It has been argued that the historical nature of evolution makes it a highly path-dependent process. Under this view, the outcome of evolutionary dynamics could have resulted in organisms with different forms and functions. At the same time, there is ample evidence that convergence and constraints strongly limit the domain of the potential design principles that evolution can achieve. Are these limitations relevant in shaping the fabric of the possible? Here, we argue that fundamental constraints are associated with the logic of living matter. We illustrate this idea by considering the thermodynamic properties of living systems, the linear nature of molecular information, the cellular nature of the building blocks of life, multicellularity and development, the threshold nature of computations in cognitive systems, and the discrete nature of the architecture of ecosystems. In all these examples, we present available evidence and suggest potential avenues towards a well-defined theoretical formulation.

This study was designed to examine the relationships among the impulsivity construct as a personality trait, the dehydroepiandrosterone sulfate (DHEA-S), and testosterone in a sample of 120 healthy middle-aged males. (Mage = 44.39; SD = 12.88). The sum of the three BIS-11 scales, the SR and the five UPPS-P scales correlated with DHEA-S .23 (p < .006) and testosterone .19 (p < .04), controlling for age. Partial correlations showed that DHEA-S is significantly related to Motor impulsivity (.24; p < .008), Sensitivity to Reward (.29; p < .002) and Lack of premeditation (.26; p < .05) and, to a lesser extent, Sensation Seeking (.19; p < .04) and Positive Urgency (.19; p < .04). Testosterone correlated with Attention impulsivity (.18; p < .04), Sensation Seeking (.18; p < .04), and Positive Urgency (.22; p < .01). Sensitivity to Reward, Negative Urgency and Positive Urgency were significant predictors of DHEA-S (R2 = .28), and Positive Urgency for testosterone (R2 = .09). Non-parametric LOESS graphical analysis for local regression allowed us to visualize the non-linear relationships between the impulsivity scales with the two androgens, including non-significant trends. We discuss the implications of these results for biological impulsive personality traits, the limitations of our analyses, and the possible development of future research.

Laser in situ keratomileusis (LASIK) is the gold standard in the surgical correction of refractive errors on the cornea. It entails the creation of a superficial hinged corneal flap by a femtosecond laser, ablation of the underlying stromal bed by an excimer laser, and reposition of the flap. The corneal flap can be build in a 2-dimension (2D) fashion with tapered edges, or in a 3-dimension (3D) fashion, with angled sidecut. The latter reduces the risk of flap dislocation and infiltration of epithelial cells. This retrospective study compares with optical coherence tomography 3D and 2D flaps, and respective intra- and early post-operative complications. Four hundred consecutive eyes were included, 200 for each group. In the 3D group, the mean edge angle was 92°. The procedure was in average 5.2 seconds slower in the 3D group (p=0). Non visually significant flap folds were found in 13 eyes of the 2D group and in 7 eyes of the 3D group (p= 0.17). An intracorneal opaque bubble layer induced by laser photodisruption was more commonly observed in the 3D group (9 eyes vs. 2; p=0.03). In conclusion, the creation of a LASIK flap by a 3D-femtosecond laser cut was safe and effective.

Reactions of Co(OAc)24H2O, N‚N'-bis(3-pyridylmethyl)oxalamide (L) and 4,4’-sulfonyldibenzoic acid (H2SDA) afforded four coordination polymers with the same mixed ligands, {[Co(L)(SDA)(H2O)2]·H2O·CH3OH}n, 1, {[Co(L)0.5(SDA)]·2H2O·0.5L}n, 2, {[Co(L)1.5(SDA)(H2O)]·H2O}n, 3, and {[Co2(L)1.5(SDA)2(H2O)2]·4H2O}n, 4, which have been structurally characterized by using single crystal X-ray crystallography. Complexes 1 – 4 are 2D layers, revealing the topologies of sql, 2,6L1, (4,4)Ia and 6L12, respectively, and demonstrating that the metal to ligand ratio, solvent system and reaction temperature are important in determining the structural diversity. Immersion of these complexes into various solvents show that the structural types govern the chemical stabilities of 1 – 4. Reversible structural transformation can be shown for complexes 1 and 2 upon solvent removal and adsorption, while those of 3 and 4 are irreversible.

This study investigates the effect of scaffold architecture on bone regeneration, focusing on 3D-printed polylactic acid-bioceramic calcium phosphate (PLA-bioCaP) composite scaffolds in rabbit femoral condyle critical defects. To assess their influence on bone healing and scaffold performance, we explored two distinct scaffold designs, alternate and helical laydown patterns. The scaffolds were meticulously characterized for pore size, strut thickness, porosity, pore accessibility, and mechanical properties. The in vivo efficacy of these scaffolds was evaluated using a rabbit femoral condyle critical defect model. Our findings indicate that both scaffold architectures are biocompatible and support bone formation. The helical scaffolds, characterized by larger pore sizes and higher porosity, demonstrated significantly greater bone regeneration than the alternate structures. However, their lower mechanical strength presented limitations for use in load-bearing sites. This study highlights the importance of scaffold architecture in bone tissue engineering and underscores the need to balance porosity and mechanical strength for optimal bone regeneration. The findings provide crucial insights for the design of 3D- printed scaffolds in clinical applications, particularly in the context of critical-sized bone defects. The study also outlines potential areas for future research, including exploring hybrid scaffold designs to achieve optimal porosity without compromising mechanical integrity.

Successful fertilization treatments targeted to improve stand productivity while reducing operational complexities and cost depend on a clear understanding of soil nutrient availability under varying environmental conditions. Soil nutrient data collected from 154 forest sites throughout the Inland Northwest, USA were analyzed to examine soil nutrient characteristics on different geologic soil parent materials and to rank soil fertility. Results show that soil parent material explains significant differences in soil nutrient availability. Soils developed from volcanic rocks have the highest CEC and are relatively high in P, K, S, Mg, Cu, Ca, and B, but generally poor in N. Forest soils developed from plutonic rocks exhibit the lowest CEC and are low in N, S, K, Mg, Cu, and Ca, but higher in P. Some soils located on mixed glacial till are low only in K, Cu, Mg, and Ca, but many glacial soils are relatively rich in other nutrients, albeit the second lowest CEC. Soils developed from metasedimentary and sedimentary rocks are among those with lowest soil nutrient availability for P and B. Sulfur was found to have the highest concentrations in metasedimentary influenced soils and the least in sedimentary derived soils. Our results should be useful in designing site-specific fertilizer and nutrient management prescriptions for forest stands growing on soils developed from these major geologies within the Inland Northwest region of the United States.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) continues to wreak havoc threatening the public health services and imposing economic collapse worldwide. Tailoring public health responses to the SARS-CoV-2 pandemic depends on understanding the mechanism of viral replication, disease pathogenesis, and accurately identifying acute infections and mapping the spreading risk of hotspots across the globe. However, effective identification and isolation of persons with asymptomatic and mild SARS-CoV-2 infections remain the major obstacles to efforts in controlling the SARS-CoV-2 spread and hence the pandemic. Understanding the mechanism of persistent viral shedding, reinfection, and the post-acute sequalae of SARS-CoV-2 infection (PASC) is crucial in our efforts to combat the pandemic and provide better care and rehabilitation to survivors. Here we present a living literature review on SARS-CoV-2 viral persistence, reinfection and PASC. We also highlight potential areas of research to uncover putative links between viral persistence, intra-host evolution, host immune status, and protective immunity to guide and direct future basic science and clinical research priorities.

This research provides an in-depth analysis of drought impacts in West Pokot, Kenya, utilizing both remote sensing surveys and focus group discussions. The study commenced by assessing the impact of drought on vegetation health via spatial sensors. It then utilized surveys and focus group discussions (FGDs) to engage farmers from the most drought-affected areas in Kacheliba and Sigor sub-counties. The analysis of remote sensing data from 1990 to 2022 highlighted that Sigor and Kacheliba experienced significant drought events during the years 1995, 2000, 2002, 2005, and 2009, and 1991, 1995, 2000, 2005, and 2019, respectively. This study delves into both the meteorological and socio-economic effects on local communities. Using the Multinomial Logistic Regression (MLR) model with the glm function, the research uncovered the impacts of so-cio-economic factors and agricultural practices on household livestock production. Additionally, the study employed Multiple Correspondence Analysis (MCA) to explore the dynamics between livestock production, community resilience, and crop production. The findings underscore the urgent need for tailored interventions to enhance community resilience in the face of increasing climatic extremes, serving as a blueprint for similar arid and semi-arid regions worldwide.

Background: Fullerenes and metallofullerenes can be considered promising nanopharmaceuticals themselves and as a basis for chemical modification. As reactive oxygen species homeostasis plays a vital role in cells, the study of their effect on genes involved in oxidative stress and anti-inflammatory response is of particular importance. Methods: Human fetal lung fibroblasts were incubated with aqueous dispersions of C60, C70, and Gd@C82 in concentrations of 5 nM and 1.5 µM for 1, 3, 24, and 72 hours. Cell viability, intracellular ROS, NOX4, NFκB, PRAR-γ, NRF2, heme oxygenase 1, and NAD(P)H quinone dehydrogenase 1 expression have been studied. Results &amp; conclusion: The aqueous dispersions of C60, C70, and Gd@C82 fullerenes are active participants in ROS homeostasis. Low and high concentrations of AFDs have similar effects. C70 was the most inert substance, C60 was the most active substance. All AFDs have both a “prooxidant” and “antioxidant” effect, but with a different balance. Gd@C82 was a substance with more pronounced antioxidant and anti-inflammatory properties, while C70 had more pronounced “prooxidant” properties.

With the widespread use of the Internet of Things, underwater control and monitoring systems for purposes such as ocean data sampling, natural disaster prevention, underwater surveillance, submarine exploration, and the like have become a popular and challenging topic in computers. So far, various topology control and routing solutions have been proposed for these networks. However, as technology expands and applications grow, so does the need for a stable underwater communication platform. On the other hand, underwater communication is associated with challenges such as node mobility, long propagation delays, low bandwidth, limited resources, and high error rates. In this research, for the first time, a topology control platform based on the RPL tree is modelled by applying its structural changes underwater. The proposed RPLUW methods in the case of RPLUWM fixed nodes are introduced to support the mobility of nodes underwater. Flexible objective functions, utilisation of decision-making systems, and application of control schedules in these methods have increased network life, reduced overhead, and increased node efficiency. The simulation results of the proposed method, in comparison with recent methods in this field, show an increase in network efficiency.

Emergence of COVID-19 had profound impact on global stock markets, including Indian mar-ket. Key indices like NIFTY50 and Sensex dropped by approximately 40% within two months in 2020, which also affected major mutual funds, leading to significant depreciation of their Net Asset Value. Securities and Exchange Board of India (SEBI) allows mutual funds to use deriva-tives for hedging purposes, capped at 100% of the scheme's net assets covering debt, equity, and derivatives. However, circular amendment by SEBI in January-2019 permitted covered call strat-egies on constituent stocks of Sensex and NIFTY50 for mutual fund schemes, excluding ETFs and Index Funds. This study investigated whether mutual funds increased their derivative us-age as risk mitigation strategy during COVID-19 pandemic, analyzing derivative holdings from 2019-2023. Surprisingly, findings indicated a decline in derivative holdings in 2020 compared to pre-pandemic levels. Statistical tests and performance evaluation metrics such as T-test, F-test, Treynor Ratio, Sharpe Ratio, and Jensen's calculations were employed to assess mutual fund performance. Although derivative-holding mutual funds didn't outperform benchmarks in aver-age returns, it showcased significantly reduced volatility, offering investors favorable risk-return trade-offs. research sheds light on derivative utilization in Mutual Fund industry, potentially in-forming regulators, fund managers, and investors in their decision-making

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

In the current scenario, liver abnormalities are one of the most serious public health concerns. Cirrhosis of the liver is one of the foremost causes of demise from liver diseases. To accurately predict the status of liver cirrhosis, physicians frequently use automated computer-aided approaches. In this paper the clustering techniques like Fuzzy C Means (FCM), Possibilistic Fuzzy C Means (PFCM), Possibilistic C Means (PCM), Sample Entropy features are extracted from normal and cirrhotic liver ultrasonic Images. The extracted features are classified as normal and Cirrhosis one through Gaussian Mixture Model(GMM), Softmax Dis(SDC), Harmonic Search Algorithm (HSA), SVM(Linear), SVM(RBF), SVM(Polynomial), Artificial Algae Optimization (AAO) and hybrid classifier Artificial Algae Optimization (AAO) with Gaussian Mixture Mode (GMM). The classifiers performances are compared based on Accuracy, F1 Score, MCC, F Measure, Error rate and Jaccard metric (JM).The hybrid classifier AAO GMM with PFCM feature outperforms than other classifiers and attained an accuracy of 99.03 % with MCC of 0.90

We report a novel dual-band barrier infrared detector (DBIRD) design using type-II superlattices (T2SLs). The DBIRD structure consists of back-to-back barrier diodes: a "blue channel" (BC) diode which has an nBp architecture, an n-type layer of larger bandgap for absorbing blue band infrared/barrier/p-type layer, and a "red channel" (RC) diode which has an pBn architecture, a p-type layer of smaller bandgap for absorbing red band infrared/barrier/n-type layer. Each has a unipolar barrier using a T2SL lattice matched to a GaSb substrate to impede the flow of majority carriers from the absorbing layer. Each channel in the DBIRD can be independently accessed with a low bias voltage, as is preferable for high-speed thermal imaging. Device modeling of DBIRDs and simulation results of the current-voltage characteristics under dark and illuminated conditions are also presented. They predict that dual-band operation of the DBIRD will produce low dark currents and 27-33% quantum efficiencies for the in-band photons in the BC with λc=5.58 μm, and a nearly-constant 33% in the RC with λc=8.05 μm. The spectral quantum efficiency of the BC for 500 K blackbody radiation is approximately 20% over the range of λ=3 − 4.2 μm, while that of the RC has a peak of 42% at 5.7 μm. The DBIRD may provide improved high-speed dual-band imaging in comparison with NBn dual-band detectors.

Transport electrification is essential for reducing CO2 emissions, and technologies such as hybrid and range-extended electric vehicles will play a crucial transitional role. Such vehicles employ an internal combustion engine for on-board chemical energy conversion. The Wankel rotary engine should be an excellent candidate for this purpose, offering high power-to-weight ratio, simplicity, compactness, perfect balance, and low cost. Until recently, however, it has not been in production in the automotive market, due, in part, to relatively low combustion efficiency and high fuel consumption and unburnt hydrocarbon emissions, which can be traced to constraints on flame speed, an elongated combustion chamber, and relatively low compression ratios. This work uses large-eddy simulation to study the in-chamber flow in a peripherally ported 225cc Wankel rotary engine, providing insight into these limitations. Flow structures created during the intake phase play a key role in turbulence production but presence of the pinch point inherent to Wankel engine combustion chambers inhibits flame propagation. Two efficiency-enhancement technologies are introduced as disruptive solutions: (i) pre-chamber jet ignition and (ii) the two-stage rotary engine. These concepts overcome the traditional efficiency limitations and show that Wankel rotary engine design can be further enhanced for its role as a range extender in electrified vehicles.

Wild-grown edible mushrooms are important in world diet, which are also efficient metal accumulators. Yunnan, southwest China is the main producing region with typically high geochemical metals. Environmental factors, bioaccumulation, distribution and human health risk of metals were examined in paired soil and Tricholoma matsutake (n=54). T. matsutake grows on acidified soils (pH=3.95–6.56) and metals showed strong heterogeneity with Fe, Mn, Zn and Cu ranged at 16–201, 0.046–8.58 g kg–1 and 22.6–215, 3.7–155 mg kg–1. High soil Fe content led to its great accumulation in T. matsutake (0.24–18.8 g kg–1). However, though soil Mn content was great higher than Zn and Cu, their concentrations in T. matsutake were comparable (21.1–487 vs. 38.7–329 and 24.9–217 mg kg–1). This suggested that T. matsutake prefers to accumulate Zn and Cu than Mn, and supported by bioaccumulation factor (BAF=0.32–17.1 vs. 0.006–1.69). Fe was mainly stored in stipe, while Mn, Zn and Cu were in cap, with translocation factor (TF) was 0.58 vs. 1.28–1.94. Therefore, stipe Fe showed the highest health risk index (HRI) at 1.28–26.9, followed by cap Cu (1.01–2.33), while 98–100% of Mn and Zn were risk-free. The higher concentration and greater risk of Fe was attributed to the significant effect of soil Fe content (R=0.34) and soil pH (R=–0.57). This study suggested that Fe as an essential mineral may exert toxic effects via T. matsutake consumption from geochemical high background areas.

In schizophrenia, cognition is closely linked to social competence and influences long-term prognosis. Thus, treatment should target cognitive improvement to enhance the patients’ societal adaptation. This study evaluated the effects of computer-assisted cognitive remediation therapy (CR) using RehaCom® on cognition in patients with schizophrenia. Thirty patients were randomized, with 15 assigned to the CR group and treatment usual care (TAU) and 15 to the TAU alone groups. Over 12 weeks, patients received CR twice weekly, including two computer sessions and one verbal session. Outcomes measured were cognition using the Brief Assessment of Cognition in Schizophrenia and Schizophrenia Cognition Rating Scale, intrinsic motivation using the Quality of Life Scale and Intrinsic Motivation Inventory, psychiatric symptoms using the Positive and Negative Syndrome Scale, negative symptoms using Scale for the Assessment of Negative Symptoms, and functional level using modified Global Assessment of Functioning scale for Functioning. The CR + TAU group demonstrated considerable improvements in cognition, intrinsic motivation, negative symptoms, and functional level compared to the TAU-alone group. These findings indicate that the CR using RehaCom® enhances cognition and other outcomes in schizophrenia.

The burden of chronic liver disease is globally increasing at an alarming rate. Chronic liver injury leads to liver inflammation and fibrosis (LF) as critical determinants of long-term outcomes such as cirrhosis, liver cancer and mortality. LF is a wound-healing process characterized by excessive deposition of extracellular matrix (ECM) proteins due to the activation of hepatic stellate cells (HSCs). In the healthy liver, quiescent HSCs metabolize and store retinoids. Upon fibrogenic activation, quiescent HSCs transdifferentiate into myofibroblasts, lose their vitamin A, upregulate -smooth muscle actin, and produce pro-inflammatory soluble mediators, collagens, and inhibitors of ECM degradation. Activated HSCs are the main effector cells during hepatic fibrogenesis. In addition, the accumulation and activation of profibrogenic macrophages in response to hepatocyte death play a critical role in the initiation of HSC activation and survival. The main source of myofibroblasts is resident HSCs. Activated HSCs migrate to the site of active fibrogenesis to initiate the formation of a fibrous scar. Single-cell technologies revealed that quiescent HSCs are highly homogenous, while activated HSCs/myofibroblasts are much more heterogeneous. The complex process of inflammation results from the response of various hepatic cells to hepatocellular death and inflammatory signals related to intrahepatic injury pathways or extrahepatic mediators. Inflammatory processes modulate fibrogenesis by activating HSCs and, in turn, drive immune mechanisms via cytokines and chemokines. Increasing evidence also suggests that cellular stress responses contribute to fibrogenesis. Recent data demonstrated that LF can revert even at advanced stages of cirrhosis if the underlying cause is eliminated, which inhibits the inflammatory and profibrogenic cells. However, despite numerous clinical studies on plausible drug candidates, an approved antifibrotic therapy still remains elusive. This state-of-the-art review presents cellular and molecular mechanisms involved in hepatic fibrogenesis and its resolution, as well as comprehensively discusses the drivers linking liver injury to chronic liver inflammation and LF.

To instruct interior lighting design of aviation cockpit and ensure the work efficiency and comfort of pilots, and reduce safety accidents caused by light environment and visual fatigue during flight, it is important to establish a multi-dimensional ergonomic evaluation mechanism of cockpit light environment. In this paper, by improving Jdms' mental load theory, we establish a thorough experimental scheme based on physiological workload, mental workload, work performance and physiological work performance to evaluate the cockpit ergonomic under different light environment multi-dimensionally. Firstly, 12 evaluation indexes including job accuracy, job speed, blinking, heart rate variability, average fixation time, saccadic speed, mental demand, physical demand, operational performance, time demand, degree of confusion and degree of effort are obtained through the experiment, and then the weight of each evaluation index is calculated by entropy method to construct the ergonomic evaluation model. The evaluation results of physiological workload, mental load, work performance and physiological work performance were combined to obtain the final ergonomic evaluation results. According to our experimental results, it was found that light environment for pilot to get the highest ergonomic efficiency is 1500 lx light illumination and 5000K color temperature. The results provide a reference for the ergonomic experiment of aircraft cockpit and the design of aviation cockpit lighting system.

In the last century, statistical process control has been considered a successful methodology for monitoring the variability and stability of a process over time. The analysis of variability using functional data analysis has become widespread during the early years of the 21st century. The present study proposes the implementation of a hybrid methodology called functional process control based on the functional data analysis methodology and combines its advantages with those of statistical process control, in order to provide a tool for detecting functional deviations. The phases are: (1) stabilization of processes through the identification and elimination of special causes of functional variability; (2) improvement of the process to be controlled by minimizing the common causes of functional variability; and (3) monitoring of the processes to ensure the maintenance or addition of further improvements.

The scope of this work is to empirically check and prove the practical applicability of the Primordially Hydridic Earth (hereinafter PHE) concept for early exploration of the resources of naturally occurring hydrogen. With the PHE concept postulates interpreted within the local geological, tectonic, petrological and geophysical context, the reconnaissance plan, as well as the field exploration and data acquisition programs, were put together and implemented in the field. The results obtained from the surface (

Recent research has implicated the gut microbiota in the development of lymphoma. Dysbiosis of the gut microbial community can disrupt the production of gut microbial metabolites, thereby impacting host physiology and potentially contributing to lymphoma. Dysbiosis-driven release of gut microbial metabolites such as lipopolysaccharides can promote chronic inflammation, potentially elevating the risk of lymphoma. In contrast, gut microbial metabolites, such as short-chain fatty acids, have shown promise in preclinical studies by promoting regulatory T-cell function, suppressing inflammation, and preventing lymphoma. Another metabolite, urolithin A, exhibited immunomodulatory and antiproliferative properties against lymphoma cell lines in vitro. While research on the role of gut microbial metabolites in lymphoma is limited, this article emphasizes the need to comprehend their significance, including therapeutic applications, molecular mechanisms of action, and interactions with standard chemotherapies. The article also suggests promising directions for future research in this emerging lymphoma and gut microbiome investigation field.

Thromboprophylaxis of hospitalized patients at risk of venous thromboembolism (VTE) presents challenges owing to patient heterogeneity and lack of adoption of evidence-based methods. Intuitive practices for thromboprophylaxis have resulted in many patients being inappropriately prophylaxed. Multiple interventions for thromboprophylaxis have been tested, including use of multifaceted approaches such as national VTE prevention programs with audits, use of passive alerts (either human or electronic), and more recently use of active clinical decision support (CDS) tools incorporated into electronic health records (EHRs). Multifaceted health-system interventions have shown mixed results in their ability to increase appropriate thromboprophylaxis and reduce VTE, unless mandated through a national VTE prevention program, though the latter approach is potentially costly, effort- and time-dependent. Studies utilizing passive human or electronic alerts have also shown mixed results in increasing appropriate thromboprophylaxis and reducing VTE. The use of active CDS tools holds the greatest promise, especially with further refinement and widespread implementation within various EHRs and clinical workflows. Recent-ly a universal cloud-based and EHR-agnostic CDS VTE tool revealed high adoption and effectiveness in increasing appropriate thromboprophylaxis and reducing major thromboembolism. This narrative review summarizes the literature on system-wide thromboprophylaxis interventions in hospitalized patients, with a focus on CDS tools.

Technological advances in DBS hardware and software represent a significant growth area in functional neurosurgery. These advancements have the potential to significantly enhance treatment outcomes and expand the scope of neurological disorders that can be effectively addressed through DBS interventions. The introduction of directional DBS marks a new phase in neuromodulation, offering extended benefits for patients with Parkinson's disease, more efficient optimization of clinical outcomes, and targeted treatment of refractory symptoms through data-driven approaches. Implementing a multimodal programming strategy, incorporating novel current fractionation technology and image-guided tools for lead localization and brain sensing, further reduces reliance on traditional trial-and-error programming methods, paving the way for a more predictive application of this therapy. These advancements are expected to drive the development of sophisticated closed-loop stimulation systems capable of integrating continuous data streams for improved patient care.

Aggregation of the protein α-Synuclein (αSyn) is a hallmark of Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple systems atrophy, and alleviating the extent of αSyn pathology is an attractive strategy against neurodegeneration. The engineered binding protein β-wrapin AS69 binds monomeric αSyn. AS69 reduces primary and secondary nucleation as well as fibril elongation in vitro. It also mitigates aSyn pathology in a mouse model based on intrastriatal injection of aSyn pre-formed fibrils (PFF). Since the PFF-based model does not represent all aspects of PD, we tested here whether AS69 can reduce neurodegeneration resulting from αSyn overexpression. Human A53T-αSyn was overexpressed in the mouse Substantia nigra (SN) by using recombinant adeno-associated viral vector (rAAV). AS69 was also expressed by rAAV transduction. Behavioral tests and immunofluorescence stainings were used as outcomes.Transduction with rAAV-αSyn resulted in αSyn pathology as reported by phospho-αSyn staining and caused degeneration of dopaminergic neurons in the SN. The co-expression of rAAV-AS69 did not reduce αSyn pathology or degeneration of dopaminergic neurons. We conclude that αSyn monomer binding by rAAV-AS69 was insufficient to protect from aSyn pathology resulting from αSyn overexpression.

Human-elephant conflict poses serious conservation challenge in Asia and Africa. We deployed an AI-based camera-alert system in a conflict hotspot in West Bengal, India that accurately detected elephants near villages (266 events) and transmitted real-time alerts ( = 42 seconds). Among detections of separate age and sex classes, lone adult bulls were the most prone to conflict. Real-time alerts permitted rapid response by field personnel to prevent conflict at the site ( = 18.2, SD = 12.4 min to arrival). Frequent detections of humans (33,217 events) on elephant trails highlighted the value of real-time alerts. Four human fatalities and five serious injuries occurred in the study area over a two-year period prior, but none during the study (2023-2024) after deploying the AI-alerting system. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to other conflict-pronespecies to promote coexistence.

Acute myeloid leukemias (AMLs) are heterogeneous hematologic cancers that occur prevalently in older patients as the result of a complex pathobiology. The clinical outcomes of older patients with AML, often unsuitable for intensive chemotherapy and allogeneic stem cell transplantation, are generally disappointing. However, recent advances in understanding molecular pathogenesis and other biological mechanisms recognized in AML development and progression have changed the treatment approach, especially for this particularly vulnerable category of patients. Indeed, non-intensive biologically tailored approaches, such as combining venetoclax with hypomethylating agents, have changed the therapeutic paradigm in this field. Moreover, other promising compounds and treatment strategies are currently under advanced clinical development. This article delves into the latest biological understanding and therapeutic advances in the clinical management of older AML patients into new conceptual frameworks that progressively transform the clinical practice in this challenging setting.

Some studies investigated the relationship between frequency domain analysis of heart rate variability and the cognitive performance at the Stroop task. We propose a combined assessment also of trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac and motor variables based on a principal component analysis. We also assessed the change on this result after an intervention of two months aiming at improving the perception-action link. At baseline, the PCA correctly identified 3 components: one related to cardiac variables, one to trunk motion and one to the performance of Stroop task. After the intervention, only two components were found with trunk symmetry and range of motion, accuracy and time to complete the Stroop task and low frequency heart rate variability aggregated in a single component by PCA. It suggested that this protocol was effective in investigating the embodied cognition and we defined this approach as “embodimetrics”.

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortage. In response to this pressing issue, this study provides a comprehensive as-sessment of water supply, demand and balance within the Cauto River Basin, considering the baseline and projected socio-economic and climatic conditions by coupling of SWAT and WEAP models. The obtained results reveal that the annual flow in the CRB is projected to slightly de-crease (2.5%) in which the reduction in the rainy season (3.1%) is higher than that in the dry sea-son (1.3%). Total water demand in the baseline scenario is around 1.194 billion m3, dominated by agriculture (96%), with rice crop requiring nearly half. For the future scenario of 2050, the study shows a 16.6% surge in demand to 1.394 billion m3, driven by climate change and agricultural expansion. However, domestic use decreases by 10% due to population reduction. Water deficit in the future is projected to increase by 52% from 172.4 to 262.7 million m3 due to rising water demand and declining water supply. This study shows that integrating a hydrological model into a water allocation model is a promising approach to estimate the water supply, demand and balance, which is a crucial component of water resources management.

The overarching vision of Society 5.0 seeks to integrate technology to enhance the quality of life and address social issues, with the primary goal of creating human-centered communities, which nowadays represent the inhabitants of Smart Cities. In this context, this work addresses the design of a modular strategic platform for the smart supervision of public expenditure, to be used by the Directorate of Information, Analysis, and Immediate Reaction (DIARI) of the General Comptroller of the Republic (CGR) of Colombia as a significant contribution towards the country’s transition into the Society 5.0. The design was performed by conducting a detailed literature review on fiscal control; a comprehensive analysis of the legal, organizational, and technological aspects of the country and the CGR; and developing six functional modules focused on topics such as continuous learning, strategic decision-making, distinctive value, strategic achievements, capacity building, and organization, within a three-year implementation plan, through a participatory approach. This plan aims to integrate the platform to enable real-time monitoring, early detection of irregularities, and increased transparency in the management of data and public resources. The strategic platform for the DIARI of the CGR is useful for Smart Cities and the transition into Society 5.0 since it ensures efficient public expenditure management, enhancing transparency and citizen empowerment through modern technologies, data analytics, and active participation in governance processes.

Colorectal cancer is the third most common malignancy and the second most lethal malignancy of the general population. Right sided colon cancer is less common than left sided, occurring more frequently in females, and associated with an older age and poor prognosis. Intraabdominal abscess formation is a rare complication from colorectal cancer. Thus, we present a case of a 66-year-old male who presented to the emergency department with 4 days of sudden onset, intractable right lower quadrant abdominal pain associated with nausea and vomiting. After further evaluation, he was diagnosed with right sided colon adenocarcinoma complicated by peri-colonic abscess formation. He was treated with hemicolectomy without immunotherapy. Considering the scarcity of data concerning colonic abscess formation and colorectal adenocarcinoma, more research is needed on this dual presentation. These authors reinforce that in older patients presenting with acute abdomen, colorectal cancer should be noted as a differential

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation

The work and life routine of long-haul truck drivers involves the use of truck stops and rest areas to meet their basic human needs. These extensions of their workspaces while on the road, do not always offer adequate physical structures and services that drivers need for optimal health. Aim: To evaluate long-haul truck drivers’ perceptions about the services of food, safety, physical activity, rest and personal hygiene offered at truck stops and rest areas in Brazil. Method: Quantitative study conducted with long-haul truck drivers from the Southern region of Brazil. For data collection, a sociodemographic questionnaire and a Likert scale on food, rest, personal hygiene, safety and physical activity services were used, offered in general at the truck stops and rest areas along Brazilian roads, from March to August 2023. The data were analyzed with simple frequency descriptive statistics. Results: 175 long-haul truck drivers participated, 70.29% declared that the services of the truck stop and rest areas were charged; more than half (53.59%) of the professionals evaluated the rest service as “good” or “excellent”; the food services, was “good” or “excellent” for 42.24% of the drivers. The spaces for physical activities were the worst evaluated as “bad” or “terrible”, by 41.61%, followed by bathroom service (28.42%) and safety (34.24%), evaluated as “bad” or “terrible”. Conclusions: In the perception of long-haul truck drivers, the rest and feeding services had better evaluations, on the other hand, the services of bathroom, safety and physical activity presented worse evaluations. The perception of drivers demonstrates the lack of investments to improve basic services such as personal hygiene, safe environment and physical exercises, fundamental to the health of the worker, aiming to reduce vulnerability, sedentary lifestyle, and meeting the basic human needs of long-haul truck drivers.

The aging of the population in developing and developed countries has lead to a significant increase in health burden of spinal diseases. These elderly patients often have a number of medical co-morbidities due to aging. The need for minimally invasive techniques to address spinal disorders in this elderly population group cannot be stressed enough. Minimally invasive spine surgery (MISS) has several proven benefits such as minimal muscle trauma, minimal bony resection, lesser post-operative pain, decreased infection rate and shorter hospital stay. Over the last 40 years, constant efforts are being made to develop newer techniques of spine surgery. Endoscopic spine surgery is one such subset of MISS which has all the benefits of modern MISS. Endoscopic spine surgery initially was limited only to treatment of lumbar disc herniations. With improvement in optics, endoscopes, endoscopic drills and shavers, irrigation pumps, there has been a paradigm shift. Endoscopic spine surgery can now be performed with high magnification thus allowing its application not only to lumbar spinal stenosis, but also to spinal fusion surgeries, cervical and thoracic pathology as well. There has been increasing evidence in support of these newer techniques of spine surgery. For the purpose of this review, we studied current available literature and outlined the historical evolution of endoscopic spine surgery, the various different endoscopic systems, and techniques available and the current applications of endoscopic techniques as an alternative to traditional spinal surgery.

(1) Objective: This study aims to lay a foundation for non-contact intensive care monitoring of premature babies. (2) Methods: Arterial oxygen saturation and heart rate were measured using a monochrome camera and a time division multiplex controlled lightning with three different wavelengths (660 nm, 810 nm and 940 nm) on a piglet model. (3) Results: Using the camera system and our newly designed algorithm for further analysis, the detection of a heartbeat and the calculation of oxygen saturation was evaluated. In motionless individuals, heartbeat and respiration were separated clearly during light breathing and only minor intervention. In this case, the mean difference between non-contact and contact saturation measurements was 0.7% (RMSE = 3.8%, MAE = 2.93%). (4) Conclusions: The new sensor has proven effective under ideal animal experiment conditions. The results allow a systematic improvement for the further development of contactless vital sign monitoring systems. The results presented here are a major step towards the development of an incubator with non-contact sensor systems for use in the neonatal intensive care unit.

Growth factor receptor-bound protein 2 (GRB2) is a negative regulator of insulin signaling and positive regulator of angiogenesis. Its expression is increased in a mouse model of retinal neovascularization and in patients with type 2 diabetes mellitus (T2DM). This case-control study aimed to investigate the association between the rs9896052 polymorphism (A>C) upstream of GRB2 and proliferative diabetic retinopathy (PDR) in patients with T2DM from Southern Brazil, taking into consideration self-reported skin color (white or non-white) and the known duration of diabetes (< 10 years or ≥ 10 years). Genotypes were determined using real-time PCR in 838 patients with T2DM (284 cases with PDR and 554 controls without DR). In the total study group and in the analysis stratified by skin color, the genotype and allele frequencies were similar between the cases and controls. However, among patients with less than 10 years of diabetes, the C allele was more frequent in cases than in controls (63.3% versus 51.8%, p = 0.032), and the CC genotype was independently associated with an increased risk of PDR (adjusted OR = 2.82, 95% CI 1.17-6.75). In conclusion, our findings support the hypothesis that the rs9896052 polymorphism near GRB2 is associated with PDR in Brazilian patients with T2DM.

Helicobacter pylori infection affects over 50% of the world population and leads to chronic inflammation and gastric disorders, being the main pathogen correlated to gastric cancer development. The increasing on antibiotic resistance levels is a major global concern and alternative treatments are needed. Soybean peptides and other compounds might be an alternative in the treatment to avoid, eradicate and/or control symptoms of H. pylori infection. This study aimed to characterize a lunasin-enriched soybean extract (LSE) by proteomics tools and to evaluate its antioxidant, anti-inflammatory and antibacterial properties against H. pylori infection. By LC-MS/MS analysis, 124 proteins were identified, with the 2S albumin (lunasin and large chain subunits) being the fourth most abundant protein (8.9%). Lunasin consisted of 44 amino acid residues and an intramolecular disulfide bond. LSE at a low dose (0.0625 mg/mL) reduced ROS production in both H. pylori-infected and non-infected AGS gastric cells. This led to a significant reduction of 6.71% in the levels of pro-inflammatory interleukin (IL)-8. LSE also showed antibacterial activity against H. pylori which can be attributed to other soybean proteins and phenolic compounds. Our findings suggest that LSE might be a promising alternative in the management of H. pylori infection and associated symptoms.

Primary cutaneous B-cell lymphomas (PCBCLs) are B-cell lymphomas that can occur in the skin without evidence of extracutaneous involvement. The 2005 WHO/EORTC classification of cutaneous lymphomas and its 2018 update have distinguished three main categories based on clinicopathological, immunohistochemical and genetic characteristics: primary cutaneous marginal zone lymphoma (PCMZL), primary cutaneous follicle centre lymphoma (PCFCL), and primary cutaneous diffuse large B-cell lymphoma, leg type (PCDLBCL-LT). PCMZL and PCFCL are clinically indolent, while PCDLBCL-LT is an aggressive lymphoma. Due to its low incidence and lack of prospective studies, it is difficult to establish a standard treatment for each subgroup. The objective of our study was to describe the clinical and pathological characteristics of 103 patients with cutaneous B-cell lymphoma from 12 centres belonging to the Spanish Lymphoma Oncology Group. The median age was 53 years (40-65). According to skin extension, 62% had single site lymphoma, 17% had regional lymphoma and 20% had multifocal lymphoma. Histology: 66% had PCMZL, 26% had PCFCL, and 8% had PCDLBCL-LT. Twenty-three percent of the patients were treated exclusively with surgery, 26% with radiotherapy only, 21% with surgery plus radiotherapy, 10% with polychemotherapy, and 5% with rituximab monotherapy. Overall, 96% of patients achieved a complete response, and 44% subsequently relapsed, most of them relapsing either locally or regionally. The 10-year OS was 94.5% for the entire cohort, 98% for the PCMZL cohort, 95% for the PCFCL cohort and 85.7% for the PCDLBCL-LT cohort. Our data are comparable to those of other published series, except for the high frequency of PCMZL. The expected heterogeneity in therapeutic management has been observed.

In this study, the biodegradation properties of leather treated with various finishing chemicals were evaluated in order to enhance the sustainability of leather processing. We applied advanced analytical techniques including FT-IR, thermogravimetric analysis (TGA), and solid-state NMR spectroscopy. Leather samples treated with different polymers, resins, bio-based materials, and traditional finishing agents were subjected to a composting process under controlled conditions to measure their biodegradability. The findings revealed that bio-based polyurethane finishes and acrylic wax exhibited biodegradability, while traditional chemical finishes like isocyanate and nitrocellulose lacquer showed moderate biodegradation levels. The results indicated significant differences in the biodegradation rates and the impact on plant germination and growth. Some materials, such as black pigment, nitrocellulose lacquer and wax, were beneficial for plant growth, while others, such as polyurethane materials, had adverse effects. These results support the use of eco-friendly finishes to reduce the environmental footprint of leather production. Overall, this study underscores the importance of selecting sustainable finishing chemicals to promote eco-friendly leather manufacturing practices.

This article presents a unique set of voltage and current data from a public building and acquired using a hybrid measurement solution that combines Python and Grafana. The transversal purpose consists of contributing to the community with a vision of the quality of the supply more oriented to the monitoring of the state of the network, providing a more realistic vision, which allows a better understanding, and the adoption of the best decisions to achieve the efficient energy management and thus optimize the operation and maintenance of power systems. The work focuses on higher order statistical estimators that, combined with exploratory data analysis techniques, improve the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination in the line of low-cost measurement solutions. It also incorporates the underlying benefit of the contribution to industrial benchmarking. The paper also includes a computational comparison between Python and LabVIEW to elicit the performance of the measurement solution.

SARS-CoV-2 is an obligatory intracellular pathogen that requires of a lipid bilayer membrane for its transport, to build its nucleocapsid envelope and to fuse with the host cell. The biological membranes are constituted by phospholipids (PLs) and vitamin E (Vit E) protects them from oxidative stress (OS). The aim of this study was to demonstrate if the treatment with Vit E restores the modified profile of the FA in PLs in serum from patients with coronavirus disease-19 (COVID-19). We evaluated Vit E, total fatty acids (TFA), fatty acid of the phospholipids (FAPL), total phospholipids (TPLs), 8-isoprostane, thromboxane B2 (TXB2), prostaglandins (PGE2 and 6-keto-PGF1α), interleukin-6 (IL-6) and C-reactive protein (CRP) in serum from 22 COVID-19 patients before and after treatment with Vit E and compared the values with those from 23 healthy subjects (HS). COVID-19 patients showed a decrease in Vit E, TPLs, FAPL and TFA in serum in comparison to HS (p≤0.01) and Vit E treatment restored their levels (p≤0.04). Likewise, there was an increase IL-6 and CRP in COVID-19 patients in comparison with HS (p≤0.001) and the treatment with Vit E decreased their levels (p≤0.001). Treatment with Vit E contributes to restore the modified profile of the PLs in the SARS-CoV-2 infection and this leads to a decrease of OS and of the inflammatory process.

As per the portfolio theory proposed by Markowitz (1952), diversification has the potential to mitigate portfolio risk. Further benefits can come from diversifying internationally since poor correlations among international markets can cause risks that are systematic in one market to become unsystematic in terms of the global economy. SEBI granted approval for Indian Mutual Funds to invest in ADR/GDR released by Indian Companies in 1999. Subsequently, SEBI has eased the rules for investment and several times it has now allowed Indian mutual funds to invest in foreign equity subject to certain limits. While SEBI had approved Indian mutual funds to invest in ADSs of Indian companies way back in 1999, the growth in investment in foreign securities started with the outbreak of COVID-19 in 2020. The exponential growth in the value of stocks in the US, driven largely by growth in technology stocks, propelled investment by Indian Mutual Funds that increased investment by ten-fold to over INR 30,000 Crores. While several focused funds with a mandate to invest in US stocks formed the bulk of the investment, other flexi cap and blue-chip funds, which had erstwhile fully invested in Indian stocks, also joined the bandwagon. While research on other developed economies has revealed the positive impact of international diversification, the Authors current research examined the advantages of international diversification on the Indian mutual funds’ performance. Authors used methods like t-test, F-test, Anova, Levene test for homogeneity and regression to check the validity of our results. Authors found that the international diversification by Indian equity mutual funds that invest in both US and Indian equities outperform benchmarks one third of the time. More importantly, by diversifying into international equities, these mutual funds are able to lower their volatility and therefore provide better risk reward returns. This is the first major study of this kind about Indian mutual funds investment in foreign equities and would be valuable investors, mutual fund managers and the regulator. As investments by Indians and Indian equity mutual funds are expected to increase significantly in the coming years, this study is timely and relevant at the current context of Indian mutual fund industry.

In the early stage of new vehicle development, the requirements of maximum performance of the air conditioning (AC) system are obtained through Amesim software simulation, but the calibration control of the AC system is usually carried out in the prototype-build vehicle test stage, and the test time is spanned up to 10 months after spring (autumn), summer and winter, of which up to 2 months are for environment chamber tests. Due to the long calibration cycle of AC control in the road test, which seriously affects the vehicle launch time, virtual calibration technology of air conditioning system is developed to shorten the calibration cycle of AC systems and ensure the quality of vehicles. In the project development stage, the calibration control of the vehicle AC system can be realized to carry out the functional test of the AC system in advance. In that, the grade of maturity for the AC system control can be improved, the on-road calibration test cycle can be shortened, and the development cost can be saved.

Word Sense Disambiguation (WSD) stands as a persistent challenge within the Natural Language Processing (NLP) community. While various NLP packages exist, the Lesk algorithm in the NLTK library, a widely recognized tool, demonstrates suboptimal accuracy. Conversely, the application of deep neural networks offers heightened classification precision, yet their practical utility is constrained by demanding memory requirements. This research paper introduces an innovative method addressing WSD challenges by optimizing memory usage without compromising state-of-the-art accuracy. The presented methodology facilitates the development of WSD system that seamlessly integrates into NLP tasks, resembling the functionality offered by the NLTK library. Furthermore, this paper advocates treating the BERT language model as a gold standard, proposing modifications to manually annotated datasets and semantic dictionaries such as WordNet to enhance WSD accuracy. The empirical validation through a series of experiments establishes the effectiveness of the proposed method, achieving state-of-the-art performance across multiple WSD datasets. This contribution represents advancement in mitigating the challenges associated with WSD, offering a practical solution for integration into NLP applications.

Blindness or visual impairment following congenital heart repair is a rare complication. It can be transient or permanent depending in underlying etiology and damage to optic pathway. We report first case of transient blindness following congenital heart repair due to unilateral subdural hematoma in occipital region.

The role of Physician Assistant emerged in 1960s America and their number has increased to become a significant component of the health care workforce in that country. On the eve of a new policy regulating Physician Associates in the United Kingdom, the role of key actors in shaping the development of regulatory policies in the two countries is critically compared against a backdrop of very different political contexts and health care systems, to reveal the factors that might help or hinder the deployment of Physician Associates/Assistants and ameliorate workforce shortages.

This study develops an intelligent fire suppression device that links microcapsule-based IoT to extinguish early fires, such as blind spots that cannot be seen by humans or places that are difficult to recognize fires. The microcapsule is a micro-unit collection that collects Novak 1230 gas generated in the semiconductor production process. The microcapsule is molded into a form with a fire suppression function, and when a fire occurs, the molded body explodes and absorbs ambient oxygen to suppress the fire. The complex sensor IoT executes smoke and heat detection generated when a fire is suppressed within 10 seconds, which derives the reliability of the detector by notifying the fire and detecting the ignition point through communication linkages such as Ieee 485 and WiFi or LoRa.

Dysregulation of the Cyclin-dependent kinase 8 (CDK8) activity has been associated to many diseases including the colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But while human CDK family members are generally activated in two steps that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated to CycC while adopted an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than for the other members of CDK family. Through MD simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8 on the one hand, and the structural molecular basis of the protein-protein interaction between the two partners on the other hand. We found that CycC has a stabilizing effect on CDK8 and identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity, to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of the CycC may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

Diffuse type of gastric cancer (GC) has an increasing prevalence worldwide, especially in Western countries, is usually diagnosed at advanced stages, and has no efficacious treatment options. Epidemiological studies have reported an increased mortality from GC after occupational exposure to well-studied pro-carcinogen that are metabolically activated by Cyp P450 enzymes through aryl hydrocarbon receptor (AhR). Substantial studies support the involvement of AhR in gastric carcinogenesis. However, little is known about the role of AhR in diffuse GC, as compared to intestinal GC. In a cohort of 29 gastric tumors, we described a significantly increased AhR protein and mRNA expression levels in GCs, independently of subtypes and clinical parameters. AhR and RhoA mRNA expression were correlated in diffuse GC. Further, our study characterized how AhR affects gene expression in diffuse GC. Using qRT-PCR, we compared the expression levels of AhR, Cyp1A1 and Cyp1B1 to the expression of genes in a panel previously described. In diffuse GC, Cyp1A1 expression correlated with genes involved in IGF signalling, EMT (VIM), migration (MMP2). In an in vitro assay using the poorly differentiated KATOIII epithelial cell line, two well-known ligands for AhR (TCDD and BaP) induced mRNA expression of CYP1A1, IL1b, as well as UGT1, NQO1 and AhRR to a lower extent. We also observed a strong increase in Cyp1B1 expression in diffuse GC, along with a lower TCDD-increased Cyp1B1 expression as compared to Cyp1A1 in KATOIII cells, and immunostaining in stromal cells. In intestinal GC, Cyp1B1 inversely correlated with several genes including IDO1 (generating endogenous kynurenin-e AhR ligand). Our data provide evidence for a major role of AhR in GC, as an environmental xenobiotics receptor, through different mechanisms and pathways in diffuse and intestinal GC. Our results support continued efforts to clarify the identities of exogenous AhR ligands in diffuse GC in order to define new therapeutic strategies.

This study comprehensively evaluates the DNA/RNA Defend Pro (DRDP) sample collection buffer designed to inactivate and stabilize patient samples. The primary objectives encompassed assessing DRDP's efficacy in ensuring sample stability, facilitating extraction-free polymerase chain reaction (PCR), and ensuring compatibility with rapid antigen testing.Ninety-five diagnostic nasopharyngeal swab samples tested for influenza A/B, RSV A/B, and/or SARS-CoV-2 were diluted 1/10 with DRDP and anonymized. Stability testing involved incubating 31 positive samples at 4 °C, 20 °C, and 37 °C for 7 days, with regular extraction-free nucleic acid amplification testing (NAAT).Results demonstrated that DRDP guaranteed viral RNA stability at all temperatures for influenza, SARS-CoV-2 and RSV showing stability up to 7 days at 4 °C. DRDP-diluted samples exhibited robust compatibility with direct PCR, as 72 out of 88 samples positive for cobas Liat also tested positive for direct PCR. Non-concordant results could be explained by the 200-fold lower input in the extraction-free NAAT.Compared to NAAT, rapid antigen testing demonstrated lower sensitivity, as expected, while maintaining perfect specificity. Clear cutoffs between positive and negative rapid antigen testing results were observed in both cobas Liat and direct PCR analyses, validating DRDP's compatibility with these techniques. In conclusion, DRDP is an effective stabilizing medium compatible with direct PCR and rapid antigen testing and shows great potential for optimizing diagnostic processes, particularly in resource-limited or time-sensitive scenarios.

In this paper, we describe the synthesis and characterization of iridium (III) half sandwich complexes of stoichiometry [Cp+IrCl2L] with Cp = 5-C5 EtMe4; L = alanine anhydride (I), ortho- (II) and para-aminophenol (III). For comparative purposes, the ionic complex [Cp*IrCl(o-phen)](PF6); Cp* = (5-C5Me5) (IV) has been also synthesized and characterized. All the isolated complexes have been characterised by C, H and N elemental analysis; infrared and 1H nuclear magnetic resonance spectroscopies; 1H-1H COSY; mass spectrometry (ESI/TOF), thermogravimetry and, in the case of (IV), by conductivity measurements. The cytotoxic behaviour of the isolated complexes was studied against HeLa and complexes (III) and (IV) were found to have an IC50 close to 160-170 m, quite close to the IC50 value of cisplatin which was found to be 134,7 m, indicating that they are good cytotoxic agents. However, complexes (I) and (II) showed IC50 values above 250 m indicating their low cytotoxicity.

There is evidence that the tendency to adopt a particular pattern of causal inference, known as attributional style, is likely to be associated with specific pattern of psychopathology among youth. This study aims to assess preliminary psychometric properties of the Italian Children’s Attributional Style Questionnaire-Revised (CASQ-R) and to explore the presence of any subgroups of children and early adolescents from the general population who might exhibit internally homogeneous and externally heterogeneous attributional styles, through cluster analyses, delving also potential sociodemographic and clinical differences among the identified clusters of attributional styles. A sample of 337 children was recruited and their attributional styles and depressive symptoms were analyzed. Four distinct clusters emerged using the six CASQ-R subscales in a multivariate finite mixture model. In particular, high levels of depressive symptoms were reported by children showing high scores in all the negative attributional subscales (globality, internality and stability) and medium scores in all the positive attributional subscales. Conversely, low levels of depressive symptoms were reported by children showing medium-to-high scores in the positive attributional subscales and low-to-medium scores in the negative attributional subscales. The identified clusters shed light on distinct patterns associated with depressive symptoms, offering potential insights for targeted interventions.

Patients with Peripheral-artery-disease (PAD) are prone to risks of major-adverse-limb-events (MALE), and major-adverse-cardiovascular-events (MACE). CHA2DS2-VASc is a prognostic score for Atrial fibrillation stroke risk, however, no study exists that evaluated its predictability for MALE and MACE in PAD patients. In this study, patients with PAD were stratified into four risk groups based on CHA2DS2-VASc score. Cox-proportional hazards models,10-fold cross-validation and Receiver operating characteristic (ROC) analyses were utilized to evaluate the predictability of CHA2DS2-VASc for predicting MALE, MACE, and MALE+MACE. Kaplan-Meier analysis estimated the survival-probability of risk-groups. CHA2DS2-VASc was found to be a significant predictor of MACE (hazard ratio (95% confidence interval; P) = 3.47 (0.99 - 12.18; 0.052), 4.12 (1.19 - 14.14; 0.024), and 5.06 (1.48 – 17.28; 0.009), for moderate-, high- and very-high-risk groups, respectively, while for MALE and MALE+MACE significance was achieved only for high-risk group. MACE demonstrated AUC > 0.8, good-discrimination (c-index > 0.8) and good-calibration. However, MALE and MALE+MACE models failed to achieve good performances. Based on all findings, CHA2DS2-VASc could potentially serve as a risk stratification score for predicting MACE in patients with PAD but failed to qualify as a good predictor for MALE.

The aim of study was to investigate epidemiology aspects of magnetic resonance imaging (MRI) during COVID-19 pandemic. The study comprised depersonalized residents of Tomsk and Tomsk Region (n = 1714). Invitations to take online survey were sent to 50,000 residents by target SMS with response rate of 1.2% (n = 727, Cohort 1). Cohort 2 comprised retrospective patients (n = 987) who underwent contrast-enhanced cardiac MRI (CMR) in 2019-2022. Referrals, clinical characteristics, diagnosis, gender, age, past COVID-19, MRI study protocols, and MRI data were analyzed. 29% of respondents in cohort 1 received MRI examination within past two years; 26% of respondents considered MRI the most informative imaging modality for detecting COVID-19 pneumonia; 12% of respondents reported MRI unavailable. Proportion of CMR among MRI studies increased during COVID-19 pandemic, and maximum incidence of cardiac diseases detected by MRI was in 2021. Incidence of myocardial fibrosis increased from ~67% in 2019 to ~84% in 2022. The rate of outpatient MRI studies significantly increased in 2020, but returned to pre-pandemic level in 2021. COVID-19 pandemic increased the need for MRI and CMR. Patients with history of COVID-19 had persistent and newly occurring symptoms of myocardial damage suggesting chronic cardiac involvement requiring continuous follow-up.

Since cART was introduced to treat AIDS, the mortality rate due to AIDS has markedly decreased and the convalescence of HIV-infected individuals has improved drastically. However, HIV-1 sexual transmission has made HIV become a global epidemic. Sacran is a megamolecular poly-saccharide extracted from cyanobacterium Aphanothece sacrum that exhibits numerous desirable characteristics for transdermic applications, such as safety as a biomaterial, a high moisture re-tention effect, the ability to form a film and hydrogel, and an anti-inflammatory effect. In this study, we evaluated the anti-HIV-1 effects of Sacran as a barrier to HIV transmission. Sacran inhibited HIV-1 infection and envelope-dependent cell-to-cell fusion. Moreover, we used a Transwell assay to confirm that sacran inhibited viral diffusion and captured viruses. The synergistic effects of sacran and other anti-HIV infection drugs were also evaluated.HIV-1 infections can be reduced through the synergistic effects of sacran and anti-HIV-1 drugs. Our study suggests the use of sacran gel to protect against HIV-1 transmission.

Through the use of Smart Sensor Networks (SSN), Marine Observatories (MO) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of SSN devices’ hardware and software when combined with the Internet. Hence, SSN are regarded as complex distributed systems. As such, SSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed SSN. To this end, we describe in this article how we extended our previously proposed ArchiMO meta-model and design tool by extending an Enterprise Architecture Framework based on the ArchiMate Modeling Language. This extension proposes the incorporation of new Underwater Environmental Constraints (UEC) for SSN in ArchiMO which is coupled with the fusion of sensors with Artificial Intelligence. This serves as the basis for generating a new version of our ArchiMO design tool, which incorporates the new added constraints and invokes the AI created Database. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to handle and control the uncertainties and variances of the provided quality of service that may occur during the performance of the SSN, hence reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of SSN.

Abstract: Flexible pressure sensors are electronic devices that can be attached to various irregular surfaces to measure the pressure. It is widely used in wearable devices and for health detection. In this study, a general carbon nanotubes/polydimethylsiloxane (CNTs/PDMS) sponge electrode was fabricated as the elementary component of the compressible system. The sensitivity of the flexible pressure sensor is improved by optimizing the preparation process of the conductive sponge and surface modification of the CNTs, and the highest sensitivity reached 71.831 kPa-1(0~2 kPa). The flexible pressure sensor can be used to detect subtle pressure quickly and accurately so that it can be used as wearable sensor to measure the radial artery wave of a human body, which has potential applications in health care and other fields.

Recently, a significant number of tools for detecting dangerous objects have been developed. Unfortunately, the performance offered by them is overestimated due to the poor quality of the datasets used (insufficiently numerous, contain items not strictly related to dangerous objects, insufficient range of presentation conditions). To fill in a gap in this area we have built an extensive dataset dedicated to detecting the objects most often used in various acts of breaching public security (baseball bat, gun, knife, machete, rifle). This collection contains images presenting the detected objects with different quality and under different environmental conditions. We believe that the results obtained from it are more reliable and give a better idea of the detection accuracy that can be achieved under real conditions. We used the Faster R-CNN with different backbone networks in the study. The best results were obtained for the ResNet152 backbone. The mAP value was 85%, while the AP level ranged from 80% to 91%, depending on the item detected. An average real-time detection speed was 11-13 FPS. Both the accuracy and speed of the Faster R-CNN model allow it to be recommended for use in public security monitoring systems aimed at detecting potentially dangerous objects.

Recent research has specifically targeted the decision-making process of eco-friendly individuals, emphasizing the significance of recycling and its impact on sustainability. Our study extends this inquiry by examining the correlation between recycling participation and pro-environmental behavior among consumers, integrating the concepts of self-efficacy, feelings of pride, and social pressure into our analysis. Utilizing Partial Least Squares-Structural Equation Modeling (PLS-SEM), we aimed to explore the intricate relationships that underpin these behaviors. Results suggest that self-efficacy and feelings of pride significantly influence individuals' recycling behaviors, highlighting the role of psychological and social factors in promoting environmental sustainability. Interestingly, it was concluded that social pressure did not have the expected moderating effect on increasing consumers' feelings of pride and self-efficacy toward recycling activities.This study not only sheds light on the underlying mechanisms that drive pro-environmental actions but also contributes to understanding sustainability promotion through recycling and offers insights for policymakers and environmental advocates to foster environmental responsibility and behavior change.

In this paper, we establish some inequalities bounding the ratio Г_p,k(x)/Г_p,k(y), where Г_p,k(.) is the (p,k)-analogue of the Gamma function. Consequently, some previous results are recovered from the obtained results.

Dent disease type 1 is a rare inherited renal disorder affecting mainly young males, generally leading to end-stage renal failure and for which there is no cure. It is caused by inactivating mutations in the gene encoding ClC-5, a 2Cl-/H+ exchanger found on endosomes in the renal proximal tubule. This transporter participates in reabsorbing all filtered plasma proteins which justifies why proteinuria is commonly observed when ClC-5 is defective. In the context of Dent disease type 1, a proximal tubule dedifferentiation was shown to be accompanied by a dysfunctional cell metabolism. However, the exact mechanisms linking such alterations to chronic kidney disease are still unclear. In this review, we gather knowledge from several Dent disease type 1 models to summarize the current hypotheses generated to understand the progression of this disorder. We also highlight some urinary biomarkers for Dent disease type 1 suggested in different studies.

Some business license commitments in online single submission (OSS) currently only consist of an independent statement from the business actor, and there is no time limit for fulfilling the license, especially for low-risk bio-business licenses. Therefore, a system design is needed to monitor the fulfillment of business license commitments and to provide confidence to the public regarding the business provided. The system design started with discussing the importance of smart governance tools, defining the requirements for monitoring the commitment of bio-business licenses, selecting documents, determining important words and document types, and proposing a design. This research produces a prototype of a business license monitoring system. This smart governance tool checks the validity of business license documents. The proposed smart governance tool will overcome the complexity of the integration process for fulfilling business licenses from the Indonesian government units or agency systems with the OSS system. Apart from that, it is also very effective by looking at the thousands of government applications that currently exist and the desire to become one application solution that contains many functions that can fulfill the many needs of business actors for simple and transparent business licenses.

Although there are numerous available immunomodulators, those of natural origin would be preferable based on their safety profile and effectiveness. The research and clinical interest in immunomodulators have increased in the last decades, especially in the immunomodulatory properties of plant-based therapies. Innovative technologies and extensive study on immunomodulatory natural products, botanicals, extracts, and active moieties with immunomodulatory potential could provide us with valuable entities to develop as novel immunomodulatory medicines to enhance current chemotherapies. This review focuses on plant-based immunomodulatory drugs that are currently in clinical studies. However, further studies in this area are of utmost importance to obtain complete information about the positive effects of medicinal plants and their chemical components and molecules as an alternative to combatting various diseases and/or prevention.

The use of energy resources is essential to the survival and development of human civilization. However, inefficient energy use not only has an impact on the economy, but it also has a significant impact on climate change. Studying and analyzing the factors that increase energy consumption is crucial for improving energy management. The aim of this study is to analyze the factors influencing energy savings in a building taken as a study model under two different climatic conditions. Measurements of the building's energy performance were carried out using the EnergyPlus calculation engine, which enabled us to analyze the strengths of building parameters such as the number of lights, the equipment used, occupancy, temperature and the relationships between the factors influenced. EnergyPlus is an important software tool in the field of building energy efficiency, enabling the precise simulation of building energy consumption. Simulation scenarios based on actual consumption data carried out by researchers have made it possible to develop energy management strategies in buildings in order to optimize energy efficiency, and in particular to promote the thermal performance of these buildings. In the present work, EnergyPlus building energy simulation software is used to simulate the energy consumption of the building of the Faculty of Electrical Engineering at the "Gheorghe Asachi" Technical University in Iasi, in order to determine the factors influencing building energy consumption. It has been shown that occupancy and heating and cooling systems are the key factors influencing energy consumption in buildings. The advantage of this study is that it can be used to model the most influential factors in predicting future energy consumption in buildings.

Supply chain disruptions, a pandemic, and war in Ukraine have exposed faultlines in a globalised food system that depends on a few staple crops grown in a few exporting regions and transported to consumers around the world. In the UK, just three crops, (wheat, barley, and oilseed rape), account for 75 per cent of the UK’s 4.5 million hectares of arable land whilst the country imports around half its food - nearly 40 per cent from just four EU countries (the Netherlands, Ireland, Germany, and France). Poor diets contribute to one in seven deaths in the UK, 63 per cent of the population is overweight or obese and health inequality is increasing between the poorest and most affluent regions. The food security and health of the UK population is therefore dependent on a small number of locally grown crops, vulnerable supply chains, and an unhealthy, obesogenic diet. The UK food system must diversify if it is to become food and nutritionally secure, meet its climate and biodiversity goals and have a healthy and active population. Climate resilient and nutritious underutilised crops can help diversify the UK agrifood system but, research and investment in them is sporadic, piecemeal, and unfocused. In this paper we compare two approaches to identifying potentially suitable underutilised crops for the UK. The first, based on Defra Project CH0224 was delivered through literature and database searches and expertise of growers, advisers, breeders, seed suppliers, processors, traders, and researchers. The second, used the CropBASE digital knowledge base for underutilised crops described in Jahanshiri et. al. (2023). The two approaches produced no single crop that was common to both shortlists. We propose that the analytical and predictive tools derived from CropBASE could be combined with local knowledge and expertise from the Defra project to provide a common framework for the identification of underutilised crops that are best suited to local UK circumstances now and in climates of the future.

The gastrointestinal tract is inhabited by the gut microbiota. The main phyla are Firmicutes and Bacteroidetes. In non-alcoholic fatty liver disease, now renamed metabolic dysfunction-associated fatty liver disease (MAFLD), an increase in Firmicutes and Bacteroidetes abundance promotes its pathogenesis and evolution into non-alcoholic steatohepatitis, liver cirrhosis and hepatocellular carcinoma. For this reason, an early treatment is necessary to disfavor its progression. The aim of the present narrative review is to evaluate the different therapeutic approaches to MAFLD. The most important treatment for MAFLD is lifestyle changes. In this regard, the Mediterranean diet could be considered the gold standard in the prevention and treatment of MAFLD. In contrast, a Western diet should be discouraged. Probiotics and fecal microbiota transplantation seem to be valid, safe, and effective alternatives for MAFLD treatment. However, more studies with a longer follow up and with a larger cohort of patients are needed to underline the more effective ap-proaches to contrasting MAFLD.

Vegetable oils contain fatty acids, phenolic compounds, natural antioxidants, and fat-soluble vitamins, which are beneficial against different diseases. Oil extraction methods can, however, affect their composition. This study aims to characterize the chemical composition of oils from two Andean seeds, cañihua (Chenopodium pallidicaule) and tarwi (Lupinus mutabilis), extracted with different organic solvents, petroleum ether, hexane, and ethanol. This study compares these oils with commercial sunflower, rapeseed, and olive oils. Results showed that oils extracted with hexane had the highest yield, while those extracted with ethanol had higher antioxidant activity and total phenolic compound content. Additionally, using ethanol makes the process more sustainable than non-green solvents. The composition of tarwi and cañahua oils extracted with ethanol includes fatty acids, tocopherols, antioxidants, and phenolic compounds associated with health benefits.

Environmental factors, such as drought-stress, significantly impact maize growth and productivity worldwide. To improve yield and quality, effective strategies for early detection and mitigation of drought-stress in maize are essential. This paper presents a detailed analysis of three imaging trials conducted to detect drought-stress in maize plants using an existing, custom-developed, low cost, high throughput phenotyping platform. We propose a pipeline for early detection of water stress in maize plants using a Vision Transformer classifier and analysis of distributions of near-infrared (NIR) reflectance from the plants. We also explored suitable regions on the plant that are more sensitive to drought-stress and show that the region surrounding the youngest expanding leaf (YEL) and the stem can be used as a more consistent alternative to analysis involving just the YEL. Our results show good separation between well-watered and drought-stressed trials for two out of the three imaging trials both in terms of classification accuracy from data-driven features as well as through analysis of histograms of NIR reflectance.

Accurate streamflow forecasting is crucial for effectively managing water resources, particularly in countries like Colombia, where hydroelectric power generation significantly contributes to the national energy grid. Although highly interpretable, traditional deterministic, physically-driven models often suffer from complexity and require extensive parameterization. Data-driven models like Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) networks offer simplicity and performance but cannot quantify uncertainty. This work introduces Sparse Variational Gaussian Processes (SVGPs) for forecasting streamflow contributions. The proposed SVGP model reduces computational complexity compared to traditional Gaussian Processes, making it highly scalable for large datasets. The methodology employs optimal hyperparameters and shared inducing points to capture short-term and long-term relationships among reservoirs. Training, validation, and analysis of the proposed approach consider the streamflow dataset from 23 geographically dispersed reservoirs recorded during twelve years in Colombia. Performance assessment reveals that the proposal outperforms baseline Linear Autoregressive (LAR) and Long Short-Term Memory (LSTM) models in three key aspects: adaptability to changing dynamics, provision of informative confidence intervals through Bayesian inference, and enhanced forecasting accuracy. Therefore, the SVGP-based forecasting methodology offers a scalable and interpretable solution for multi-output streamflow forecasting, thereby contributing to more effective water resource management and hydroelectric planning.

High-density olive groves, despite their interesting production potential, have several limitations, also due to the high fruit load and the irrigation requirements.The study aimed to evaluate the effects of fruit load and deficit irrigation on oil yield and fruit quality, and on olive chemical composition in a high-density olive grove (cv Sikitita). Our main hypothesis was that the primary metabolism, as influenced by crop load and stress, could modify the accumulation of different phenolic classes.Different fruit loads were generated through flower thinning (66%, 50%, 33%, 0%) and two deficit irrigation treatments (-60%, -75%) were compared to the well-watered control (920 m3/ha).Thinning treatments had a limited effect on oil yield, on the other hand, deficit irrigation caused considerably less oil accumulation in the fruit on all sampling dates.Thinning 66% and deficit irrigation 75% were considered with the control for untargeted metabolomic analysis, considering three sampling dates. 233 different phenolic compounds were annotated. Multivariate HCA results indicated the impact of harvest time on the phenolic profile of olive fruits, yielding two separate clusters grouping t1 and t2 together and apart from t3. Regarding agronomic techniques, they played a differential role in the phenolic profile (supervised OPLS – DA). Fruit load mostly affected flavonoid glycosides. In contrast, the phenolic response to deficit irrigation is more heterogeneous, with phenolic acids (35%), flavonoids (25%), LMW, and other phenols (25%).

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p&gt;5 × 10-8). Our results are consistent with prior finding regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, and allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Background Nigeria is among the top 5 countries that have the highest gap between people reported as diagnosed and estimated to have developed Tuberculosis (TB). To bridge this gap, there is a need for innovative approaches to identify geographical areas at high risk of TB transmission and targeted Active Case Finding (ACF) interventions. Leveraging community level data together with granular sociodemographic contextual information can unmask local hotspots which could be otherwise missed. This work evaluated if this approach helps to reach communities with higher numbers of undiagnosed TB. Methodology A retrospective analysis of the data generated from an ACF intervention program in 4 south-western states in Nigeria was conducted. Wards (the smallest administrative level in Nigeria) were subdivided into further smaller population clusters. ACF sites and their respective TB screening outputs were mapped to these population clusters. This data was then combined with open-source high resolution contextual data to train a Bayesian inference model. The model predicted TB positivity rates on the community level (population cluster level), and these were visualised on a customised geoportal for use by the local teams to identify communities at high risk of TB transmission and plan ACF interventions. The TB positivity yield (proportion) observed at model-predicted hotspots was compared with the yield obtained at other sites identified based on aggregated notification data. Results The yield in population clusters that were predicted to have high TB positivity rates by the model was at least 1.75 times higher (p-value <0.001) than the yield in other locations in all four states. Conclusion The community level Bayesian predictive model has the potential to guide ACF implementers to high TB positivity areas for finding undiagnosed TB in the communities, thus improving efficiency of interventions.

In this multicenter, retrospective study we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients - 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast enhanced-MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists were evaluated using Cohen’s Kappa. On a per patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI were 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2) these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen’s kappa = 0.4250, p=0.004). The results of this study show the potential of MRDI to improve interobserver variability and the detection of csPCa.

Introduction: Anterior Lumbar Interbody Fusion (ALIF) and Posterior Spinal Fusion (PSF) play pivotal roles in restoring lumbar lordosis in spinal surgery. Debates persist between combined single-position surgery and traditional prone-position PSF for optimizing segmental lumbar lordosis. Research Question: The study investigates the impact of performing ALIF in the supine position followed by PSF in the prone position on segmental lumbar lordosis. Material and Methods: A cohort of 59 patients underwent ALIF and PSF at a single institution. Preoperative, post-ALIF supine, and post-PSF prone Cobb angles were assessed using x-ray imaging. Statistical analyses, including one-way repeated measures ANOVA and Post-hoc analyses with Bonferroni adjustment, were employed for mean comparisons within subjects. Results: The mean Cobb angle for the entire cohort showed significant variations over different time points (p).

ProAKAP4, a precursor of AKAP4 (A-kinase anchor protein) found in the flagellum of mammalian and non-mammalian spermatozoa, serves as a structural protein with established correlations to motility parameters across diverse species. This study aimed to determine the proAKAP4 levels evolution in thawed stallion semen over a 3-hour period, examining its correlation with motility descriptors and mitochondrial membrane potential. Utilizing sixteen ejaculates from four French warmblood stallions, the study involved maintaining thawed samples at 37°C for 3 hours, conducting proAKAP4 enzyme-linked immunosorbent assay (ELISA), computer-assisted sperm analysis (CASA), and mitochondrial membrane potential by JC-1 probe and flow cytometry at 0, 1, and 3 hours post-thawing. The findings indicate significant positive correlations (p≤0.05) between proAKAP4 levels and sperm total or progressive motility at all time points analyzed. Spermatozoa velocity descriptors (VAP, VCL, VSL) and spermatozoa lateral head displacement (ALH) display positive correlations (p≤0.05) with ProAKAP4 at the 0-hour post-thawing. ProAKAP4 concentration exhibits no discernible difference between batches with or without cryoprotectant. Notably, proAKAP4 consumption remains insignificant within the initial hour after thawing but becomes significant (p≤0.05) between 1 and 3 hours post-thawing. In summary, proAKAP4 demonstrates positive correlations with total and progressive motility in stallion semen for up to 3 hours after thawing, albeit showing a noticeable decrease starting from the first hour post-thawing, indicating a progressive consumption as a result of spermatozoa motile activity.

Nuclear waste is one of the most important environmental problems of nuclear power plants. A novel renewable distillation method has been proposed for an on-site recycling of the spent nuclear fuel and separation of its valuable components from the fissile isotopes, which is especially applicable for reactors using liquid fuels.

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a simplified RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

Consumer IoT (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem like a smart home. Due to security and privacy concerns, Blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their Machine Learning (ML) model using end-user data. FL uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralised aggregator to safeguard the ecosystem. However, Blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research contributes a novel architecture emphasising Gateway Peer (GWP) in blockchain network to resolve scalability, ledger optimisation and secure model transmission issues. In the architecture we replace the centralised aggregator by the blockchain network, while GWP restricts the number of local transactions to execute in BCN. Considering the security and privacy of FL processes, we have added differential privacy and advanced normalisation techniques to ML processes. The approaches strengthen end-users' cyber security and encourage the adoption of technological innovation standards by service providers. The proposed approach has been tested extensively using a well-respected Stanford Cars dataset. We experimentally demonstrate that the proposed architecture makes the network scalable and optimises the ledger significantly. In addition, the normalisation technique outperforms batch normalisation when features are under DP protection.

Migraine is a neurovascular disorder that can be debilitating for individuals and society. Current research focuses on finding effective analgesics and management strategies for migraines by targeting specific receptors and neuropeptides. However, the efficacy of calcitonin gene-related peptide (CGRP) receptor antagonists and monoclonal antibodies (mAbs) in treating migraines can vary among patients, and tolerance may develop over time, reducing their effectiveness. To address the need for novel therapeutic targets, researchers are exploring the potential of another secretin family peptide, pituitary adenylate cyclase-activating polypeptide (PACAP), as a ground-breaking treatment avenue for migraine. Animal models have revealed how PACAP affects the trigeminal system, which is implicated in headache disorders. Clinical studies have demonstrated the significance of PACAP in migraine pathophysiology. Intriguingly, the pituitary adenylate cyclase-activating peptide 1 receptor mAb, AMG 301 showed no benefit for migraine prevention, while the PACAP ligand mAb, Lu AG09222 significantly reduced the number of monthly migraine days over placebo in a phase 2 clinical trial. In addition, another secretin family peptide vasoactive intestinal peptide is gaining interest as a potential new target. In light of recent advances in PACAP research, we emphasize the potential of PACAP as a promising target for migraine treatment. Recent findings highlight the importance of exploring PACAP as a member of the antimigraine armamentarium, especially for patients who do not respond to anti-CGRP therapies. By updating our knowledge on PACAP and its unique contribution to migraine pathophysiology, we can pave the way for reinforcing PACAP and other secretin peptides as a novel treatment approach for migraines.

Migraine and neuropathic pain (NP) are evocative of painful, disabling, chronic conditions which exhibit resembling symptoms and thus considered to share a common etiology. Calcitonin gene-related peptide (CGRP) has gained credit as a target for migraine management; nevertheless, the efficacy and the applicability of CGRP modifiers warrant search for more effective therapeutic targets for pain management. This scoping review overviews human studies of common pathogenic factors in migraine and NP to explore potential novel therapeutic targets. CGRP causes inflammation in the meninges; monoclonal antibodies and inhibitors target CGRP. Gluta-mate-induced hyperexcitability and subsequent sensitization are closely linked to an alteration of the tryptophan (Trp)-kynurenine (KYN) metabolic system; the Trp-KYN system may serve as a potential target. Microglial overaction is observed in migraine and NP; modifying the microglial activity may be a possible approach. Cytokine-induced inflammation is a leading hypothesis of the pathogenesis of the conditions; alleviating neuroinflammation may complement a pain-relieving armamentarium. Transient receptor potential (TRP) ion channels evoke the release of several substances; TRP ion channels may potentially emerge as new targets. The endocannabinoid system plays a major role in the pain trafficking pathway; modification of the system may open a new path toward discovery of new analgesics. Here we highlight the mechanism of those common pathogenic factors to explore therapeutic targets for innovative pain management in migraine and NP.

Nearly half a century has passed since the discovery of cytoplasmic inheritance of human chloramphenicol resistance. The inheritance was then revealed to take place maternally by mitochondrial DNA (mtDNA). Later, a number of mutations in mtDNA were identified as a cause of severe inheritable metabolic diseases with neurological manifestation, and the impairment of mitochondrial functions has been probed in the pathogenesis of a wide range of illnesses including neurodegenerative diseases. Recently growing number of preclinical studies has revealed that animal behaviors are influenced by the impairment of mitochondrial functions and possibly by the loss of mitochondrial stress resilience. Indeed, as high as 54% of patients with one of the most common primary mitochondrial diseases, mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome, present psychiatric symptoms including cognitive impairment, mood disorder, anxiety, and psychosis. Mitochondria are multifunctional organelles which produce cellular energy and play a major role in other cellular functions including homeostasis, cellular signaling, and gene expression, among other. Mitochondrial functions are observed to be compromised and to become less resilient under continuous stress. Meanwhile, stress and inflammation have been linked to the activation of the tryptophan (Trp)-kynurenine (KYN) metabolic system, which observably contributes to development of pathological conditions including neurological and psychiatric disorders. This narrative review discusses the functions of mitochondria and the Trp-KYN system, the interaction of the Trp-KYN system with mitochondria, and the current understanding of the involvement of mitochondria and the Trp-KYN system in preclinical and clinical studies of major neurological and psychiatric diseases.

The performance of the absolute atom gravimeters used on moving platforms, such as vehicles, ships and aircrafts, is strongly affected by the vibration noise. To suppress its influence, we summarize a vibration compensation method utilizing data measured by a classical accelerometer. The measurements with the accelerometer show that the vibration noise in the vehicle can be 2 order of magnitude greater than that in the lab during daytime, and can induce an interferometric phase fluctuation with a standard deviation of 16.70π. With the compensation method, our vehicle-mounted atom gravimeter can work normally in these harsh conditions. Comparing the Allan standard deviations before and after the vibration noise correction, we find a suppression factor of 22.74 can be achieved in static condition with an interrogation time of T = 20 ms, resulting a sensitivity of 1.35 mGal/Hz1/2, and a standard deviation of 0.5 mGal with an average time of 10 s. We also demonstrate the first test of an atom gravimeter in a moving vehicle, in which a suppression factor of 50.85 and a sensitivity of 60.88 mGal/Hz1/2 were realized with T = 5 ms.

Fusarium stalk rot (FSR) caused by the Fusarium species complex is an economic threat to maize cultivation all over the world. We investigated the population structure and genetic diversity of Fusarium spp. obtained from five major maize-growing regions of India. The Tef-1α locus was used for phylogenetic analysis of geographically distinct isolates of Fusarium verticillioides, F. andiyazi, F. proliferatum, F. nygamai, and F. acutatum causing FSR. Geographical separation among four local populations contributed to 7.87% variance, whereas 92.12% of the variance was within popula-tions, suggesting a predominant influence of local adaptation or stochastic events like genetic drift within populations, with geographical separation playing a lesser but significant role in shaping genetic diversity. Genetic differentiation statistics between Fusarium species showed lower gene flow from haplotypes except in the population of F. acutatum and F. andiyazi having high GST values. In contrast, a high Kxy was reported, indicating elevated genetic differentiation between populations. The haplotype network analysis revealed the presence of eight distinct haplotypes which reflected pathogenic evolution and adaptive potential of Fusarium spp. The results offer a comprehensive framework for discussing the implications of genetic diversity in pathogen management and the evolutionary dynamics of the Fusarium spp. causing FSR of maize in the Indian subcontinent.

Objective: To evaluate the direct costs of treating patients with neuromyelitis optica spectrum disorders (NMOSD) in outpatient care, from a hospital and Unified Health System (SUS) perspective. Methods: Observational study with data collection by microfunding, carried out with patients diagnosed with neuromyelitis optics, treated at a university hospital, in the city of Rio de Janeiro. Mann-Whitney tests were performed to measure cost differences between patient groups by disease severity and analysis perspective. Results: Nine individuals with a median age of 48 years (IQR 30 - 59 years) were included. The median total costs for patients with greater severity from the perspective of the SUS and the hospital were R$ 21,638.22 (IIQ: R$ 15,614.63; R$ 25,985.32) and R$ 32,094.11 (IIQ: R$ 25,610 .60; R$ 38,617.25) respectively. For patients with moderate severity the median was R$ 7,339.85 (IIQ: R$ 6,235.45; R$ 11,912.05) from the SUS perspective and R$ 11,505.80 (IIQ: R$ 7,339.85; R$ 22,424.76) from the perspective of the hospital, where the use of medications had a major impact. Conclusion: The main cost drivers were medicines, especially those used off-label, and procedures.

The research showsThis paperstudy presents a theoretical model of sustainable tourism in protected areas based on the experiences obtained in fromthrough field work carried out in the Machalilla national park. The units of analysis that compose it and their theoretical–-methodological foundation, and as well as the indications for their practical implementation in the face of the changes imposed by future tourism are exposed. Using the deductive method, the an analysis of the problem and the general theories linked to sustainable tourism in protected areas was carried out., the This involved establishingment of the premises and the developingment of the objectives to reach conclusions on the topic studied. A qualitative investigation is presented that allowed for the integration of contributions from the analyszes carried out for the treatment and processing of information. Among the results, the systematization of theoretical models linked to tourism in protected areas and, from a practical point of view, the application of a sustainable tourism model was were achieved. The results show the relevance of the proposed theoretical model that is proposed as a contribution to the scientific development of tourism. This model highlights, the systemic nature of its components from a new perspective of analysis, which considerings the need for changes as a development factor.

A new clothing resistance model is described and applied to characterize the human thermal and moisture climates. The climate was described by the thermal (rcl,t) and evap-orative (rcl,e) resistances of comfortable, imaginary clothing. The key input variable of the model is the rate of sweating (λEsw). Since sweating is an individual-specific process, the model applies to the individual. The observations were carried out by a single individual in Martonvásár (Hungarian lowland, Central Europe) in the summer of 2023 and the winter of 2024. During the observations, the observer walked at a speed of 1.1-1.7 ms-1 in weather-appropriate clothing. Among the results, we would highlight the following: Dur-ing large environmental heat surpluses, the rcl,t values were found to be between 0.1-0.5 clo-t (clo-t = 0.155 m2·℃·W-1), while the rcl,e values fell between 0.4-0.8 clo-e (clo-e = 0.155 m2·hPa·W-1). The values of the parameters close to 0 were caused by intense sweating (λEsw > 200 Wm-2). The applicability of the model is limited and largely depends on the rela-tionship between λEsw and the metabolic heat flux density.

This paper delves into the concept of information within the context of conscious systems, emphasizing the pivotal role of entropy as a fundamental aspect in comprehending consciousness. Drawing on insights from Integrated Information Theory (IIT) and information theory, the argument posits that consciousness entails dynamic information processing, distinct from the static storage and retrieval model employed by modern computers. The intrinsic dynamics of neural systems are explored, illuminating how they integrate incoming stimuli into a unified state of subjective experience, thereby shaping conscious awareness. By considering entropy as a temporal and qualitative value, its significance in reducing uncertainty and facilitating adaptability in conscious systems is underscored. Through a series of principles, the intricate relationship between entropy, neural dynamics, and consciousness is elucidated. This analysis suggests the necessity of rethinking traditional notions of information when applied to conscious systems, highlighting the dynamic nature of consciousness and its interaction with the environment.

: Schizophrenia and schizoaffective disorder are generally treated with second-generation antipsychotic drugs. These drugs are mostly D2 and 5-HT2A antagonists. They improve positive schizophrenia symptoms sufficiently well; however, they ameliorate negative schizophrenia symptoms and cognitive functions to a small extent. We review novel antipsychotic drugs exerting a partial agonism at dopaminergic and serotonergic receptors such as cariprazine, brexipiprazole and lumateperone. Besides, the mechanisms of actions of non-anti-dopaminergic antipsychotic drugs are pointed out. Updated neural networks are used to explain the mechanism of action of M4 and M1 receptor agonists, for example xanomeline combined with trospium or emraclidine, and trace-amine-associated receptor 1 agonists (TAAR1), for example ulataront. Phase 3 clinical trials of new third generation antipsychotic drugs are presented. Novel antipsychotic drugs with a partial agonism at D2 and D3 receptors improve positive and negative schizophrenia symptoms as well as cognitive symptoms better than second generation antipsychotic drugs. Besides, they are well tolerated. M4 and M1 receptor agonists, i.e. xanomeline combined with trospium or emraclidine, and TAAR1 agonists, i.e. ulataront, have promising results in clinical trials; they well improve negative schizophrenia symptoms and cognitive functions. Phase 3 clinical trials offer promising results for anti-dopaminergic and non-anti-dopaminergic novel antipsychotic drugs. These new non-anti-dopaminergic antipsychotic drugs better emend negative schizophrenia symptoms, and they better improve cognitive functions than second-generation antipsychotic drugs. Promising new antipsychotic drugs are cariprazine, brexipiprazole, lumateperone, ulataront, and xanomeline combined with trospium. Although phase 3 clinical studies are not yet completed, they showed a therapeutic effect superior to those achieved by second-generation antipsychotic drugs. They are tolerated very well, and they better treat negative schizophrenia symptoms and improve cognitive functions.

The rapid growth in scientific article publications allows us to access articles as soon as possible. Therefore, automatic summarization systems (ATSs) are widely preferred. In most studies, the en-tire source document is expected to be summarized, just as it would be summarized by a human. Summarizing long articles, such as scientific articles, is quite difficult due to token restraint and extraction of scientific words. To address this problem, a novel Graph-Based Abstractive Summa-rization (GBAS) model is proposed, which is a novel scientific text summarization model based on SciBERT and the graph transformer network (GTN). The document's integrity is maintained since the SciIE system uses the graph structure to create a terminology-based document structure. Therefore, long documents are also summarized. The proposed model is compared with baseline models and human evaluation. Human evaluation results show that the results of the proposed model are informative, fluent, and consistent with the ground-truth summary. The experimental results indicate that the proposed model outperforms baseline models with a 37.10 and 34.96 ROUGE-L score.

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. The model dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.

Neuronal timing is critical for many brain functions such as perception and learning. At the level of the chemical synapse, the synaptic delay is determined by the presynaptic release probability (Pr) and the waveform of the presynaptic action potential (AP). Depolarization-induced analogue-digital facilitation (d-ADF) is a form of context-dependent synaptic facilitation that is induced by constant depolarization of the presynaptic neuron and is mediated by voltage inactivation of presynaptic Kv1 channels. Whether synaptic delay is modulated during d-ADF remains unclear. We show here that despite Pr is elevated during d-ADF at L5-L5 synapses, the synaptic delay is surprisingly unchanged, suggesting that both Pr- and AP-dependent changes in synaptic delay compensate for each other. We conclude that in contrast with other short- or long-term modulation of presynaptic release, timing is not affected during d-ADF because of the opposite interaction of Pr- and AP-dependent modulations of synaptic delay.

We investigated the sleep-wake rhythm of nursery school children with the aim of supporting their health and balanced mental/physical development. We analyzed 4881 children from infant to 6 years of age, using 2-week sleep tables recorded by their guardians. The table contains sleep onset times, wake times, nighttime/daytime sleep duration, and the differences in these between weekdays and weekends. The total sleep decrement of children with age is due to a decrease in daytime sleep only, and nighttime sleep duration remains almost unchanged at about 10 hours, and is therefore called the nighttime basic sleep duration (NBSD). While sleep onset time stabilizes at around 9:30 pm by the age of 2, wake-up times to be before 7 am, resulted in weekdays sleep insufficiency. This lack of sleep is compensated by long naps on weekdays and by catching up sleep on weekends morning, which may be the background to future social-jet-lag. Guardians are encouraged to know their children's exact NBSD and set an ap-propriate bedtime to maintain it on weekdays, which prevent sleep dept and form a daily rhythm of waking up at the same time both on weekdays/weekends. These conditions are believed to maintain balance in mental/physical development and school-social-adaptation.

Background: With the rapid improvement of the healthcare technologies, security and privacy of the most sensitive data, health data is at risk. Protecting patient privacy has many components, even though the data are in electronic format. Although patient privacy is thoroughly discussed in the literature, there is no study presenting all components of patient privacy protection. Methods: In this study, a complete evaluation framework is presented, as an evaluation tool, an inventory is developed, reliability and validity of the inventory is examined. Study is conducted in three phases: Conceptual framework development, inventory development and an evaluation case study. In the evaluation, fuzzy conjoint analysis is employed to handle the subjectivity and am-biguity. As the result of the evaluation, the institution is given a patient privacy protection ma-turity grade, between 1 and 5, where 1 is the worst and 5 is the best grade. Results: In the case study, XXX’s biggest hospital, employing 800 nurses, is evaluated. Half of the nurses, 400, have partici-pated in the study. Literature tells healthcare institutions do not invest enough to protect patient privacy, and the study results support this finding. Institution’s maturity grade resulted as level 2, which is bad. Conclusion: The study measures he privacy maturity with many evaluation com-ponents. Result of the evaluation explains to the patients and the public if their data is safe or not. With this maturity grade, patients have an idea about which institution to choose, public can conclude the institutions’ reliability in terms of patient privacy.

The conserved cyanobacterial protein PipX is part of a complex interaction network with regulators involved in essential processes that include metabolic homeostasis or ribosome assembly. Because PipX interactions depend on the relative levels of their different partners and of the effector molecules binding to them, in vivo studies are required to understand the physiological significance and contribution of environmental factors to regulation of PipX complexes. Here we have used the NanoBiT complementation system to analyse regulation of complex formation in Synechococcus elongatus between PipX and each of its two best characterized partners, PII and NtcA. Our results confirm previous in vitro analysis on regulation of PipX-PII and PipX-NtcA complexes by 2-oxoglutarate and on regulation of PipX-PII by the ATP/ADP ratio, showing the disruption of PipX-NtcA complexes by increased levels of ADP-bound PII in Synechococcus elongatus. The demonstration of a positive role of PII on PipX-NtcA complexes under the initial response to nitrogen starvation or the impact of a PipX point mutation on the activity of PipX-PII and PipX-NtcA reporters are further indications of the sensitivity of the system. This study reveals additional regulatory complexities in the PipX interaction network, opening the way to future research in cyanobacteria.

The discovery by the Large Area Telescope on board Fermi of variable gamma-ray emission from radio-loud narrow-line Seyfert 1 (NLSy1) galaxies revealed the presence of a possible third class of AGN with relativistic jets in addition to blazars and radio galaxies. Considering that NLSy1 are usually hosted in spiral galaxies, this finding poses intriguing questions about the nature of these objects and the formation of relativistic jets. We report on a systematic investigation of the gamma-ray properties of a sample of radio-loud NLSy1, including the detection of new objects, using 7 years of Fermi-LAT data with the new Pass 8 event-level analysis. In addition we discuss the radio-to-very-high-energy properties of the gamma-ray emitting NLSy1, their host galaxy, and black hole mass in the context of the blazar scenario and the unification of relativistic jets at different scales.

The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in-situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service that was co-developed with in-region partners to provide year-round, low-latency weather-hazards information across the HKH. The paper describes the end-user focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR’s broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which is providing capability to scale automatically with event size. A performance assessment of our quantitative algorithms is described, demonstrating capabilities to map flood extent and water depth at an accuracy of >90% and

The case of a patient with autoimmune haemolytic anaemia and an anastomosing haemangioma, is presented. The main dilemma was whether the haemangioma was the cause or the consequence of the autoimmune haemolytic anaemia and how both processes should be management. The diagnostic methods used are analytical and imaging techniques, which have not been conclusive in the diagnosis of anastomosing haemangiomas. Preoperative corticosteroid treatment does not prevent the recurrence of autoimmune haemolytic anaemia in the postoperative period. Surgical indication is established by the progression of proliferative activity, tumor enlargement and compression of the vena cava over time. Surgical resection of the tumor is the procedure used. The indication for surgical treatment of the anastomosing haemangioma and the decrease in alpha- fetoprotein after tumor resection are the most relevant results, although it increases again after a few weeks. The development of an anastomotic haemangioma may be secondary to autoimmune haemolytic anaemia. Angiogenesis resulting from the formation of erythroblastic islands at the periphery of the tumor and clonal expansions may be a mechanism to compensate for the haemolysis caused by autoimmune haemolytic anaemia

This study is dedicated to the economic valuation of human capital in the regions where the Indigenous peoples of Kamchatka reside. The entire Kamchatksky Krai is considered an Indigenous people's ancestral territory. However, in this study, only municipalities whose population is more than one-third Indigenous were chosen for the assessment. This includes six municipal districts and one urban district (Aleytsky, Bystrinsky, Karaginsky, Olyutorsky, Penzhinsky, Tigilsky municipal districts and Palana urban district). The study employs statistical analysis and integrated, situational approaches: the investment approach was deemed the most appropriate tool for the economic assessment of human capital in Indigenous territories. The document analysis was based on a content analysis of open-access government documents and included legal acts, resolutions, orders, and other documents issued by federal, regional, and local authorities and pertaining to the economic activities of Kamchatka Indigenous peoples. Based on proposed calculation algorithm the assessed combined monetized value of human capital for the Kamchatka territories with large Indigenous populations at 38.8 billion rubles (approximately 520 million U.S. dollars) in 2021. It was observed that the growth of human capital in the Indigenous areas of Kamchatka between the years 2017 and 2021. The mean regional value of human capital per capita increased by more than twofold over this period. The accurate and precise assessment of human capital in the Kamchatka Indigenous homelands is provides baseline information necessary for the decision-making about economic development and sustainable development policies, and the approach proposed in this paper can be utilized by the Indigenous communities worldwide.

While cycling presents environmental benefits and promotes a healthy lifestyle, the risks associated with overtaking maneuvers by motorized vehicles pose significant hindrances for many potential cyclists. Large-scale analysis of overtaking maneuvers could inform traffic researches and city planners on how to reduce these risks by better understanding these maneuvers. Drawing from the fields of sensor-based cycling research and of LiDAR-based traffic data sets, this paper provides a step towards addressing these safety concerns by introducing the Salzburg Bicycle 3d (SaBi3d) data set, consisting of LiDAR point clouds capturing car-to-bicycle overtaking maneuvers. The data set, collected using a LiDAR-equipped bicycle, facilitates detailed analysis of a large quantity of overtaking maneuvers without the need for manual annotation through enabling automatic labeling by a neural network. Additionally, a benchmark result for 3d object detection using a competitive neural network is provided as a baseline for future research. The SaBi3d data set is structured identically to the nuScenes data set, and therefore offers compatibility with numerous existing object detection systems. This work provides valuable resources for future researchers to better understand cycling infrastructure and mitigate risks, thus promoting cycling as a viable mode of transportation.

Biases in Artificial Intelligence (AI) or Machine Learning (ML) systems due to skewed datasets problematise the application of prediction models in practice. Representation bias is a prevalent form of bias found in the majority of datasets. This bias arises when training data inadequately represents certain segments of the data space, resulting in poor generalisation of prediction models. Despite AI practitioners employing various methods to mitigate representation bias, their effectiveness is often limited due to a lack of thorough domain knowledge. To address this limitation, this paper introduces human-in-the-loop interaction approaches for representation debiasing of generated data involving domain experts. Our work advocates for a controlled data generation process involving domain experts to effectively mitigate the effects of representation bias. We argue that domain experts can leverage their expertise to assess how representation bias affects prediction models. Moreover, our interaction approaches can facilitate domain experts in steering data augmentation algorithms to produce debiased augmented data and validate or refine the generated samples to reduce representation bias. We also discuss how these approaches can be leveraged for designing and developing user-centred AI systems to mitigate the impact of representation bias through effective collaboration between domain experts and AI.