the "deformation" of Hamiltonians used in quantum annealing by suggesting the use of general homotopies between the surface corresponding to the cost function under processing and another specific landscape, being this possible because of the ability of Fuzzy ASA of handling time-varying objective functions. The proposed paradigm shows that it is possible and beneficial to superpose the two types of annealing, displaying amazing numerical results and suggesting a kind of interlacing or synergic behavior - perhaps we could call it an "annealing entanglement". Finally, given the fast advances in commercial quantum annealing processors, it seems sensible to expect that an implementation of the proposed approach using such devices may occur very soon. In order to demonstrate the efficacy of the proposed algorithm, some significant and detailed examples are included in the text, so as to illustrate and clarify the presented ideas.

In this paper the problem of sampling from uniform probability distributions is approached by means of space-filling curves (SFCs), a topological concept that has found a number of important applications in recent years. Departing from the theoretical fact that they are surjective but not necessarilly injective, the investigation focused upon the structure of the distributions obtained when their domain is swept in a uniform and discrete manner, and the corresponding values used to build histograms, that are approximations of their true PDFs. This work concentrates on the real interval [0,1], and the Sierpinski space-filling curve was chosen because of its favorable computational properties. In order to validate the results, the Kullback-Leibler distance is used when comparing the obtained distributions in several levels of granularity with other already established sampling methods. In truth, the generation of uniform random numbers is a deterministic simulation of randomness using numerical operations. In this fashion, sequences resulting from this sort of process are not truly random.

This study evaluated the physicochemical, mineralogical properties, mobile chemical species’ bioavailability and translocation in Brassica juncea and Spinacea oleracea L plants of a South African coal fired power utility. Coal fly ash (CFA) disposal is associated with various environmental and health risks including air, soil, surface and ground water pollution due to the leaching of toxic chemical species; these ends up in food webs affecting human health, while repeated inhalation causes bronchitis, silicosis, hair loss and lung cancer. The morphology, chemical, and mineralogical composition of CFA were determined using Scanning Electron Microscopy (SEM), X-ray fluorescence (XRF) and X-ray Diffraction, respectively. In pot culture experiments, S. oleracea L and B. juncea plants were grown in three sets of pots containing CFA (set 1), soil (set 2) and a mixture of CFA plus soil at ratio 1:1 (50% CFA: 50% soil) (set 3), while no plants were grown in set 4 as a control for the leachate samples. SEM showed that surface morphology of CFA has a lower degree of sphericity with irregular agglomerations of many particles. The XRF results revealed that CFA contains 43.65%, 22.68% and 10.89% of SiO₂, Al₂O₃ and Fe₂O₃ respectively which indicate that the CFA is an alumino-silicate material. While XRD showed that the coal CFA contains mullite as a major phase followed by quartz mineral phases. Chemical species such as Fe, Mn, B, Ba and Zn were accumulated highly in most parts of the plant species. However, B. juncea showed higher potential to accumulate chemical species as compared to S. oleracea L. The bioconcentration and translocation factors (BF and TF) showed that B. juncea was the most effective in terms of bioconcentration and translocation of most of the chemical species. This indicates that B. juncea has potential in application for phytoremediation of CFA dumps and could contribute to remediation of CFA dumps and reduction of potential health and environmental impacts associated with CFA.

This article presents a forecast model that uses a hybrid architecture of recurrent neural networks (RNN) with surface neural networks (ANN), based on historical records of exported active energy (EAE) and weather data. Two types of models were developed: the first type includes six models that use EAE records and weather variables as inputs, while the second type includes eight models that use only weather variables. Different metrics were applied to assess the performance of these models, and the best model of each type was selected. Finally, a comparison of the performance between the selected models of both types is presented, and they are validated with real data provided by a solar plant, achieving acceptable levels of accuracy. The selected model of the first type has an RMSE of 0.19, MSE of 0.03, MAE of 0.09, a correlation coefficient of 0.96, and a determination coefficient of 0.93. The other selected model of the second type showed lower precision in the metrics (RMSE = 0.24, MSE = 0.06, MAE = 0.10, Corr. Coef. = 0.95, and Det. Coef. = 0.90). Both models demonstrated good performance and acceptable accuracy in forecasting the weekly photovoltaic energy production of the solar plant.

Assessment of the environmental impact of organic chemicals has become an important subject in chemical science. Efficient quantitative descriptors of their impact are their partition coefficients logPow, logKoa and logKaw. We present a group-additivity method that has proven its versatility for the reliable prediction of many other molecular descriptors for the calculation of the first two partition coefficients and indirectly of the third with high dependability. Based on the experimental logPow data of 3332 molecules and the experimental logKoa data of 1900 molecules at 298.15K the respective partition coefficients have been calculated with cross-validated standard deviations of only 0.42 and 0.48 log units and a goodness of fit Q^2 of 0.9599 and 0.9717, respectively, in a range of ca. 17 log units for both descriptors. The third partition coefficient logKaw has been derived from the calculated values of the former two descriptors and compared with the experimentally determined logKaw values of 1937 molecules, yielding a standard deviation of 0.67 log units and a correlation coefficient R^2 of 0.9467. This approach enabled the quick calculation of 29462 logPow, 27069 logKoa and 26220 logKaw values for the more than 37100 molecules of ChemBrain's database available to the public.

Background: Participation is low (43%) in Australia’s National Bowel Cancer Screening Program which provides a biennial Fecal Immunochemical Test kit mailed to the home of Australians aged 50-74 years. While several factors for non-participation have been identified, the role of mental and physical health on screening behaviour has not been assessed. Methods: Participants of the Australasian Colorectal Cancer Family Registry Cohort were asked to complete a questionnaire on their colorectal cancer screening in the past five years and a validated measure of mental and physical health. The association between mental and physical health and screening was determined for Australian participants aged 45-75 years who had never been diagnosed with colorectal cancer. Multivariable logistic regression was used to adjust for measured potential confounders. Results: Of the 1130 eligible participants, 819 reported colorectal cancer screening in the past five years (72%). After adjusting for potential confounders, there was no evidence that overall mental or physical health was associated with colorectal cancer screening. However, one specific scale, general health, was positively associated with colorectal cancer screening (p=0.014) with those reporting higher levels of general health undergoing screening.Conclusion: We found limited evidence that mental and physical health, as measured by a short questionnaire, are associated with colorectal cancer screening. A potential limitation is reverse causation where previous screening may have impacted mental or physical health. A more detailed study of physical and mental health as barriers or enablers of screening is needed.

Data on the temporal and spatial evolution of Sars-Cov-2, local control measures and their effects on morbidity and mortality patterns in rural Brazil are scarce. We analyzed data from case notification systems, epidemiological investigation reports, and municipal decrees in a small municipality in northeast Brazil. For spatial analysis, cases and deaths in the urban area were mapped. There were a total of 3,020 cases of COVID-19 from April 2020 to December 2021; 135 (4.5%) died. The cumulative incidence and mortality rates were 5,650.3 cases and 252.6 deaths per 100,000 population, respectively. The index case of Sars-Cov-2 in the city was diagnosed in March 2020. The first peak of cases and deaths occurred in May 2020. The second wave of infection peaked in May 2021, with the highest number of deaths in March 2021. In spatial analysis, the highest density of cases and deaths occurred in the urban area. The municipal government issued 69 decrees on restriction measures, surveillance, and maintenance of social isolation to address the spread of SarsCov-2. The spread of the Sars-Cov-2 pandemic in Itapajé mirrored the behavior observed in large metropolitan regions, from central neighborhoods to the periphery.

The concept of ecosystem services (ESs) provides a valuable approach to communicate societies' dependence on natural ecosystems, assisting in the evaluation of measures to protect vegetation in watersheds that promote water-related ESs. Vegetation cover and land use are important factors related to the capacity of ecosystems to provide soil loss regulation and sediment retention services, which are highly relevant for sediment management in watersheds draining into reservoirs with multiple water uses. This study aims to assess the relationship between potential changes in land use and land cover and the sediment retention service provided by riparian vegetation in a watershed draining into a hydroelectric reservoir in the Brazilian Cerrado. Sediment load was selected as a physical variable that affects different water uses in reservoirs, with these uses being dependent on the quality or quantity of stored water. Scenarios were analyzed to represent landscape reconfigurations from a baseline condition in order to account for the recovery of riparian vegetation by the agricultural sector, as foreseen in the Brazilian Forest Code. To map and quantify variations in annual sediment retention, the InVEST model was used, which allows estimating an integrated response of the drainage basin to large-scale land use changes over time and space. The results show that for the drainage basin of the Corumbá IV Hydroelectric Power Plant (HPP), the recovery of riparian areas occupied by annual crops has the potential to generate greater benefits to water use in the reservoir. In the studied catchment area, 14% of the total vegetation deficit in riparian areas is occupied by crops, while 86% is occupied by pastures. This highlights the buffering role of riparian vegetation as an effective practice for managing sediment flows originating from sheet erosion in agricultural landscapes. The methodology employed in this study allows for the quantification and mapping of the effects of soil and water conservation measures in river basins. This enables the prioritization of sectoral efforts for the restoration of native vegetation, considering the highest returns in benefits perceived by water users affected by sediment input in reservoirs. The study's results reinforce the importance of conserving vegetation in riparian areas and their surroundings for sediment retention, highlighting the role of these areas as assets in providing water-related ecosystem services.

A wealth of Full Waveform (FW) LiDAR data are available to the public from different sources, which is poised to boost the extensive application of FW LiDAR data. However, we lack a handy and open source tool that can be used by potential users for processing and analyzing FW LiDAR data. To this end, we introduce waveformlidar, an R package dedicated to FW LiDAR processing, analysis and visualization as a solution to the constraint. Specifically, this package provides several commonly used waveform processing methods such as Gaussian, adaptive Gaussian and Weibull decompositions, and deconvolution approaches (Gold and Richard-Lucy (RL)) with users’ customized settings. In addition, we also developed functions to derive commonly used waveform metrics for characterizing vegetation structure. Moreover, a new way to directly visualize FW LiDAR data is developed through converting waveforms into points to form the Hyper Point cloud (HPC), which can be easily adopted and subsequently analyzed with existing discrete-return LiDAR processing tools such as LAStools and FUSION. Basic explorations of the HPC such as 3D voxelization of the HPC and conversion from original waveforms to composite waveforms are also available in this package. All of these functions are developed based on small-footprint FW LiDAR data, but they can be easily transplanted to the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) and Global Ecosystem Dynamics Investigation (GEDI) data analysis. It is anticipated that these functions will facilitate the widespread use of FW LiDAR and be beneficial for better estimating biomass and characterizing vegetation structure at various scales. The package and code examples can be found at https://github.com/tankwin08/waveformlidar.

Aim: Streptococcus pneumoniae and influenza H1N1 virus are common organisms associated with human infections. These infections could play a significant role in immune regulation. The study was performed to analyse the genome sequences of these organisms with human genome and study its functional significance. Methods: The study was performed to analyse the overlapping of genome sequences in Streptococcus pneumoniae and Influenza (H1N1) virus against human genome sequences by BLASTn sequence analysis. The alignments are studied against the corresponding genes for their functional significance with DAVID and NDEx software.Results: Several hits or overlapping nucleotide segments were identified. Between streptococcus and homo sapiens 287 overlaps were identified, and among influenza and homo sapiens 124 hits were identified. A wide range of functional significance of these genes were identified, and the results are presented in this study. The results show insights into functional pathways and biological activities associated with the respective vaccinations or infections by these microorganisms. Conclusion: The common organisms like Streptococcus pneumoniae and Influenza H1N1 virus actively interact with the immune system and result in a wide range of immune regulations.

We propose a conceptual model for the closeness parameter $\epsilon$, which characterizes exotic compact objects (ECOs). To estimate $\epsilon$, a thin spherical dust shell is considered, which gravitationally contracts from a specific position $r(t_{0})$ to near its gravitational radius $r(t_{2})=r_{s} + \epsilon$, in a finite time $t_{2}$, measured in the frame of a fiducial observer (FIDO). For an external observer, the shell’s kinematics is characterized by two clearly distinguishable phases: one of rapid contraction, where the shell is far away from the gravitational radius, $r(t_{0})\gg r_{s}$, and a second phase quasi-stationary, $r(t)\sim r_{s}$, where all of the shell’s mass is concentrated around the associated horizon, such that for a FIDO, a black hole (BH)is undistinguishable from a shell configured as a black shell (BS). \\ In the semi-classical approximation $E\ll \kappa_{0}l_{p}^{2}$ and tends to zero when the observation time of collapse $t_{2}$, measured by FIDO, tends to infinity; $\kappa_{0}$ and $l_{p}$ are surface gravity and Planck length, respectively. The quantum effects are significant when $\epsilon\ll r(t_{2})$ and $\epsilon$ tends to $\kappa_{0}l_{p}^{2}$. \\ Without knowing details on quantum gravity, parameter $\epsilon$ is calculated, which, in general, allows distinguishing the ECOs from BHs. Specifically, a BS (ECO) is undistinguishable from a BH.

The human body supports the growth of a wide array of microbial communities in various niches, such as the oral cavity, gastro-intestinal and urogenital tracts and on the surface of the skin. These host associated microbial communities include yet-un-cultivable bacteria and are influenced by various factors. Together, these communities of bacteria are referred to as the human microbiome. Human oral microbiome consists of both symbionts and pathobionts. Deviation from symbiosis among the bacterial community leads to “dysbiosis”—a state of community disturbance. Dysbiosis occurs due to many confounding factors that predispose to a shift in the composition and relative abundance of microbial communities. Dysbiotic communities have been a major cause for many microbiomes related systemic infections. Such dysbiosis is directed by certain important pathogens called the “keystone pathogens” that could modulate community microbiome variations. One such persistent infection is oral infection, mainly periodontitis, where a wide array of causal organisms has been implied to systemic infections such as cardio vascular disease, diabetes mellitus, rheumatoid arthritis and Alzheimer’s disease. The keystone pathogens co-occur with many yet-cultivable bacteria and their interactions lead to dysbiosis. This has been the focus of recent research. While immune evasion is one of the major modes that lead to dysbiosis, new processes and new virulence factors of bacteria have been shown to be involved in this important process of that determine disease or health state. This review focuses on such dysbiotic communities, their interactions and their virulence factors that predispose the host to other systemic implications.

Identification and segmentation of rock particles is very important in geology, mining, engineering construction, and environmental monitoring. Traditional methods for recognizing the rock particle characteristics are time-consuming, labor-intensive, and limited by the geographical scope of the sampling sites, which makes it more difficult to represent the spatial distribution of the rock particles accurately. Recent advancements in deep learning techniques offer promising solutions to automate this process. This study aims at utilizing state-of-the-art (SOTA) Mask R-CNN deep learning algorithm from the Detectron2 framework, to capture global features of rocks that will enable the recognition of rock particles more efficiently, just from having the rock images. These images are subject to image processing techniques such as a Gaussian filter, to denoise and smoothen the image, and an Illumination Adaptive Transformer (IAT) framework, to adjust the lighting exposure; all of which add to improve the quality of the image dataset. Afterward, the Mask R-CNN and Detectron2 models are utilized in training the images using transfer learning. Experimental results from evaluating the performance of the proposed algorithms showcase the effectiveness of the approach, thereby highlighting its potential to revolutionize rock particle segmentation across various domains.

(R)-(+)-3,5-Dinitro-N-(1-phenylethyl)benzothioamide 1 is a potential chiral solvating agent (CSA) for the spectral resolution of enantiomers by 1H NMR spectroscopy. The single enantiomer of 1 was synthesized from commercially (R)-(+)-a-methylbenzylamine 2 in two-steps with 85% yield.

We study certain function algebras and their operator algebra completions on r-discrete abelian groupoids, the corresponding conditional expectations, maximal abelian subalgebras (masa) and eigen-functionals.

Derelict asbestos mine sites in South Africa pose a considerable risk to human, environmental and socio-economic health. Comprehensive mineralogical and geochemical datasets for the existing hazardous geological materials still exposed in Southern African derelict asbestos mines remain largely non-existent, as very little published and up-to-date literature is available. In this study three representative types of asbestos mineral fibres from derelict asbestos mines in Southern Africa, namely chrysotile from Havelock mine, amosite from Penge mine and crocidolite from Prieska mine are characterized mineralogically and geochemically to critically evaluate real-life hazards in rural and asbestos-fibre contaminated regions. The samples were examined using polarising light microscopy, X-ray fluorescence (major and trace elemental analysis), X-ray diffraction (including Rietveld refinement), specific surface area analyses and bio-durability tests. Data are discussed in view of their potential toxicities on both human health and the environment in the context of developing countries. Finally, information on the mineralogical and geochemical status of asbestos mine waste and its importance as baseline data for rehabilitation considerations is also evaluated.

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of software testing within quality assurance frameworks. However, due to its complexity and resource intensity, the exhaustive nature of comprehensive testing often surpasses budget constraints. This research utilizes a machine learning (ML) model to enhance software testing decisions by pinpointing areas most susceptible to defects and optimizing scarce resource allocation. Previous studies have shown promising results using cost-sensitive training to refine ML models, improving predictive accuracy by reducing false negatives through addressing class imbalances in defect prediction datasets. This approach facilitates more targeted and effective testing efforts. Nevertheless, the generalizability of these models across different projects (cross-project) and programming languages (cross-language) remained untested. This study validates the model's applicability across diverse development environments by integrating various datasets from distinct projects into a unified, using a more interpretable ML approach. The results demonstrate that ML can support software testing decisions, enabling teams to identify up to seven times more defective modules with the same testing effort as a benchmark.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

Satellite communication (Satcom) is an artificial geostationary satellite that facilitates a wide range of telecommunications. Considering its quality of service (QoS) and security is crucial in government/military applications. The most challenging situation for efficient Satcom is radio frequency interference (RFI) environment. Thus, it is necessary to ensure that transmissions are incorruptible or at least sense the quality of its spectrum. This paper presents a new method to recognize received signal characteristics using a hierarchical classification in a multi-layer perceptron neural network. We consider signal modulation and the type of RFI as the characteristics of a real-time video stream transmitted in the direct broadcast satellite. Four different modulation types are investigated in this study. Moreover, the combination of the communication signal with various kinds of interference and their effects on the classification method widely have been analyzed. Besides, two robust feature selection techniques have been developed to reduce the data-set dimensional, which leads to optimizing the classification process. The results show that the Genetic Algorithm (GA) slightly outperforms Principal Component Analysis (PCA) for feature selection. Furthermore, the robustness of the proposed techniques is assessed to detect unknown signals at different signal to noise ratios.

Prior research shows that individuals who have exhibited antisocial behavior are in poorer health than their same-aged peers. A major driver of poor health is aging itself, yet research has not investigated relationships between offending trajectories and biological aging. We tested the hypothesis that individuals following a life-course persistent (LCP) antisocial trajectory show accelerated aging in midlife. Trajectories of antisocial behavior from age 7 to 26 years were studied in the Dunedin Multidisciplinary Health and Development Study, a population-representative birth cohort (N=1037). Signs of aging were assessed at age 45 years using previously validated measures including biomarkers, clinical tests, and self-reports. First, we tested whether the association between antisocial behavior trajectories and midlife signs of faster aging represented a decline from initial childhood health. We then tested whether decline was attributable to tobacco smoking, antipsychotic medication use, debilitating illnesses in adulthood, adverse exposures in childhood (maltreatment, socioeconomic disadvantage) and adulthood (incarceration), and to childhood self-control difficulties. Study members with a history of antisocial behavior had a significantly faster pace of biological aging by midlife, and this was most evident among individuals following the LCP trajectory (β, .22, 95%CI, .14, .28, p.001). This amounted to 4.3 extra years of biological aging between ages 25-45 years for Study members following the LCP trajectory compared to low-antisocial trajectory individuals. LCP offenders also experienced more midlife difficulties with hearing (β, -.14, 95%CI, -.21, -.08, p.001), balance (β, -.13, 95%CI, -.18, -.06, p.001), gait speed (β, -.18, 95%CI, -.24, -.10, p.001), and cognitive functioning (β, -.25, 95%CI, -.31, -.18, p.001). Associations represented a decline from childhood health. Associations persisted after controlling individually for tobacco smoking, antipsychotic medication use, midlife illnesses, maltreatment, socioeconomic status, incarceration, and childhood self-control difficulties. However, the cumulative effect of these lifestyle characteristics together explained why LCP offenders have a faster Pace of Aging than their peers. While older adults typically age-out of crime, LCP offenders will likely age-into the healthcare system earlier than their chronologically same-aged peers. Preventing young people from offending is likely to have substantial benefits for health, and people engaging in a LCP trajectory of antisocial behaviors might be the most in need of health promotion programs. We offer prevention and intervention strategies to reduce the financial burden of offenders on health care systems and improve their wellbeing.

With the rapid development of the Internet industry, the problem of information overload has arisen due to the abundance of information available online. Recommendation algorithms, as the core of recommendation systems, have been attracting much attention and are a hot topic of research for many experts and scholars. The classical recommendation algorithms are mainly divided into three major categories: collaborative filtering recommendation algorithms, content-based recommendation algorithms, and hybrid-based recommendation algorithms. Although these algorithms are widely used in various fields, with the proliferation of information, these traditional recommendation algorithms are no longer able to meet the needs of the times. To address this issue, recommendation systems have been developed to provide users with personalized and relevant information or products. Despite the wide use of recommendation algorithms, such as collaborative filtering, content-based filtering, and hybrid approaches, traditional recommendation algorithms have limitations and are no longer suitable for meeting the demands of the times. This paper proposes a new recommendation algorithm, SFRRG, that fuses structure and feature information in graph neural networks to improve the performance of the recommendation system in rating prediction. The effectiveness of the proposed algorithm is demonstrated through experiments on various data sets and compared with existing recommendation algorithms.

The continued application of organochlorine pesticides (OCPs) in indoor residual spraying has posed significant threat to human health in Northern part of South Africa, despite its ban. In this study, we investigated the occurrence and spatial distribution of DDTs and its metabolites in surface soil (30 samples) collected in and around the spray homesteads; demarcated into three concentric zones A, B, C in Tshilamusi Vhembe district, South Africa. DDTs were the most abundant of all the OCPs chemicals found in soil samples. The concentrations of DDT range from 12.19 to 65.69 µg/kg, with the highest occurring at zone A which is the zone of application. DDTs and all its metabolites considered in this study were found in appreciable concentrations in soil of Zones B and C, far from spray sites. The results showed a strong correlation between distance and concentration levels of DDTs and its metabolites. However, there is a need for proper monitoring of OCPs chemicals in other environmental matrices as well as relevant agencies enforcing strict adherence to regulations on consumption of OCPs.

This article discusses an international scientific expedition to Greenland that researched geography, geodesy, botany, and glaciology of the area. The results here focus on the geodetic and glaciological results obtained with the eBee drone in the eastern part of Greenland at the front of the Knud Rasmussen glacier. From two overflights nearby the glacier front, it was possible to obtain the speed of the glacier flow and the distribution of velocities in the glacier stream. The results correlate with other measurement methods and this technology has been shown as feasible. Of course, there are more accurate and long-term options or devices for monitoring the flow of glaciers. In this case of short-term visits to the site, the possibility of using a drone is interesting and the results show not only the flow speed of the glacier, but also the shape and structure from a height of up to 200m. The second part of the paper focuses on the analysis of modern satellite images of the Knud Rasmussen glacier from Google Earth (Landsat series 1984-2016) and a comparison with historical aerial images from 1932-1933. Experimentally, historical images were processed photogrammetrically into a 3D model.

The term Conjugated Linoleic Acid (CLA) refers generically to a class of positional and geometric conjugated dienoic isomers of linoleic acid. Among the isomers of linoleic acid cis9, trans11-CLA (c9, t11-CLA) and trans10, cis12-CLA (t10, c12-CLA) are found to be bio-logically active isomers, and they occur naturally in milk, dairy products and meat from ruminants. In addition, some vegetables and some sea-foods have also been reported to contain CLA. Although the CLA levels in these natural sources are insufficient to confer the essential health benefits, anti-carcinogenic or anti-cancer effects are of current interest. In the rumen, CLA is an intermediate of isomerization and the biohydrogenation process of linoleic acid to stearic acid conducted by ruminal microorganisms. In addition to rumen bacteria, some other bacteria, such as Propionibacterium, Bifidobacterium and some lactic acid bacteria (LAB) are also capable of producing CLA. In this regard, Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) has demon-strated the ability to produce CLA isomers from linoleic acid by multiple enzymatic activi-ties, including hydration, dehydration, and isomerization. L. plantarum is one of the most versatile species of LAB and the bacterium is widely used in the food industry as a micro-bial food culture. The studies reviewed in this article reveal how, in the production of some fermented foods, the use of appropriate strains of L. plantarum, as a starter or additional culture, can be considered a critical factor in the design of new CLA-enriched functional foods.

Human T-lymphotropic virus type 1 (HTLV-1)–associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a slowly progressive spinal cord disorder with no effective treatment. There is much of interest in developing potential biomarkers for predicting the pathogenesis of HAM/TSP disorder. This study used Illumina massive parallel sequencing (MPS) technology to assess the cellular global noncoding RNAome expression profile in HAM/TSP patients (n = 10), asymptomatic HTLV-1 infected carriers (ASP, n = 8), and a second group of healthy controls (n = 5). Using various bioinformatics tools, the sRNA MPS reads were aligned, annotated, and profiled. There were 251 known and 50 potential novel sRNAs among the 402 detected sRNAs in the HAM and ASP groups versus the HC group. Sixty-eight known sRNAs were found to be significantly different between the ASP and HAM groups. In HAM vs ASP subjects, 88 mature miRNAs were downregulated. Three of these miRs (hsa-miR-185-5p, 32-5p, and 192-5p) have the potential to be used as biomarkers for predicting the pathogenesis of HAM/TSP. The top seven deregulated miRS target genes were linked to a variety of biological processes and molecular functions. Relevant reactome pathways to our findings provide a rich source of data and an opportunity to further understand sRNA regulation and function in HTLV-1 pathophysiology.

Symmetry concepts in parametrized dynamical systems may reduce the number of external parameters by a suitable normalization prescription. If, under the action of a symmetry group G, parameter space A becomes a (locally) trivial principal bundle, A ~ A/G x G, then the normalized dynamics only depends on the quotient A/G. In this way, the dynamics of fractional variables in homogeneous epidemic SI(R)S models, with standard incidence, absence of R-susceptibility and compartment independent birth and death rates, turns out to be isomorphic to (a marginally extended version of) Hethcote's classic endemic model, first presented in 1973. The paper studies a 10-parameter master model with constant and I -linear vaccination rates, vertical transmission and a vaccination rate for susceptible newborns. As recently shown by the author, all demographic parameters are redundant. After adjusting time scale, the remaining 5-parameter model admits a 3-dimensional abelian scaling symmetry. By normalization we end up with Hethcote's extended 2-parameter model. Thus, in view of symmetry concepts, reproving theorems on endemic bifurcation and stability in such models becomes needless.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

The authors previously found a model of universal quantum computation by making use of the coset structure of subgroups of a free group $G$ with relations. A valid subgroup $H$ of index $d$ in $G$ leads to a \lq magic' state $\left|\psi\right\rangle$ in $d$-dimensional Hilbert space that encodes a minimal informationally complete quantum measurement (or MIC), possibly carrying a finite \lq contextual' geometry. In the present work, we choose $G$ as the fundamental group $\pi_1(V)$ of an exotic $4$-manifold $V$, more precisely a \lq small exotic' (space-time) $R^4$ (that is homeomorphic and isometric, but not diffeomorphic to the Euclidean $\mathbb{R}^4$). Our selected example, due to to S. Akbulut and R.~E. Gompf, has two remarkable properties: (a) it shows the occurence of standard contextual geometries such as the Fano plane (at index $7$), Mermin's pentagram (at index $10$), the two-qubit commutation picture $GQ(2,2)$ (at index $15$) as well as the combinatorial Grassmannian Gr$(2,8)$ (at index $28$) , (b) it allows the interpretation of MICs measurements as arising from such exotic (space-time) $R^4$'s. Our new picture relating a topological quantum computing and exotic space-time is also intended to become an approach of \lq quantum gravity'.

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson’s R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.