Pervasive purifying selection on non-synonymous substitutions is a hallmark of papillomavirus genome history. Whereas the role of selection on, and drift of, non-coding DNA elements on HPV diversification is poorly understood. More than a thousand complete genomes representing Alphapapillomavirus types, lineages and SNP variants were examined phylogenetically and interrogated for the number and position of non-coding DNA sequence motifs using Principal Components Analyses, Ancestral State Reconstructions and Phylogenetic Independent Contrasts. For anciently diverged Alphapapillomavirus types, composition of the 4 nucleotides (A,C,G,T), codon usage, trimer usage and 13 established non-coding DNA sequence motifs revealed phylogenetic clusters consistent with genetic drift. Ancestral state reconstruction and Phylogenetic Independent Contrasts revealed ancient genome alterations, particularly for CpG and APOBEC3 motifs. Each evolutionary analytical method we performed supports the unanticipated conclusion that genetic drift and different evolutionary drivers have structured Alphapapillomavirus genomes in distinct ways during successive epochs, even extending to differences in more recently formed variant lineages

Remote Photoplethysmography (rPPG) has emerged as a non-intrusive and promising physiological sensing capability in HCI research, gradually extending its applications in health-monitoring and clinical care contexts. With advanced machine learning models, recent datasets collected in real-world conditions have gradually enhanced the performance of rPPG methods in recovering heart-rate and heart-rate variability metrics. However, the signal quality of reference ground-truth PPG data in existing datasets is by and large neglected, while poor quality references negatively influence models. Here, this work introduces a new imaging blood volume pulse (iBVP) dataset of synchronized RGB and thermal infrared videos with PPG ground-truth signals from the ear and its high resolution signal quality labels, for the first time. Participants perform rhythmic breathing, head-movement, and stress-inducing tasks, which help reflect real-world variations in psycho-physiological states. This work conducts dense (per sample) signal quality assessment to discard noisy segments of ground-truth and corresponding video frames. We further present a novel end-to-end machine learning framework, iBVPNet that features an efficient and effective spatio-temporal feature aggregation for reliable estimation of BVP signals. Finally, this work examines the feasibility of extracting BVP signals from thermal video frames, which is underexplored. The iBVP dataset and source codes are publicly available for research use.

Regeneration of lost tail is of great importance to lizards. Anolis carolinensis, a green lizard, is capable of regenerating its tail efficiently after autotomy. Hence, it is considered as a model organism in regeneration study. A. carolinensis shed its tail in order to distract the predator’s attention and thus makes a way to escape. Restoring of the amputated tail takes several days and the mechanism is currently clearly understood. Although save its life, tail regeneration is associated with the impairment of several vital functions in Anoles. In addition, various differences have been observed between original and regenerated tail in terms of mechanism and structure. To date, very little work has been conducted on tail autotomy and regeneration at molecular and genetic level. The genes responsible for regeneration in anoles are identified recently. These genes are evolutionarily conserved through all tetrapod vertebrates. They are, however, in a state of ‘switched-off’ in other vertebrates including humans. Consequently, a throughout study of these so called ‘switched-off’ genes may provide a way of restoring lost organs in human, and thus could revolutionize the modern medical science.

Immune checkpoint inhibitors (ICI) are a promising form of immunotherapy that has significantly changed the therapeutic landscape for many advanced cancers. They have shown unique clinical benefit against a broad range of tumour types and a strong overall impact on survival in studied patient populations. However, there are still many limitations holding back this immunotherapy from reaching its full potential as a possible curative option for advanced cancer patients. A great deal of research is being undertaken in the hope of driving advancements in this area, building a better understanding of the mechanisms behind immune checkpoint inhibition and ultimately developing more effective, safer, and wider-reaching agents. Taking into account the current literature on this topic, this review aims to explore in depth the basis of the use of ICIs in the treatment of advanced cancers, evaluate its efficacy and safety, consider its current limitations, and finally reflect on what the future holds for this very promising form of cancer immunotherapy.

In this paper, we investigate an exact Universe which is observational viable and filled with binary mixture of perfect fluid and cosmological constant $\Lambda$. Owning the non-uniform expansion of cosmos, we have considered redshift drift $\dot{z} = -(1+z)H_{0}+H(z)$ and performed statistical test to obtain the best fit value of model parameters of derived Universe with its observed values. Here $H_{0}$ and $z$ denote the present value of Hubble constant and redshift respectively. We estimate the best fit values of Hubble constant and density parameters are $H_{0} = 68.58 \pm 0.84$ km/s/Mpc, $(\Omega_{m})_{0} = 0.26 \pm 0.010$ and $(\Omega_{\Lambda})_{0} = 0.71 \pm 0.025$ by bounding the derived model with latest observational Hubble data (OHD) while with joint Pantheon data and OHD, its values are $H_{0} = 71.93 \pm 0.58$ km/s/Mpc, $(\Omega_{m})_{0} = 0.272 \pm 0.06$ and $(\Omega_{\Lambda})_{0} = 0.74 \pm 0.09$. The analysis of deceleration parameter and jerk parameter show that the Universe in derived model is compatible with $\Lambda$CDM model.

Article contents the analytical model of the drift of a separate ice field under action of wind and current, which velocities and directions can vary during time. Model takes into account the mass of ice, added mass of sea water and the effects of the wind and current on the ice field in form the friction on its upper and underwater surfaces and frontal resistance on its end (forward and backward) surfaces. Results of performed the steady wind drift of the ice fields modelling show the drift velocity exceeds considerable known velocity of a compact ice cover wind drift. Drifting ice field has the certain kinetic energy that should be released when collision with unmovable obstacle and spent on brittle breakdown of part of the ice field. Volume of formed small ice pieces (fragments of ice field) was estimated by comparison of the specific energy of the sea ice brittle destruction and the kinetic energy of drifting ice field. Article presents the results of estimation of possible volume of the ice pieces and the scales of formed piles as result of collision with an obstacle depending on initial dimensions of ice field and wind speed. Developed models and the results of computer modelling can be used to estimate the ice pile sizes near the stationary platforms and terminals on the Arctic seas.

Abstract: High step-up voltage gain nonisolated DC-DC converter have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. In this paper, by combining input current ripple-free boost cell with coupled-inductor voltage-doubler cell, an input current ripple-free high voltage gain nonisolated converter is proposed. In addition, passive lossless clamp circuit is adopted to recycle the leakage inductor energy and to reduce the voltage spike across the power switch. By utilizing voltage-doubler cell consisting of diode and capacitor, the voltage stress of switch is further reduced and the resonance between the leakage inductor and the stray capacitor of the output diode is eliminated. A low switch-on-resistance low-voltage-rated MOSFET can therefore be employed to reduce the conduction loss and cost. The reverse recovery loss of output diode is reduced, and the efficiency of converter can be improved. Furthermore, the proposed converter can achieve nearly zero input current-ripple and make the design of electromagnetic interference (EMI) filter easy. Steady state analysis and operation mode of the converter is performed. Finally, experimental results are presented to verify the analysis results of the proposed converter.

Research on spatio-temporal geostatistical modelling remains a critical challenge in numerous scientific and engineering disciplines. This work introduces a novel extension of the dual kriging the spatio-temporal dual kriging (ST-DK) whose drift functions with fixed and adaptive coefficients are established. The approach appears to be effective in modelling complex spatio-temporal dynamics, particularly when relevant auxiliary variables exert substantial influence on the target variable. To illustrate its performance, we compare the ST-DK model with the classical spatio-temporal regression kriging (ST-RK) method for estimating temperature and air pressure data across Thailand in 2018. Our findings demonstrate that both ST-DK and ST-RK models, when utilizing adaptive coefficients, outperform their constant coefficient counterparts. Furthermore, the ST-DK method consistently exhibits superior performance compared to the ST-RK model.

We introduce a modelling framework for the investigation of on-line machine learning processes in non-stationary environments. We exemplify the approach in terms of two specific model situations: In the first, we consider the learning of a classification scheme from clustered data by means of prototype-based Learning Vector Quantization (LVQ). In the second, we study the training of layered neural networks with sigmoidal activations for the purpose of regression. In both cases, the target, i.e. the classification or regression scheme, is considered to change continuously while the system is trained from a stream of labeled data. We extend and apply methods borrowed from statistical physics which have been used frequently for the exact description of training dynamics in stationary environments. Extensions of the approach allow for the computation of typical learning curves in the presence of concept drift in a variety of model situations. First results are presented and discussed for stochastic drift processes in classification and regression problems. They indicate that LVQ is capable of tracking a classification scheme under drift to a non-trivial extent. Furthermore, we show that concept drift can cause the persistence of sub-optimal plateau states in gradient based training of layered neural networks for regression.

In the field of railroad safety, effective detection of surface cracks is critical, necessitating reliable, high-speed non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of ’lift-off noise’ due to varying distances between the probe and test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver coils, aiming to enhance detection sensitivity and minimize lift-off impact. The study optimizes ECT probes employing different driver coils, emphasizing three main objectives: a) quantitatively evaluating each probe using signal- to-noise ratio (SNR) and outlining a real-time data processing algorithm based on SNR methodology; b) exploring the frequency range proximal to the electrical resonance of the receiver coil; c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with figure 8-shape driver coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. Simulation results closely align with experimental findings, validating the investigation of optimal operational frequency and lift-off distance for selected probe performance, determined to be 0.3 MHz and 0.5 mm, respectively. The realization of this project would lead to notable advancements in enhancing railroad safety by improving crack detection efficiency.

In this paper we study solutions and drift homogenization for a class of viscous lake equations by using the method of semigroups of bounded operators. Suppose that the initial value i.e.,for some Hölder continuous function onwith smooth function value satisfying and Then the initial value problem (2) for viscous lake equations has a unique smooth local strong solution. Using this result we study the drift homogenization for three-dimensional stationary Stokes equation in the usual sense

Zero-rate output (ZRO) drift induces deteriorated micro-electromechanical system (MEMS) gy-roscope performances, severely limiting its practical applications. Hence, it is vital to explore an effective method toward ZRO drift reduction. In this work, we conduct an elaborate investigation on the impacts of the internal and packaging stresses on the ZRO drift at the thermal start-up stage, and propose a temperature-induced stress release method to reduce the duration and magnitude of ZRO drift. Self-developed high-Q dual mass tuning fork gyroscopes (TFGs) are adopted to study the correlations between temperature, frequency and ZRO drift. Furthermore, a rigorous finite element simulation model is built based on the actual device and packaging structure, revealing the temperature and stresses distribution inside TFGs. Meanwhile, the relationship between temperature and stresses are deeply explored. Moreover, we introduce a temperature-induced stress release process to generate thermal stresses and reduce the temperature-related device sensitivity. By this way, the ZRO drift duration is drastically reduced from ~2000 s to ~890 s, and the drift magnitude decreases from ~0.4 °/s to ~0.23 °/s. This stress release method achieves a small bias instability (BI) of 7.903 °/h and a low angle random walk (ARW) of 0.792 °/√h, and the long-term bias performance is significantly improved.

Polynomial recurrence bounds for a class of stochastic differential equations with a gradient type drift and an additive Wiener process are studied without Lyapunov functions.

This work involves results of research on short-term and long-term DC-drifts in electro-optical modulators based on annealed proton exchange waveguides in LiNbO3 crystals after wafer pre-annealing. The relaxation time of the DC-drift of the operating point for a short-term drift is minutes, and for a long-term drift, hours and days. DC-drift was measured by applying bias voltage and changing crystal temperature. Obtained results shows significant impact on stability of operating point in EO-modulators after treatment of defective structure of the near-surface layer of a LiNbO3 crystal. Treatment of the disturbed near-surface layer of a LiNbO3 crystal results in twice reduction of short-term DC-drift and increase of operation stability of electro-optical modulators during long-term measurement of temperature by activation energy calculation.

In this paper, we study the Parisian time of a reflected Brownian motion with drift on a finite collection of rays. We derive the Laplace transform of the Parisian time using a recursive method, and provide an exact simulation algorithm to sample from the distribution of the Parisian time. The paper is motivated by the settlement delay in the real-time gross settlement (RTGS) system. Both the central bank and the participating banks in the system are concerned about the liquidity risk, and are interested in the first time that the duration of settlement delay exceeds a predefined limit, we reduce this problem to the calculation of the Parisian time. The Parisian time is also crucial in the pricing of Parisian type options; to this end, we will compare our results with the existing literature.

Introduction Livestock abortigenic agents, which are microorganisms that lead to premature foetal death and expulsion before completion of the gestation period, are common in Africa and Asia. Abortion events cause economic losses by lowering reproduction (and hence herd/flock sizes) and effects on milk production. Despite the importance of livestock production for food security and livelihoods of millions of the world’s poorest communities, very little is known about the scale, magnitude or causes of livestock abortion in Africa. The aim of this review was to determine the current status of the burden of livestock abortion and surveillance measures adopted for livestock abortigenic pathogens in Africa and Asia, and to explore feasible surveillance technologies. Methodology A systematic literature search was conducted using Preferred Reporting of Systematic Reviews and Meta-analyses (PRISMA) guidelines in four databases for studies published between 1 Jan 1990 and 31 July 2021 that reported epidemiological surveys of livestock abortigenic pathogens in cattle, goats and sheep in Africa and Asia including; Brucella spp., Neospora caninum, Toxoplasma gondii, Rift valley fever virus, Coxiella burnetii, Chlamydia, Leptospira and Bovine viral Diarrhoea Virus. A meta-analysis was used to estimate the species-specific prevalence of the abortigenic diseases and the region where they were detected. Results In the systematic literature search, 48 full papers were included which in total included 50 species-specific surveillance reports from Africa and 19 from Asia. Adjusted median seroprevalence calculations estimated Brucella at 6.85% (range 1.2-11.6) of 9071 sheep, 3.35% (range 0.90-5.40) of 17,007 goats, 8.95% (range 0.50-63.60) of 171,733 cattle, Neospora at 6.80% (range 6.80 -6.80) of 555 sheep, 10.80 (range 10.80-10.80) of 185 goats, 12.65% (range 3.40- 25.60) of 3775 cattle, Toxoplasma at 27.50% (range 1.40 – 75.90) of 2284 sheep, 32.0% (range 20.00- 64.80) of 1226 goats, 7.50% (range 7.50 - 7.50) of 174 cattle, Coxiella at 9.20 (range 9.20 – 9.20) of 184 sheep, 24.20% (range 24.20-24.20) of 91 goats, 13.80% (range 13.80-13.80) of 217 cattle, Rift valley fever virus at 7.70 (2.40-40.00) of 874 sheep, 20.95 (range 2.50-40.00) of 547 goats, 7.45% (range 3.60-11.30) of 309 cattle, Bovine viral diarrhea virus at 78.90 (range 78.90 – 78.90) of 398 cattle, Leptospira at 70.50 (range 70.50 – 70.50) of 373 cattle and Chlamydia at 6.60 (6.60-6.60) of 803 sheep. We found that most studies, 45 (89%) used serological surveys, 1 (2%) used molecular and 1 (2%) reported to have used Mobile-phone based surveillance approach. Three studies (6.25%) of the 48 included were embedded in the national surveillance programs of the respective countries they were conducted, majority 89% were stand-alone cross-sectional studies. Conclusion In conclusion, livestock abortigenic pathogens are still a burden in many African and Asian countries.

Artificial Intelligence (AI) is required since multiple resources are in need to complete depending on a daily basis. As a result, automating routine tasks is an excellent idea. This reduces the foundation's work schedules while also improving efficiency. Furthermore, the business can obtain talented personnel for the business strategy through Artificial Intelligence. Explainability in XAI derives from a combination of strategies that improve machine learning models' environmental flexibility and interpretability. When Artificial Intelligence is trained with a large number of variables to which we apply alterations, the entire processing is turned into a black box model which is in turn difficult to understand. The data for this research's quantitative analysis is gathered from the IEEE, Web of Science, and Scopus databases. This study looked at a variety of fields engaged in the (Explainable Artificial Intelligence) XAI trend, as well as the most commonly employed techniques in domain of XAI, the location from which these studies were conducted, the year-by-year publishing trend, and the most frequently occurring keywords in the abstract. Ultimately, the quantitative review reveals that employing Explainable Artificial Intelligence or XAI methodologies, there is plenty of opportunity for more research in this field.

We have studied on the stress measurement by making use of salivary nitrate, which can be a candidate of stress markers, with ion-selective field-effect transistors (ISFETs). ISFETs are suitable for on-site single-drop analysis of salivary nitrate within 10 seconds. However, when ISFETs are used for salivary nitrate, ISFETs have a problem which is called the initial drift. The initial drift makes it difficult for determination of an accurate nitrate monitoring. Thus, the purpose of this study is to suppress an initial drift and to search for new easy polymer to possess more performance of sensor responses than conventional matrix membrane such as PVC. In this research, we investigated ISFETs using specific matrix membrane for example, KP-13, Pellethane^® and P7281-PU. The initial drift was evaluated from the fluctuation of the response values generated by ISFETs which are immersed in saliva or aqueous solution. As a result, P7281-PU showed its suppression effect for the initial drift in the whole saliva and various solutions. Furthermore, the cause of drift may be H⁺ diffusion, and drift suppression effect of P7281-PU may be affected by urethane bond capturing H⁺ in ion-selective membrane. This result suggests a continuous nitrate monitoring and development of wearable sensors.

Thyroid surgery rates have tripled over the past 3 decades making it one of the most frequently performed procedures within general surgery. They are associated with the possibility of serious postoperative complications having a significant impact on the patient's quality of life. The recurrent laryngeal nerve (RLN) palsy and the external branch of the superior laryngeal nerve (EBSLN) palsy are, next to hypoparathyroidism and bleeding after operation, one of the most common complications. The introduction of neuromonitoring into thyroid surgery, enabling both confirmation of anatomical integrity and assessment of laryngeal nerve function, was a milestone that has begun a new era in thyroid surgery. The International Neural Monitoring Study Group made standardization of the technique of RLN and EBSLN monitoring during thyroid and parathyroid surgery which increased prevalence of neural monitoring during thyroidectomy. Current status of IONM and benefits of its use have been presented in this publication.

The gastrointestinal tract is colonized by trillions of different microorganisms, named the gut microbiota, which is key to degrade undigested food such as dietary fibers. The fermentation of these food components leads to the production of short-chain fatty acids (SCFA) acetate, propionate, and butyrate, which exploit several beneficial roles for the host’s health. Their production and absorption happen in different ways in the human intestine and depend on the type of dietary fiber reaching the gut and the microorganisms involved in the fermentation. The supplementation of SCFAs, mostly butyrate, in treating gastrointestinal, metabolic, cardiovascular, and gut-brain-related diseases has been reported in the medical literature. This review aims to give an overview of the production and absorption dynamics of acetate, propionate, and butyrate in the human gut, with a final focus on the role played by these SCFAs on gastrointestinal and metabolic health and the present therapeutic implications.

New coronavirus (SARS-CoV-2) treatments and vaccines are under development to combat the COVID-19 disease. Several approaches are being used by scientists for investigation including 1) various small molecule approaches targeting RNA polymerase, 3C-like protease, and RNA endonuclease and 2) exploration of antibodies obtained from convalescent plasma from patients who have recovered from COVID-19. The coronavirus genome is highly prone to mutations that lead to genetic drift and escape from immune recognition; thus, it is imperative that sub-strains with different mutations are also accounted for during vaccine development. As the disease has grown to become a pandemic, new B-cell and T-cell epitopes predicted from SARS coronavirus have been reported. Using the epitope information along with variants of the virus, we have found several variants which might cause drifts. Among such variants, 23403A>G variant (p.D614G) in spike protein B-cell epitope is observed frequently in European countries such as the Netherlands, Switzerland and France.

Fibrodysplasia Ossificans Progressiva (FOP) is an enigmatic, ultra-rare genetic disorder characterized by progressive heterotopic ossification, wherein soft connective tissues undergo pathological transformation into bone structures. This incapacitating process severely limits patient mobility and poses formidable challenges for therapeutic intervention. Predominantly caused by missense mutations in the ACVR1 gene, the disorder has hitherto defied comprehensive mechanistic understanding and effective treatment paradigms. This write-up offers a comprehensive overview of the contemporary understanding of FOP's complex pathobiology, underscored by advances in molecular genetics and proteomic studies. We shed light on targeted therapy, spanning genetic therapeutics, enzymatic and transcriptional modulation, stem cell therapies, and innovative immunotherapies. We also focused on the intricate complexities surrounding clinical trial design for ultra-rare disorders like FOP, addressing fundamental statistical limitations, ethical conundrums, and methodological advancements essential for the success of interventional studies. We advocate for the adoption of a multi-disciplinary approach that converges bench-to-bedside research, clinical expertise, and ethical considerations to tackle the challenges of ultra-rare diseases like FOP and comparable ultra-rare diseases. Overall, this article serves a dual role: as a definitive scientific resource for ongoing and future FOP research and as a call to action for innovative solutions to address methodological and ethical challenges that impede progress in the broader field of medical research for ultra-rare conditions.

The Swiss Personalized Health Network has developed a national framework for enabling the semantic representation of health data within a Knowledge Graph. This framework has been implemented in all Swiss university hospitals, promoting seamless sharing and integration of clinical routine data with other health-related data, including omics and clinical research data. While research projects often have flexibility in selecting terminologies and specific versions, historical clinical routine data are typically coded for billing or administrative purposes using predefined terminologies in various (sometimes even unknown) versions over time. Some of these terminologies do not adhere to best practices for ontology design, presenting significant challenges to the retrospective re-use of such coded data for research. Common issues with these terminologies include the lack of machine-readable traceability across versions and non-adherence to FAIR principles. Terms from older versions frequently disappear in newer ones, making it challenging to distinguish outdated from invalid terms. Additionally, 'semantic drift' occurs, where the meaning of terms changes across versions. To address these challenges, we have implemented FAIR and historized versions of ATC, CHOP, and ICD-10-GM. We represent each version in RDF using versioned URIs and track meaning changes between versions in a machine-readable way using OWL and RDFS. The integration of these historized terminologies into our quality control framework, based on SHACLs, enables comprehensive data quality control in hospitals and empowers researchers to effectively utilize this data. Our work aims to bridge the gap between health data coded in different terminology versions, ensuring a consistent and reliable semantic representation.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Microfinance banks and Institutions must simultaneously provide micro financial loans to unprivileged and poor people as well as self-sustaining, which means covering enough costs to eliminate the need for subsidies. To ascertain if Micro-finance Institutions can successfully navigate the double challenge of financial self-sustainability (FSS) as well as outreach to poor clientele and women borrowers i.e. outreach. There is no other alternative but to analyse the balance between FSS and outreach indicators of MFIs. The research goal is to see whether there was any compromise between the self-sustainability and outreach towards poor and female customers. The study used data of 100 MFIs driven from the database of microfinance information’s exchange (MIX) market with the objective to determine trade off between financial sustainability and outreach. The study found financial performance variables are positively and significantly related with average loans size which shows a mission drift, in which MFIs serve wealthy clientele. However, Indian MFIs have a extremely high outreach with their female clientele, confirming MFI's social commitment to objective of women’s empowerment. The research recommends to the Policy-makers that MFIs are compromising their financial services to underprivileged people and women in order to be financially sustainable. To guarantee that institutions are focused on outreach to underserved people in rural areas, the government should reform the policies regarding governing MFIs.

This paper analyzes and compares models for predicting average magnet losses in interior permanent-magnet motors with fractional-slot concentrated windings due to harmonics in the armature reaction (assuming sinusoidal phase currents). Particularly, loss models adopting different formulations and solutions to the Helmholtz equation to solve for the eddy currents are compared to a simpler model relying on an assumed eddy-current distribution. Boundaries in terms of magnet dimensions and angular frequency are identified (numerically and using an identified approximate analytical expression) to aid the machine designer whether the more simple loss model is applicable or not. The assumption of a uniform flux-density variation (used in the loss models) is also investigated for the case of V-shaped and straight interior permanent magnets. Finally, predicted volumetric loss densities are exemplified for combinations of slot and pole numbers common in automotive applications.

This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are such promises through which AI-driven marketing will meet business goals and be huge at societies' values.

Natural language Processing (NLP) has significantly transformed in the last decade, especially in the field of Language Modeling. Large Language Models (LLMs) have achieved SOTA performances on Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in Language Models. In this paper, we examine the different aspects of Language Models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to task-and-language-independent architectures. This paper extensively discusses different pre-training objectives, benchmarks, and transfer learning methods used in LLMs. It also examines different fine-tuning and In-Context learning techniques used in downstream tasks. It also explores how LLMs can perform well across many domains and datasets if sufficiently trained on a large and diverse dataset. Next, it discusses how, over time, the availability of cheap computational power and large datasets have improved LLM’s capabilities and raised new challenges. As part of our study, we also inspect LLMs from the lens of scalability to see how their performance is affected by the model’s depth, width, and data size. Lastly, we provide an empirical comparison of existing trends and techniques and a comprehensive analysis of where the field of LLM currently stand.

Abstract Introduction: In the last thirty years, brain neuromodulation techniques have been used as an alternative to pharmacological treatment of neurological disorders. Parkinson's disease (PD) is a neurodegenerative disorder leading to bradykinesia, rest tremor, postural changes, and non-motor symptoms such as depression, anxiety, sleep disorders, pain, and cognitive decline that compromises executive functions (EFs), responsible for the orderly execution of behaviors and tasks of daily life and intentional and directed actions. To this date, a few studies with transcranial direct current stimulation (tDCS) have shown beneficial effects in PD patients concerning specific motor and non-motor symptoms, targeting the motor cortex and/or prefrontal regions. Objective: The main objective of this study was to evaluate the effects of left prefrontal tDCS across a broad spectrum of motor and non-motor symptoms of PD using established validated scales. Method: Single-blind randomized clinical trial with 18 volunteers with PD, aged between 45 and 80 years (66.1 ± 9.65), who met inclusion and exclusion criteria. Participants were submitted to assessments of motor and non-motor functions employing psychometric scales and tests to evaluate EFs and were randomly divided into two groups: control (sham stimulation) and experimental (active stimulation). All participants were involved in three separate tDCS sessions. The anode was positioned over the left dorsolateral prefrontal cortex and the cathode over the right supraorbital region, with a direct current intensity of 2mA, lasting 20 minutes. At the end of the three sessions, all participants were reassessed. Results: Significant effects of tDCS on non-motor functions were observed for cognition (verbal fluency of actions, clock copy test, appointment by visual confrontation, and verbal memory with immediate free recall) and subjective assessment of sleep quality (overall restlessness and discomfort in the arms and legs at night, leg and arm cramps at night and distressing dreams). There was also an improvement in the rate of errors and successes for congruent and incongruent stimuli of the Stroop Test. The beneficial effects on motor function were decreased rigidity, improved gait, and greater agility in the finger-tapping test. Conclusion: Three tDCS sessions showed positive results for participants with PD, producing significant improvements in various motor and non-motor functions, including sleep quality, cognition, and EFs. Additionally, the present results indicate that tDCS neuromodulation of the left dorsolateral prefrontal cortex region is feasible, safe, and provides significant objective benefits for PD patients.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

Systemic inflammation and coronary microvascular endothelial dysfunction are essential pathophysiological factors in heart failure with preserved ejection fraction (HFpEF) that support the use of statins. The pleiotropic properties of statins, such as anti-inflammatory, antihypertrophic, antifibrotic, and antioxidant effects, are generally accepted and may be beneficial in HF, especially in HFpEF. Numerous observational clinical trials have consistently shown a beneficial prognostic effect of statins in patients with HFpEF, while the results of two larger trials in patients with HFrEF have been controversial. Such differences may be related to a more pronounced impact of the pleiotropic properties of statins on the pathophysiology of HFpEF and pro-inflammatory comorbidities (arterial hypertension, diabetes mellitus, obesity, chronic kidney disease) that are more common in HFpEF. This review discusses the potential mechanisms of statin action that may be beneficial for patients with HFpEF, as well as clinical trials that have evaluated the statin effects on left ventricular diastolic function and clinical outcomes in patients with HFpEF.

Just when Catholic school Religious Education (RE) needs to be more outwardly focused on the contemporary search for meaning, its discourse has ‘drifted’ almost so exclusively into ecclesiastical terminology that its value as a spiritual/moral subject is being eroded –creating an ever widening discontinuity with classroom realities and young people’s spirituality. Religious educators’ perceptions of this problem, labelled as ‘ecclesiastical drift’, were investigated. While ecclesiastical terms were respected, issues related to their excessive usage were identified. By contrast, the unanimous, positive endorsement of educational terms raises the question why such language is largely missing from many Catholic accounts of RE.

Day by day, the share of renewable energy-based power plants such as offshore wind farms and photovoltaic power plants, in the present-day power systems is escalating. Nevertheless, most of these power-producing facilities have been located quite far away from the load centers. At this stage, HVDC power systems provide satisfactory options due to qualities such as reduced line losses, substantial controllability, and environmental advantages. Nevertheless, unique converter designs are required to combine asynchronous HVDC networks with each other and with already existing high voltage alternating current (HVAC) networks. In this study, based on the above special cases, a unique DC-DC modular multilevel converter (MMC) architecture is presented that provides an excellent solution for both integrating modern asynchronous HVDC networks and integrating these modern HVDC power systems with existing asynchronous HVAC power systems. The mathematical analysis of the recommended DC-DC MMC design has been examined in detail and the power transfer between two asynchronous power grids has been realized in a simulation environment. Efficient bilateral power transmission has been made achievable by the control system. The recommended DC-DC MMC topology has shown to be a highly successful approach, in the interconnection of HVDC power systems, according to the simulation results.

Responding to changing value creation processes in the sheet metal working sec-tor, where the complexity and interchangeability of products challenge traditional dif-ferentiation strategies, this empirical analysis explores integrating service-oriented and data-driven business models as new paths to ensure competitiveness, especially for small and medium-sized enterprises (SMEs). This study aims to capture the current state and challenges associated with the implementation of these business models in this sector. The research was conducted through semi-structured interviews with SMEs in the industry. The findings indicate that service-oriented and data-driven business models are not yet widely adopted and that manufacturing companies re-quire support in their implementation. Fields of action were identified for the industry. These are "Creating awareness and understanding", "Recognizing added value", "In-creasing company maturity" and "Understanding the change process". Cooperation between science and industry is essential in tackling these fields of action to ensure the successful integration of such business models in manufacturing companies. This pa-per identifies challenges in the fields of action that companies must address through a structured approach promoting awareness, recognizing value, improving organiza-tional maturity, and understanding the change process to successfully implement ser-vice-oriented and data-driven business models.

Pediatric onset multiple sclerosis (POMS), characterized by the onset of multiple sclerosis before the age of 18, is gaining increased recognition. Approximately 5 percent of MS cases manifest before the age of 18, with less than 1 percent occurring before the age of 10. Despite its rarity, pediatric MS exhibits distinct characteristics, with an association between younger age at onset and a comparatively slower disease progression. Despite this slower progression, individuals with POMS historically reach disability milestones at earlier ages than those with adult-onset multiple sclerosis. While various immunomodulatory agents demonstrate significant benefits in MS treatment, such as reduced relapse rates and slower accumulation of brain lesions on magnetic resonance imaging (MRI), the majority of disease-modifying therapies (DMTs) commonly used in adult MS lack evaluation through pediatric clinical trials. Current evidence is predominantly derived from observational studies. This comprehensive review aims to consolidate existing knowledge on the mechanisms of action, efficacy, safety profiles, and recommended dosages of available DMTs specifically in the context of pediatric MS. Furthermore, the review outlines recent advancements and explores potential medications still in developmental stages, providing a thorough overview of the current landscape and future prospects for treating POMS.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

Abstract: Lipidic carriers employed for the entrapment, encapsulation and precise targeting the bioactive compounds offer significant advantages to the biomedical, pharmaceutical, nutraceutical and cosmeceutical industries. These lipid and phospholipid-based vesicles can improve the solubility, permeation, pharmacokinetics, pharmacodynamics and bioavailability of the encapsulated material. As a matter of fact, nano-sized phospholipid vesicles have attained the highest success rate in commercialization among the available drug encapsulation technologies. Nevertheless, developing industrially acceptable products still remains a challenge. Among the main disadvantages of conventional lipidic carriers are their instability in the biological environments, and their sensitivity to changes in the pH, temperature and enzymes. To overcome these problems, the new generation of phospho/lipid-based carrier systems was developed using ingredients from microorganisms living in extremely harsh environments (i.e., archeaeobacteria). The present entry aims to review unique features of archaeolipids and recent developments in their application for the encapsulation of genetic material as well as their role and function as adjuvants and vaccine candidates.

Among natural disasters, earthquakes have a considerable impact and are among the ten deadliest, with an extreme impact on the healthcare sector. This study aimed to analyze best practices in nursing care for earthquake victims. An in-depth analysis was carried out by using a scoping review, a method used in accordance with the PRISMA-ScR recommendations to identify best nursing practice in these circumstances based on searches of eight databases: MEDLINE via PubMed; Cochrane Library; Embase; VHL; PDQ-Evidence; Scopus; ProQuest; Google Scholar. Twenty-one studies were selected. The nursing practices identified were grouped into two distinct dimensions, each subdivided into four subcategories: (i) care practices: a) immediate care, b) intermediate care, psychosocial care and d) ethical care; (ii) care management and coordination practices, which cover (a) care coordination, (b) victim care network organization, (c) teamwork and (d) training. By analyzing these nursing practices during care and relief operations for earthquake victims, this study identified the various actions carried out, the nursing skills to be developed and the reinforcement of these advanced practices through the systematization of nurses’ skills, in order to promote victims’ rehabilitation, minimize their suffering and improving their quality of life during and after an earthquake.

Purpose of review The forest industry has deployed ICTs to improve productivity of forest supply chains. In this sense, digitalization of data flows significantly impacts wood supply chains, from forest to mills, which must react flexibly to market fluctuations of forest products. The goal of this study was to conduct a literature review on data flow implementations in management systems of wood supply chains and to evaluate their applicability in supply chains to analyze the opportunities for improving them in practice. Recent findings We utilized the ScienceDirect database, Scopus and Web of Science in order to document data flows in systems and actual applications. Due to ongoing outsourcing, the wood procurement chains, and the wood supply chains were identified in the forest industry. Several different technologies can be implemented also in wood supply chains to digitalize the data flow depending on the specific needs of organizations. In this regard, digitalization of Big Data causes significant changes in elements of supply models that should be integrated and standardized in the optimization and simulation systems. Summary A modelling guide is suggested for accurate dynamic solution of problems of forest logistics. Then, the opportunities in digitalization for connecting different data flows, technologies, and stakeholders are discussed thoroughly. We conclude that data-driven dynamic optimization, and locally implemented digitalization contributes to wood supply modeling in the establishment of standards for cloud-based platforms at time-related and sequential measures which will ensure successful forest logistics through the planning and the monitoring of wood supply chains.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

Agricultural workers utilize pesticides extensively on their farms to control weeds and insects, as well as increase crop productivity. Despite these advantages, their excessive use poses a seri-ous threat, particularly to the population living at the nexus of urban and rural areas. Exposure to pesticide drift can be investigated using geospatial tools. Remote sensing technology and Geographic Information Systems (GIS) techniques have been used intensively and constitute trusted tools in different sectors, especially in agriculture. Remote sensing depends on pro-cessing the electromagnetic radiation reflected and emitted from the ground target and can be used to identify the spectral signature of crops exposed to pesticides. GIS has powerful tools for building a spatial geo-database of pesticide exposure drift. Therefore, the major objective of the research was to explore the effectiveness of using remote sensing and GIS techniques to estimate the exposure to pesticides in Macon County (Alabama). To achieve this objective, Maximum Likelihood Classification (MLC) was used to identify accurate cropland areas. The Landsat-8 and Sentinel-2 satellite images. Available agricultural pesticide usage data (seven of the seventeen organophosphates used in Alabama) were obtained through the United States Geological Survey (USGS). The results indicated that 6.6% of Macon County’s residents are considered potentially severely exposed, and the potentially affected population resides primarily in rural areas. While 23 percent of residents of rural edges are considered to have potentially medium to high expo-sure. In addition, 38% of residents living in suburban areas are considered to have potentially low-to-medium exposure. Also, the results indicated that both GIS and remote sensing can play an effective role in estimating pesticide exposure drift.

Spatial interpolation of meteorological data can have immense implications on risk management and climate change planning. Kriging with external drift (KED) is a spatial interpolation variant that uses auxiliary information in the estimation of target variable at unobserved locations. However, the traditional KED methods with linear trend functions may not be able to capture the complex and non-linear interdependence between target and auxiliary variables, which can lead to an inaccurate estimation. In this work, a novel KED method using least squares support vector regression (LSSVR) is proposed. This machine learning algorithm is employed to construct trend functions regardless of the type of variable interrelations being considered. To evaluate the efficiency of the proposed method (KED with LSSVR) relative to the traditional method (KED with a linear trend function), a systematic simulation study for estimating the monthly means temperature and pressure in Thailand in 2017 was conducted. The KED with LSSVR is shown to have superior performance over the KED with the linear trend function.

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

The therapeutic, attenuative, and morphological effects of proprietary neural stem cell-derived extracellular vesicles (NSC EVs, AB126) produced by Aruna Bio, Inc. were assessed in a range of in vitro and in vivo models of stroke. We emphasize that modulation of neuroinflammation is a key target and suggest further studies to advance our understanding of the mechanisms of action and ultimately how best to dose and monitor the benefits of AB126 in stroke patients.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Antibacterial bone cements (ABCs), such as antibiotic-loaded bone cements (ALBCs), have been widely utilized in clinical treatments. Currently, bone cements loaded with vancomycin, gentamicin, tobramycin, or clindamycin are approved by the US Food and Drug Administration. However, traditional ALBCs exhibit drawbacks like burst release and bacterial resistance. Therefore, there is a demand for the development of antibacterial bone cements containing novel agents. In this review, we summarize the latest advancements in ABCs. More importantly, we provide an overview and outlook on novel antibacterial agent-loaded bone cements, including metallic antibacterial agents, pH-switchable antibacterial agents, cationic polymers, N-halamines, non-leaching acrylic monomers, antimicrobial peptides, etc. Offering novel perspectives for designing ABCs and treating bone infections.

Background: The control of energy metabolism is fundamental for cell growth and function, and anomalies are implicated in complex diseases and ageing. It is important for cells to carefully tune metabolic pathways to optimize their function in response to different nutrient or physiological conditions. Metabolism in yeast cells can be easily manipulated by supplying different carbon sources: on glucose yeast rapidly proliferates by fermentation, analogous to tumour cells growing by aerobic glycolysis, whereas on non-fermentable carbon sources metabolism shifts towards respiration. Results: We screened deletion libraries of fission yeast to identify over 200 genes required for respiratory growth. The growth medium and auxotrophic mutants strongly influenced respiratory metabolism. Most genes uncovered in the mutant screens have not been implicated in respiration in budding yeast. We applied gene expression profiling approaches to compare steady-state fermentative and respiratory growth and to analyse the dynamic adaptation to respiratory growth. The transcript levels of most genes functioning in key energy metabolism pathways were coherently tuned, reflecting anticipated differences in metabolic flows between fermenting and respiring cells. We show that the acetyl-CoA synthase, rather than the citrate lyase, is essential for acetyl-CoA synthesis in fission yeast. We also investigated the transcriptional response to mitochondrial damage by genetic or chemical perturbations, defining a retrograde response that involves the concerted regulation of distinct groups of nuclear genes that may avert harm from mitochondrial malfunction. Conclusions: These systematic and targeted analyses provide a rich framework of the genetic and regulatory basis of fundamental metabolic states to guide future studies on energy metabolism in fission yeast and beyond. Our study pinpoints weaknesses of commonly used auxotroph mutants for investigating energy metabolism. As a model for cellular energy regulation, fission yeast provides an attractive and complementary system to budding yeast.

Hyperuricemia (HU), characterized by elevated uric acid (UA) levels in the blood, represents a global health concern associated with various conditions, including cardiovascular diseases, gout, hypertension, metabolic syndrome, renal dysfunction, and neurodegenerative diseases. This review offers a contemporary analysis of HU, encompassing its causes, associated health risks, diagnosis, treatment, and future outlook. Recent studies have underscored the multifaceted origin of HU, implicating genetic predisposition, dietary patterns, lifestyle choices, and environmental influences. Genetic variations affecting enzymes and transporters involved in purine metabolism and UA excretion have been identified, laying the groundwork for personalized treatment strategies. Advances in diagnostic imaging and omics technologies provide enhanced precision in the detection and evaluation of risks. While pharmacological interventions remain central to managing HU, persistent challenges such as treatment resistance prompt exploration of novel drug targets and lifestyle modifications. Chinese herbal medicines offer a potentially alternative approach with fewer side effects. Emerging research on the impact of gut microbiota on UA metabolism opens new therapeutic avenues. Despite progress, challenges such as optimizing treatment duration and understanding long-term effects persist. Collaborative efforts are crucial to address these challenges and advance our comprehension of HU. The integration of precision medicine and holistic patient care approaches holds promise for improving outcomes and enhancing quality of life for individuals with HU.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

Recent measurements in the MRX laboratory plasma [J.Yoo et al, Phys. Rev. Lett. 132, 145101 (2024)] have evidenced the role of lower hybrid drift waves produced during magnetic reconnections in producing an effective anomalous resistivity and heating of electrons. A detailed modelization of the energy transfer from the waves to electrons is missing, though. In this work, we attempt such an exercise using a Hamiltonian test-particle model for wave-electron interaction, valid for low-β weakly collisional plasmas. Quantitative agreement with MRX results is found.

We present in this work a method for estimation of plasma bubble mean zonal drift velocities using keograms generated from images of the OI 6300.0 nm nightglow emission collected from an equatorial station -- Cariri (7.4$^\circ$S, 36.5$^\circ$W), and a mid-latitude station -- Cachoeira Paulista (22.7$^\circ$S, 45$^\circ$W), both in the Brazilian sector. The mean zonal drift velocities were estimated for 239 events recorded from 2000 to 2003 in Cariri, and for 56 events recorded over Cachoeira Paulista from 1998 to 2000. It was found that plasma bubble zonal drift velocities are smaller ($\sim$60 ms$^{-1}$) for events occurring later in the night compared to those occurring earlier ($\sim$150 ms$^{-1}$). The decreasing rate of the zonal drift velocity is of $\sim$10 ms$^{-1}$/h. We have also found that, in general, bubble events appearing first in the west-most region of the keogram are faster than those appearing first in the east-most region of the keograms. Larger zonal drift velocities occur from 19 LT to 23 LT in a longitude range from 37$^\circ$ to 33$^\circ$. The method of velocity estimation using keograms compares favorably against the mosaic method developed by \cite{Arruda:2005}, but the standard deviation of the residuals for the zonal drift velocities from the two methods is $\sim$15 ms$^{-1}$

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.

Greek roots: "phos" (φῶς) - means "light" and "dynamis" (δύναμις) - means "force" or "power". Photodynamic therapy (PDT) is an innovative treatment method based on the ability of photosensitizers to produce reactive oxygen species after exposure to light of a specific wavelength range, either in the visible or near infrared range. This process results in damage to pathological cells, such as cancer cells, while minimizing the impact on healthy tissues. PDT is a promising direction in the treatment of many diseases, with particular emphasis on the fight against cancer and other diseases asso-ciated with excessive cell growth. The power of light contributed to the creation of phototherapy, whose history dates back to ancient times. It was then noticed that some substances exposed to the sun have a negative effect on the body, while others have a therapeutic effect. This work provides a detailed review of photodynamic therapy, from its origins to the present day. It is surprising how a seemingly simple beam of light can have such a powerful healing effect, which is used not only in dermatology, but also in oncology, surgery, microbiology, virology, and even dentistry. However, despite promising re-sults, photodynamic therapy still faces many challenges. The availability of this thera-py is limited due to the small number of centers offering this type of treatment and the high costs, which may be unaffordable for many patients. Moreover, photodynamic therapy requires further research and improvement.

Recent technical advances in the stem cell field have enabled the in vitro generation of complex structures resembling whole organs termed organoids. Most of these approaches employ culture systems that allow stem cell-derived or tissue progenitor cells to self-organize into three-dimensional (3D)-structures. Since organoids can be grown from various species, organs and from patient-derived induced pluripotent stem cells, they create significant prospects for modelling development and diseases, for toxicology and drug discovery studies, and in the field of regenerative medicine. Here, we report on intestinal stem cells, organoid culture, organoid disease modeling, transplantation, current and future uses of this exciting new insight model to veterinary medicine field.

The paper presents a study of two novel visual motion onset stimulus-based brain–computer interfaces (vmoBCI). Two settings are compared with afferent and efferent to a computer screen center motion patterns. Online vmoBCI experiments are conducted in an oddball event–related potential (ERP) paradigm allowing for “aha–responses” decoding in EEG brainwaves. A subsequent stepwise linear discriminant analysis classification (swLDA) classification accuracy comparison is discussed based on two inter–stimulus–interval (ISI) settings of 700 and 150 ms in two online vmoBCI applications with six and eight command settings. A research hypothesis of classification accuracy non–significant differences with various ISIs is confirmed based on the two settings of 700 ms and 150 ms, as well as with various numbers of ERP response averaging scenarios.The efferent in respect to display center visual motion patterns allowed for a faster interfacing and thus they are recommended as more suitable for the no–eye–movements requiring visual BCIs.

We extend the standard solid-state quantum mechanical Hamiltonian containing only Coulomb interactions between the charged particles by inclusion of the (transverse) current-current diamagnetic interaction starting form the non-relativistic QED restricted to the states without photons and neglecting the retardation in the photon propagator. This derivation is supplemented with a derivation of an analogous result along the non-rigorous old classical Darwin-Landau-Lifshitz argumentation within the physical Coulomb gauge.

Dolichandrone spathacea is a rare and endangered semi-mangrove plant species with an extremely small population, naturally distributed only in Zhanjiang City and the east coast of Hainan Island, China. Regrettably, the present situation of the D. spathacea population in China has not yet been carefully investigated. In this study, we aim to evaluate the current resource status and population dynamic characteristics of D. spathacea on Hainan Island, China, in order to propose sustainable conservation and management strategies for future ecological restoration of its natural population. Our results show that D. spathacea on Hainan Island can be divided into four populations. All the D. spathacea populations present a state of overall dispersion, local concentration, and occasionally sporadic existence, and they exist in geographical isolation. The young, middle, and old D. spathacea plants account for 20.42%, 66.20%, and 13.38%, respectively, indicating that the overall age class of the D. spathacea population on Hainan Island belongs to a declining type. Furthermore, instead of temporal structure, we chose diameter at breast height (DBH) to establish a static life table, draw a population survival curve, and quantify the future development trend through population dynamic analysis and time-series prediction. These results directly point out that the D. spathacea population on Hainan Island is sensitive to external disturbances and possesses two main increases in mortality rate—namely, in its juvenile and mature stages—due to weak vitality, competition, and anthropogenic interferences, which are the most important reasons for its endangered status. Depending on the current conditions of the D. spathacea population, we should conserve and expand mature trees in situ, preserve their germplasm resources, rehabilitate their habitats to promote provenance restoration, and conduct artificial cultivation and spreading planting in order to realize the sustainable conservation and management of D. spathacea.

Indole is a versatile pharmacophore widely distributed in bioactive natural products. This privileged scaffold has been found in a variety of molecules isolated from marine organisms such as algae and sponges. Among these, indole alkaloids represent one of the biggest, most promising family of compounds, having shown a wide range of pharmacological properties, including anti-inflammatory, antiviral and anticancer activities. The aim of this review is to show the current scenario of marine indole alkaloid derivatives, covering not only the most common chemical structures, but also new synthetic routes developed during the last years as well as promising therapeutic applications.

A meta-analysis showed a significant association between activated immune-inflammatory and nitro-oxidative (IO&NS) pathways and suicide attempts (SA). There are no data whether suicidal ideation (SI) is accompanied by activated IO&NS pathways and whether there are differences between SA and SI. The current study searched PubMed, Google Scholar, and Web of Science, for articles published from inception until May 10, 2021, and systematically reviewed and meta-analyzed the association between recent SA/SI (< 3 months) and IO&NS biomarkers. We included studies which compared psychiatric patients with and without SA and SI and controls (either healthy controls or patients without SA or SI) and used meta-analysis (random-effect model with restricted maximum-likelihood) to delineate effect sizes with 95% confidence intervals (CI). Our search included 59 studies comprising 4.034 SA/SI cases and 12.377 controls. Patients with SA/SI showed activated IO&NS pathways (SMD: 0.299; CI: 0.200; 0.397) when compared to controls. The immune profiles were more strongly associated with SA than with SI, particularly when compared to healthy controls, as evidenced by activated IO&NS pathways (SMD: 0.796; CI: 0.503; 1.089), an immune-inflammatory response (SMD: 1.409; CI: 0.637; 1.462), inflammation (SMD: 1.200; CI: 0.584; 1.816), and neurotoxicity (SMD: 0.904; CI: 0.431; 1.378). The effects sizes of the IO&NS, immune-inflammatory response and inflammatory profile were significantly greater in SA than in SI. In conclusion: increased neurotoxicity due to inflammation and nitro-oxidative stress and lowered neuroprotection may explain at least in part why psychiatric patients show increased SA and SI. The IO&NS pathways are more pronounced in recent SA than in SI.

The measurement range of a conventional current sensor is narrow because it is used with signals relative to the rated values of the measurement range from a voltage-type device. Consequently, multiple current sensors must be used in accordance with the measurement range. To address this problem, this paper proposes a new current sensor with a clamp-shaped part for low current measurement and a simple straight structure for high current measurement. The output signals of the proposed current sensor are amplified with a Hall element using the magnetic force of a rectangular air gap inside the clamp. To verify the characteristics of the proposed current sensor, a current was applied to an external load, and the value determined by the current sensor noted. Then, electromagnetic field analysis was performed through current sensor modeling and the results obtained compared to the actual sensor results. The proposed sensor had a 1% linearity in the output signals and exhibited dynamic characteristics over a wide current range.

Background: In Transcranial Direct Current Stimulation (tDCS) the injected current gets distributed across the brain areas. The motive is to stimulate the target region-of-interest (ROI), while minimizing the current in non-target ROIs. For this purpose, determining the appropriate current-dose for an individual is difficult. Aim: To introduce Dose-Target-Determination-Index (DTDI) to quantify the focality of tDCS and examine the dose-focality relationship in three different populations. Method: Here, we extended our previous toolbox i-SATA to the MNI reference space. After a tDCS montage is simulated for a current-dose, the i-SATA(MNI) computes the average (over voxels) current density for every region in the brain. DTDI is the ratio of average current density at target ROI to the ROI with maximum value (peak region). Ideally target ROI should be the peak region, so DTDI shall range from 0 to 1. Higher the value, the better the dose. We estimated the variation of DTDI within and across individuals using T1-weighted brain images of 45 males and females distributed equally across three age groups- (a) Young adults (20 ≥ x ˂ 40 years), (b) Mid adults (40 ≥ x ˂ 60 years), and (c) Older adults (60 ≥ x ˂ 80 years). DTDI’s were evaluated for the frontal montage with electrodes at F3 and right supra-orbital for three current doses 1mA, 2mA, and 3mA with the target ROI at left middle frontal gyrus. Result: As the dose is incremented, DTDI may show (a) increase, (b) decrease, and (c) no change across the individuals. The focality decreases with age and the decline is stronger in males. Higher current dose at older age can enhance the focality of stimulation. Conclusion: DTDI provides information on which tDCS current dose will optimize the focality of stimulation. DTDI recommended dose should be prioritised based on the age (> 40 years) and sex (especially males) of an individual. The toolbox i-SATA(MNI) is freely available.

Colorectal cancer is a frequent neoplasm in western countries, mainly due to dietary and behavioral factors. Its incidence is growing in developing countries for the westernization of foods and lifestyles. An increased incidence rate is observed in patients under 45 years of age. In last years the mortality for CRC is decreased, but this trend is slowing. The mortality rate is reducing in those countries where prevention and treatments have been implemented. The survival is increased to over 65%. This trend reflects earlier detection of CRC through routine clinical examinations and screening, more accurate staging through advances in imaging, improvements in surgical techniques and advances in chemotherapy and radiation. The most important predictor of survival is the stage at diagnosis. The screening programs are able to reduce incidence and mortality rates of CRC. The aim of this paper is to provide a comprehensive overview of incidence, mortality and survival rate for CRC.

Real-world evidence (RWE) is increasingly involved in the early benefit assessment of medicinal drugs. It is expected that RWE will help to speed up approval processes comparable to RWE developments in vaccine research during the COVID-19 pandemic. Definitions of RWE are diverse marking the highly fluid status in this field. So far, RWE comprises information produced from data routinely collected on patient’s health status and/or delivery of health care from various sources other than traditional clinical trials. These sources can include electronic health records, claims, patient-generated data including in home-use settings, data from mobile devices as well as patient, product and disease registries. The aim of the present update was to review the current RWE developments and guidelines mainly in the U.S., the UK, Europe and Germany field during the last decade. RWE has already been included in various approval procedures of regulatory authorities reflecting its actual acceptance and growing importance in evaluating and accelerating new therapies. However, since the RWE research is still in a transition process and since a number of gaps in this field have been explored, more guidance and a consented definition are necessary to increase the implementation of real-world data.

A large number of novel treatments for myeloma have been developed and approved, however alkylating drugs continue to be part of standard regimens, additionally, novel alkylators are currently being developed. We performed a non-systematized literary search for relevant papers and communications at large conferences, as well as exploiting the authors knowledge of the field to review the history, current use and novel concepts around traditional alkylators cyclophosphamide, bendamustine and melphalan and current data on the newly developed pro-drug melflufen. Even in the era of targeted treatment and personalized medicine, alkylating drugs continue to be part of standard-of-care in myeloma, and new alkylators are coming to the market.

GM2 gangliosidoses are a group of pathologies characterized by GM2 ganglioside accumulation into the lysosome due to mutations on the genes encoding for the β-hexosaminidases subunits or the GM2 activator protein. Three GM2 gangliosidoses have been described: Tay-Sachs disease, Sandhoff disease, and the AB variant. Central nervous system dysfunction is the main characteristic of GM2 gangliosidoses patients that include neurodevelopment alterations, neuroinflammation, and neuronal apoptosis. Currently, there is not approved therapy for GM2 gangliosidoses, but different therapeutic strategies have been studied including hematopoietic stem cell transplantation, enzyme replacement therapy, substrate reduction therapy, pharmacological chaperones, and gene therapy. The blood-brain barrier represents a challenge for the development of therapeutic agents for these disorders. In this sense, alternative routes of administration (e.g. intrathecal or intracerebroventricular) have been evaluated, as well as the design of fusion peptides that allow the protein transport from the brain capillaries to the central nervous system. In this review, we outline the current knowledge about clinical and physiopathological findings of GM2 gangliosidoses, as well as the ongoing proposals to overcome some limitations of the traditional alternatives by using novel strategies such as molecular Trojan horses or advanced tools of genome editing.

Neisseria meningitidis causes most cases of bacterial meningitis. Meningococcal meningitis is a public health burden to both developed and developing countries throughout the world. There are a number of vaccines (polysaccharide-based, glycoconjugate, protein-based and combined conjugate vaccines) that are approved to target five of the six disease-causing serogroups of the pathogen. Immunization strategies have been effective at helping to decrease the global incidence of meningococcal meningitis. Researchers continue to enhance these efforts through discovery of new antigen targets that may lead to a broadly protective vaccine and development of new methods of homogenous vaccine production. This review describes current meningococcal vaccines and discusses some recent research discoveries that may transform vaccine development against N. meningitidis in the future.

Overweight and Obesity are global health and economic concerns. According to the World Health Organization, the number of individuals with obesity has nearly tripled since 1975. This health issue is currently considered an epidemic, affecting over 1.9 billion adults and 340 million children and adolescents. It contributes to more than 5 million deaths each year and has a global economic burden that will reach $4.32 trillion annually by 2035, according to the World Obesity Federation. This disease can affect every system of the human body and can lead to complications such as metabolic syndrome, diabetes, cancer, dyslipidemia, cardiovascular diseases, and hypertension, among others. Treatment may sometimes include diet, exercise, drugs, and bariatric surgery. Nonetheless, not all people have access to these treatments, and public health strategies consider prevention the most important factor. In this regard, recent investigations are aiming to find alternatives and adjuvants for the treatment of obesity, its prevention, and the reversion of some of its complications, using natural sources of anti-obesogenic compounds like polyphenols, terpenes, alkaloids, saponins, among others. In this review, we gather the most current information using PubMed, Google Scholar, Scopus, Cochrane, and Web of Science. We present and discuss the current information about natural products that have shown anti-obesogenic effects at a molecular level. We also consider the impact of dietary habits and lifestyle in preventing overweight and obesity due to the evidence of the benefits of certain foods and compounds consumed regularly. We discuss mechanisms, pathways, and receptors involved in the modulation of obesity, especially those related to inflammation and oxidative stress linked to this disease, due to the relevance of these two aspects in developing complications.

On January 1, 2024, a large earthquake occurred in Japan’s Noto region. Many buildings collapsed as a result of violent shaking. Electricity and water supplies were cut off and communications were disrupted. Immediately after the earthquake, we visited Noto and conducted disaster-relief activities. This report integrates and discusses the results of the site visits, information broadcasts by public institutions, and previous research. Evacuation centers lacked water and proper sanitation, leading to health issues, including infectious diseases. Disaster Medical Assistance Teams (DMAT) were delayed in implementing infection control measures. Isolated evacuation centers faced communication and supply challenges. Infrastructure restoration, power supply, and toilet facilities at evacuation centers were delayed because of geographical challenges. There was a lack of intervention by medical professionals in evacuation centers because the DMATs were forced to invest manpower in rescue operations. It is important to have a team that can determine and carry out the necessary activities on site, even without instructions from the DMAT. It is believed to be effective to decide in advance how volunteer teams and the private sector will conduct their activities, assuming that they will be unable to contact public institutions during a disaster. In large-scale disasters, evacuees must operate evacuation centers autonomously. To achieve this, it is necessary for residents to form healthy communities regularly. A serious disaster is expected to soon occur in Japan. We hope that the experience of this disaster will be useful for preparing for future disasters.

The properties of the current-induced Hall effect are analysed, for which the static magnetic field, supplied by an external source in the traditional experiment, is created by the current itself. The special experimental setup, needed for its observation, is described. It is shown how, combined with the skin effect, it could give access to the concentration of conduction electrons in superconductors. Besides this experiment might permit to dodge shortcomings, ensueing from the Meissner effect and limiting severely the sensitivity of the conventional Hall voltage measurement.

It is widespread to examine and explain the functioning of the standard “Current Doubler Rectifier” as strictly symmetrical according to the electrical current through the two inductances. The present work challenges this consideration and proposes a new version of the electrical circuit daigram where the current symmetry is improved. The proposed circuit is called “Improved Current Doubler Rectifier”.

This article theoretically derives the magnetic field and vector potential produced by a steady current I flowing in an arbitrary plane loop at an arbitrary point r. Numerical examples are presented to demonstrate the behavior of the magnetic field produced by loops of various shapes such as polygons, circles, ellipses, and p-norm balls. Taking the limit as the loop shrinks to a point and the current I grows to infinity so that the magnetic dipole moment m of the loop (defined as the current I times the vector area of the loop) is kept constant, the magnetic field and vector potential are theoretically shown to converge to those of an ideal point magnetic dipole m.

Pluripotent stem cells (PSCs) can differentiate into three germ layers and diverse autolo-gous cell lines. Being among the most commonly used large domesticated hoofed animals and serving as a vital source of food and bioreactors, cattle are among the many species in which PSCs have been developed. Bovine PSCs (bPSCs) are the "seed cells" of regenerative science and have immense potential to advance species propagation, genetic engineering, and disease treatment. Moreover, they can aid in screening new drugs for efficacy and toxicity, model human diseases, and establish a sustainable agricultural system that can cater to the needs of the growing global population. Establishing stable bPSCs in vitro has been a critical scientific challenge, and researchers have made numerous attempts to address this issue. This review primarily delves into the current research progress of bPSCs, the challenges faced, and their potential applications.

As part of a project ordered by the Ministry of Science, Technology and Innovation of Brazil, an assessment of Brazilian biological collections was conducted by the Brazilian Societies of Botany, Microbiology, Virology and Zoology to obtain data on the current state of these collections. The goal was to provide subsidies for future public policies, including financial support and prioritization policies. Herein, we present the results of the microbiological collections, which play a fundamental role in the ex situ conservation of biodiversity and support research, development and innovation. A survey was sent to public and private institutions in Brazil and answered by 168 microbiological collections from 79 different institutions. Among these, 73 comprise public research institutions and universities, demonstrating the State's importance in preserving and safeguarding Brazilian microbial diversity. The main taxonomic groups are bacteria (present in 70.24% of the collections) and fungi (52.98% of the collections) from different Brazilian ecosystems and biomes, including several type strains. Furthermore, the collections preserve microorganisms with biotechnological potential for application in environmental protection, public health, industry, and agribusiness. However, despite all these economic and biotechnological potentials, the data analysis showed serious limitations and fragilities, especially regarding physical infrastructure and human resources, and raises alerts about the risk that Brazilian collections are subjected to.

(1) Background: The definition of value addition is based on the process or processes which are used to transform physically the initial raw material in the final food or non-food article. Diversification can enhance the possibility of increased gains. The aim of this work is to give a reliable description of value addition when speaking of coconut-based beverages among all possible derivatives; (2) Methods: a systematic review of main papers on the argument has been critically examined and discussed; (3) Results: Processing degree is a consequence of consumers’ requests. Three different drivers for value addition have been considered: packaging, durability, and size options; sensorial features; and sustainability. Results of this investigation have highlighted the added value of several products because of recyclable packaging materials, intermediate or long durability expectations, different available sizes, and good or excellent sensorial performances; (4) Conclusions: There are different value-added coconut-based beverages with interesting perspectives. On the other side, sustainability and eco-friendly policies may be a problem for those products which are produced similarly to non-coconut based beverages. The opportunity of certified organic and/or fair-trade products could help the industry of coconuts in the next future. More research is still needed in this ambit.

For a comprehensive exploration of the Bimolecular Fluorescence Complementation (BiFC) approach, we critically assess whether protein pairs establish direct or indirect interactions within this context. Emphasizing the multifaceted nature of protein interactions, this review underscores the imperative of delineating macromolecular complex characteristics across five distinct levels: composition, stoichiometry, copy number, topology, and dynamics. A pivotal discussion revolves around the challenges introduced by the overexpression of target proteins and the potential artificial ramifications of fusion proteins. The significance of stoichiometry in protein interactions is illuminated, with the HOXA9/PBX1 interaction serving as a pertinent case study. The research identifies and elaborates on the inherent limitations of prevailing large-scale BiFC screenings, advocating for the incorporation of rigorous negative controls. A novel proposition is introduced in the form of a high-throughput multicolor BiFC strategy, exemplified using the HOXA9 and PBX1 proteins. The paper culminates with an insightful discourse on the implications of tags within the BiFC system, presenting the TriFC (Tripartite Fluorescence Complementation) assay as a promising alternative.

The education landscape is an environment prone to change due to the volatile and ever-changing nature of the digital society in which we all live. Although the world moves at a different pace and any generalization is bound to have several exceptions, there is evidence from research conducted in different places and contexts that educational methods are becoming increasingly digitized and driven by technological innovation. Among technological trends fuelled in many cases by the COVID-19 pandemic and the need to stay at home but online, augmented reality solutions received an additional push as a valid and versatile educational technology worth exploring and eventually integrating into several teaching methods already in use. Although the technology still faces problems related to its affordability, accessibility, and the technical skills required of users, some ongoing projects have already provided evidence that using augmented reality solutions as teaching and learning tools can improve teachers’ and students’ learning outcomes by increasing their engagement and interactivity. The same issues arose when personal computers, tablets, and smartphones were first discussed as valuable tools for education and have now found their way into most classrooms. This paper reviews some of the key concepts related to augmented reality, as well as some current trends, benefits, and concerns related to its inclusion in educational contexts in areas such as life sciences, engineering, and health. The work carried out and presented in this paper provides an interesting insight into a technology that has led to global phenomena, such as Pokémon Go, and is constantly improving in terms of portability, usability, and overall user experience. Throughout the paper and in the conclusions section, we discuss the relevance of using the best features of augmented reality and how they can contribute to positive educational outcomes.

Introduction: Dementia is a cognitive decline with patients often exhibit behavioural and psychological symptoms, severely affecting the quality of life and placing a heavy burden on caregivers. Acupressure has reported benefits for dementia. This study aims to critically review the available evidence for its use as a non-pharmacological therapy. Methods: Systematic search of major research databases for human clinical trials using acupressure as an intervention for dementia patients was conducted. Results were synthesised for the effects of acupressure on various outcome measures of interest for dementia.Results: Twelve clinical trials (N=973), including eight randomised control studies, were included in this review. The study sample was predominantly institutionalised residents with moderate to severe dementia. Baihui (GV20), Shenmen (HT7), Fengchi (GB20), Neiguan (PC6), Sanyinjiao (SP6), and Yingtang (EX-HN3) were the most used acupoints for intervention. Acupressure techniques employed in these clinical trials vary greatly with no standardised approach. This review finds inconsistent evidence in the effectiveness of acupressure in reducing agitation and behavioural disturbances. However, the treatment appears to improve their ease of care and reduce physical stress. Affixing acupressure devices on selected acupoints can also potentially improve psychiatric pain, anxiety, and depression. Long-term (6 months) treatment can potentially improve the cognitive function, activities of daily living, and quality of life of patients with mild to moderate dementia. The effect of acupressure on sleep disturbances remains unclear. Conclusion: More high-quality research on acupressure is needed to fill the gaps in knowledge and inform better care for dementia patients in the future.

Cancer is one of the leading causes of death and morbidity with a complex pathophysiology. Traditional cancer therapies include chemotherapy, radiation therapy, targeted therapy, and immunotherapy. However, limitations such as lack of specificity, cytotoxicity, and multi-drug resistance pose a substantial challenge for favorable cancer treatment. The advent of nanotechnology has revolutionized the arena of cancer diagnosis and treatment. Nanoparticles (1-100nm) can be used in the treatment of cancer owing to their specific advantages such as biocompatibility, reduced toxicity, more excellent stability, enhanced permeability and retention effect, and precise targeting. Nanoparticles are classified into several main categories. The nanoparticle drug delivery system is particular and utilizes tumor and tumor environment characteristics. Nanoparticles not only solve the limitations of conventional cancer treatment but also overcome multidrug resistance. Additionally, as new multidrug resistance mechanisms are unraveled and studied, nanoparticles are being investigated more vigorously. Various therapeutic implications of nano-formulations have created brand new perspectives for cancer treatment. However, a majority of the research is limited to in vivo and in vitro studies, and the number of nano-drugs that are approved has not much amplified over the years. In this review, we discuss numerous types of nanoparticles, targeting mechanisms along with approved nanotherapeutics for oncological implications in cancer treatment. Further, we also summarize the current perspective, advantages, and challenges in clinical translation.

The rise in the volume, variety and complexity of data in healthcare has made it as a fertile-bed for Artificial intelligence (AI) and Machine Learning (ML). Several types of AI are already being employed by healthcare providers and life sciences companies. The review summarises a classical machine learning cycle, different machine learning algorithms; different data analytical approaches and successful implementation in haematology. Although there are many instances where AI has been found to be great tool that can augment the clinician’s ability to provide better health outcomes, implementation factors need to be put in place to ascertain large-scale acceptance and popularity.

Pakistan is an important country located in South Asia and ranks the world's sixth most populous country. It has diverse landscapes with their own specific vegetation. The country specific vegetative diversity has a great ecological and economic impact on the conservation of local fauna. It has huge potential for sustainable beekeeping industry if properly exploited. Beekeeping in Pakistan is mainly focused in Khyber Pakhtunkhwa and central and north regions of Punjab provinces but nowadays it is growing rapidly across the country. Honey produced in Pakistan enjoys good repute in the Middle East due to its unique taste and quality. Pakistan exports around 4000 tons of the honey with the worth of about $ 23.00 million to Arab countries every year.

The order Mononegavirales harbors numerous viruses of significant relevance for human health, including both established and emerging infections. Currently, vaccines are only available for a small subset of these viruses and antiviral therapies remain limited. Being obligate cellular parasites, viruses must utilize the cellular machinery for their replication and spread. Therefore, targeting cellular pathways used by viruses can provide novel therapeutic approaches. One of the key challenges confronted by both hosts and viruses alike is the successful folding and maturation of proteins. In cells, this task is faced by cellular molecular chaperones, a group of conserved and abundant proteins that oversee protein folding and help maintain protein homeostasis. In this review, we summarize the current knowledge of how the mononegavirales interact with cellular chaperones, highlight key gaps in our knowledge, and discuss the potential of chaperone inhibitors as antivirals.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

The accurate identification of bacterial infections is critical for effective treatment in intensive care units (ICUs), yet current diagnostic methods face limitations in sensitivity and specificity, along-side cost and accessibility issues. Consequently, there's a pressing need for a marker that is economically feasible, rapid, and reliable. Presepsin (PSP), also known as soluble CD14 subtype (sCD14-ST), has emerged as a promising biomarker for early sepsis diagnosis. PSP, derived from soluble CD14, reflects the activation of monocytes/macrophages in response to bacterial infec-tions. It has shown potential as a marker of cellular immune response activation against patho-gens, with plasma concentrations increasing during bacterial infections and decreasing post-antibiotic treatment. Unlike traditional markers such as procalcitonin (PCT) and C-reactive protein (CRP), PSP specifically indicates monocyte/macrophage activation in bacterial infections. While limited studies in critical illness have explored PSP's role in sepsis, its diagnostic accuracy varies with threshold values, impacting sensitivity and specificity. Recent meta-analyses suggest PSP's diagnostic potential for sepsis, yet its standalone effectiveness in ICU infection management remains uncertain. This review provides a comprehensive overview of PSP's utility in ICU set-tings, including its diagnostic accuracy, prognostic value, therapeutic implications, challenges, and future directions.

This article presents a critical review of the current and future state of “business architecture” within the enterprise architecture frameworks. The review is conducted in the following four stages. In the first stage of analysis, the research and publication questions are established. In the second stage, the search for information is designed and implemented using the Prisma methodology, and once the selection criteria were applied, 75 article-type documents were selected from Scopus, WoS, and Dimensions databases. In the third stage, the information analysis is conducted, and then it is synthesized. Finally, in fourth stage, the discussion is elaborated. This research contributes in understanding the current and future trends of business architecture in Industry 4.0. Considering the challenges of the changing market, the results show the need to implement architectures and dynamic business models, including their artifacts, in a globalized context immersed in new technologies.

During the last few years, advancement in the area of biochemistry, science of the material world, engineering and computer-aided testing has directed towards advancement of high-throughput tools for the sake of profiling information encoded in a gene. Single-cell RNA-sequencing (scRNA-seq) tools capable to examine the sequence data from each individual cells and it shows within population variety and permit exploring of cell conditions and transformation by extreme resolution, possibly give out cell sub-types or gene expression fluctuations that are shaded in mass sequencing processes, which shows population-averaged evaluations. Yet, the major disadvantage for this tool is the lack of success to pick out location related details of the RNA transcriptome, as this needs tissue detachment and cell isolation. Location based transcript determination is among the advancements in the area of medical biotechnology as this can find out the molecules like RNA dataset in their intact physical placement in tissue segment with spatial context at the scale of a single-cell, which is very advantageous as compare to single-cell sequencing techniques. These approaches give key observation in the areas of biomedical field sub-disciplines like neurology, embryology, carcinoma study, immune cell investigation and histological activities. Generally, this review mainly focused towards single-cell sequencing methods, technology development, its challenges observed, different expression data analysis mechanisms and their applications in different areas, such as in cancer research, microbes, central nervous system, sex organs and immune-biology, intensifying the essentiality of sequencing tools at single-cell level for the characterization of extremely dynamic individual cells.

Cytomegalovirus (CMV) infection is the most common congenital infection worldwide, affecting between 0.7% and 1% of all live births. Approximately 11% of infected newborns are symptomatic at birth, and between 30% and 40% of these are at risk of developing long-term neurological sequelae. Until recently, the lack of an effective treatment did not justify universal testing of pregnant women. In recent years, however, valacyclovir at a dose of 8 g/day has been shown to be effective in preventing vertical transmission, and ganciclovir has been shown to be effective in preventing long-term sequelae in the treatment of symptomatic neonates. The aim of this article is to review congenital CMV infection, from its epidemiology to its treatment, using the most recent studies in the literature, and to help in the decision to modify protocols for universal testing of pregnant women according to the possibilities of each locality.

Pain is frequently reported during cancer disease, and still remains poorly controlled in 40% of patients. Recent developments in oncology have helped to better control pain. Targeted treatments may cure cancer disease and significantly increase survival. Thereby, a novel population of patients (cancer survivors) has emerged, also enduring chronic pain (27.6% moderate to severe pain). The present review discuss the different options currently available to manage pain in (former) cancer patients in the light of progress made in the last decade. Major progress in the field are recent development of a chronic cancer pain taxonomy now included in International Classification of Diseases (ICD-11) and update of WHO analgesic ladder. Until recently, cancer pain management has mostly relied on pharmacotherapy, opioids being considered as mainstay. The opioids crisis has prompted the reassessment of opioids use, both in cancer patients and cancer survivors. The review focuses on the current utilization of opioids, on the neuropathic pain component often neglected and on techniques and non-pharmacological strategies available which help to personalize patient’s treatment. Cancer pain management is now closer to the management of chronic non-cancer pain i.e. “an integrative pain care” aiming to improve patient’s quality of life.

There has been a surge in the interest for (semi)transparent photovoltaics (sTPVs) in recent years, since the more traditional, opaque, devices are not ideally suited for a variety of innovative appli-cations spanning from smart and self-powered windows for buildings to those for vehicle inte-gration. Additional requirements for these photovoltaic applications are a high conversion effi-ciency (despite the necessary compromise to achieve a degree of transparency) and an aesthetical-ly pleasing design. One potential realm to explore in the attempt to meet such challenges is the bio-logical world, where evolution has led to highly efficient and fascinating light-management structures. In this mini-review, we explore some of the biomimetic approaches that can be used to improve both transparent and semitransparent photovoltaic cells, such as moth-eye inspired structures for improved performance and stability or tuneable, coloured, and semi-transparent devices inspired by beetles’ cuticles. Lastly, we will briefly discuss possible future developments for bio-inspired and potentially bio-compatible sTPVs.

Fecal microbiota transplantation (FMT) is an emerging therapeutic option for a variety of diseases, which is characterized as transferring fecal microorganisms from a healthy donor into the intestinal tract of a diseased receipt. In human clinics, FMT has been used for treating diseases for decades with promising results. In recent years, veterinary specialists adapted FMT in canine patients, however, compared to humans, canine FMT is more inclined to research purposes than practical applications in most cases due to safety concerns. Therefore, in order to facilitate the application of fecal transplant therapy in dogs, in this paper, we aimed to review recent application of FMT in canine clinical treatments as well as possible mechanisms that are involved in the process of therapeutic effect of FMT.

Abstract Traditional plants are known to contain a wide array of secondary metabolites with important biological activity, including anticancer activity. One of such metabolites is saponin; a steroidal or triterpenoid glycoside that is distinguished by its soap forming nature. Different saponins have been characterized and purified so far, and are gaining attention in cancer chemotherapy. Saponins possess incredible structural diversity which has been linked to their activity. They have been implicated in cancer chemoprevention and chemotherapy. Several studies have reported the role of saponins in cancer and their mechanism of actions including cell cycle arrest, antioxidant, cellular invasion inhibition, induction of apoptosis and autophagy. Despite the extensive research and significant anticancer effect of saponins there are no known FDA approved saponin based anticancer drugs due to a number of limitations including toxicities and drug likeness properties. Recent studies have explored options such as structural optimization, combination therapy and drug delivery systems to design saponins with increased efficacy and decreased toxicities. This review discussed the current knowledge on different saponins, their anticancer activity, mechanism of action as well as the current promising research on saponins within the last two decades and recommendations for future studies.

The article discusses the role of humanistic values in the contemporary configuration of cities. Today's times put us in a privileged position as we can observe deep and clear changes happening very quickly. Visible changes are reflected not only in society and culture, but also in the space of developing cities, towns, and metropolises. While characterizing contemporary urban trends and ideas, the philosophical trends that contribute to them and the values on which they are based were discussed. Corrections are also shown, which usually start with slight dissonances and initially slight differences in the content of theses, and as a result lead to completely different views on the world. Contemporary determinants of postmodernism, deconstructivism, ecological ideas, sustainable development, social integration and participation, high-tech, digital, and smart city are discussed in detail.

The treatment of peptides has played an important role in clinical practice since the discovery of insulin therapy in the 1920s. Over 60 peptide drugs are approved in the United States (US and other regional mar-kets, and peptides continue to undergo drug discovery steadily. Peptide research and development has lev-eraged a wider range of structures known from other plant sources, via pharmacology and medicinal molecular biology, beyond its conventional focus on individual endogenous peptides. We build a comprehensive database of peptides that have met scientific studies with more than 150 constantly evolving peptides. Here we provide a simple overview of the peptide-based drug therapy environment, comprising evolutionary points of view, structural properties, operational thresholds, and explanation of the therapeutic area.

Intensive application of synthetic pesticides was the routine practice of commercial agriculture during the Green Revolution to boost agricultural productivity to meet global food demand. Alongside this, the application of chemical pesticides caused adverse effects on the environment and its ecoreceptors including human health. Negative externalities arising from conventional farming instigated the call for sustainable development during the sixties to promote and balance the nexus between socially acceptable economic growth and environmental protection. Consequently, a blueprint of 17 Sustainable Development Goals (SDGs) and 169 targets including ecological stewardship and food security was drafted. Eight out of the 17 SDGs are directly linked to sustainable agriculture based on the direct impact of agriculture, judicious use of critical resources and conservation and the Principles of green chemistry. As a green chemical agent, biopesticides have been shown to have the potentials to substitute chemical pesticides with equal agricultural productivity. The adoption of bio-based pesticides via integrated pest management (IPM) has proven to be the most effective option to influence most dimensions of sustainable agriculture. Therefore, biopesticide-driven IPM if utilized with requisite education, skills and research would boost sustainable agriculture. This chapter reviews the prospects, importance, and limitations of biopesticides to sustainable agriculture and how sustainable agriculture is connected to sustainable development, Green Chemistry, and integrated pest management.

The review analyzes a possible role of autoimmune processes in the pathogenesis of schizophrenia and evolution of concepts on this issue from its origin to present. Risks of autoimmune processes causing schizophrenia are associated with several factors: an impaired functioning of dopaminergic and glutamatergic systems in the brain, kynurenine pathway disorder with overproduction of quinolinic, anthranilic and kynurenic acids (possibly altering both neurons and T-regulators), increased intestinal permeability, as well as food antigens’ effects, stress and infections with various pathogens at different stages of ontogenesis. An increase in the levels of proinflammatory cytokines and chemokines as well as a decrease in the levels of anti-inflammatory ones also may contribute to schizophrenia risks. Schizophrenia often occurs in those patients having various autoimmune diseases and their first-degree relatives. Cases of schizophrenia resulted from autoimmune pathogenesis (including autoimmune encephalitis caused by autoantibodies against various neuronal antigens) are characterized by quite severe cognitive and psychotic symptoms and less favorable prognosis. This severe course may result from the chronic immune damage of the neuronal receptors such as NMDA, GABA, and others and depend on hyperprolactinemia, induced by antipsychotics, but aggravating autoimmune processes [with 2 tables, 4 figures, bibliography: 99 references].

Currently, the COVID‐19 has directly affected the millions of humans lives. The symptoms of the disease involving fever, malaise, chest infection, and breathing difficulties, were identified, and its existence is continuously becoming restructured. The World Health Organization (WHO) had mentioned the wide diagnostics test besides COVID-19 that would also assist medical facilities to recognize infectious diseases as well as currently focusing efficiently on preventing and afterward defeating this viral disease. The infection is usually transmitted among human beings in direct contact, greatest through the liquid bubbles generated through cough, sneeze, or speaking. This paper reviews the COVID 19 pandemic, its history, current updates, contact tracing applications, and use of emerging technologies like the Internet of Things (IoT) and Blockchain for stopping the spreading and provide service online to the patient from a distance.

Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.

The progression of the recent COVID-19 pandemic surprised political authorities as well as scientists. The possibility to design powerful strategies for health care and preserving economic and social activities strongly relies on the capacity to monitor correctly the virus spreading and the immune response in the symptomatic and asymptomatic population. The available data relative to the first pandemic months indicate that the test reliability was progressively improved but also that the extremely variable methodologies used in the diagnostic studies generated data that are often not comparable. This condition prevents a simple metadata analysis for the identification of reliable diagnostics guidelines. Nevertheless, there are converging evidences that combinations of complementary approaches may enable more precise identification of virus infection. Furthermore, it appears that the similarities between SARS-CoV2 and the related types SARS-CoV1 and MERS that caused outbreaks in the last 20 years can be exploited to infer some information for which no direct evidence is still available

Thalassemia is genetic blood disease cause by absence or decrease of one or more of the globin chain synthesis. Beta thalassemia is characterized by one or more mutations in beta globin gene. Absence or reduced amount the of beta globin chains cause ineffective erythropoiesis which leads to anemia. Beta thalassemia has been further divided into three main forms: Thalassemia minor/silent carrier, major and intermedia. More severe form is thalassemia major in which patients depend upon blood transfusion for survival and high level of iron occur as a consequence of consistent blood transfusion. Over loaded iron invokes the synthesis of reactive oxygen species that are toxic in redundancy and triggering the impairment to vascular, endocrine and hepatic system. Thalassemia can be diagnosed and detected through various laboratory tests such as blood smear, prenatal testing (genetic testing of amniotic fluid), DNA analysis (genetic testing) and complete blood count. Treatment of thalassemia intermedia is symptomatic but it can also be managed by splenectomy and folic supplementation. While thalassemia major can be treated by transplantation of bone marrow, regular transfusion of blood and iron chelation treatment, stimulation of fetal hemoglobin production, hematopoietic stem cell transplantation and gene therapy.

Quasicrystals are a class of ordered solids made of typical metallic atoms but they do not exhibit the physical properties usually signaling the presence of metallic bonding and their electrical and thermal transport properties resemble a more semiconductor-like than metallic character. In this paper I first review a number of experimental results and numerical simulations suggesting that the origin of the unusual properties of these compounds can be traced back to two main features. For one thing, we have the formation of covalent bonds among certain atoms grouped into clusters at a local scale. Thus, the nature of chemical bonding among certain constituent atoms should play a significant role in the onset of non-metallic physical properties of quasicrystals bearing transition-metal elements. On the other hand, the self-similar symmetry of the underlying structure gives rise to the presence of an extended chemical bonding network due to a hierarchical nesting of clusters. This novel structural design leads to the existence of quite diverse wave functions, whose transmission characteristics range from extended to almost localized ones. Finally, the potential of quasicrystals as thermoelectric materials is discussed on the basis of their specific transport properties.