Background: We investigated ion channels at the skin, including peripheral nerve endings, which serve as output machines and molecular integrators of many pruritic inputs mainly received by multiple G protein-coupled receptors (GPCRs). Methods: Based on the level of chronic kidney disease–associated pruritus (CKD-aP), subjects were divided into two groups: non-CKD-aP (no or slight pruritus; n=12) and CKD-aP (mild, moderate, or severe pruritus; n=11). Skin samples were obtained from the forearm or elbow during operations on arteriovenous fistulas. We measured ion channels expressed at the skin, including peripheral nerve endings by RT-PCR: Nav1.8, Kv1.4, Cav2.2, Cav3.2, BKCa, Anoctamin1, TRPV1, TRPA1, and ASIC. Results: Expression of Cav3.2, BKCa, and anoctamin1 was significantly elevated in patients with CKD-aP. On the other hand, expression of TRPV1 was significantly reduced in these patients. We observed no significant difference in the levels of Cav2.2 or ASIC between subjects with and without CKD-aP. TRPA1, Nav1.8，and Kv1.4 were not expressed. Conclusions: It was concluded that this greater difference in expression of ion channels at the skin tissue including specific for cutaneous peripheral nerve endings in CKD patients with CKD-aP may increase generator potential related to itching.

Hypertension is a common and growing medical problem that leads to enormous cardiovascular and kidney disease worldwide. While many drugs exist to treat hypertension, there is large individual variation in how a given individual responds to different agents, which contributes to dismal rates of hypertension control. While demographic factors predict which drugs may work better in certain individuals, a great degree of this variation has a genetic basis. In recent years, genome wide association studies have begun to identify specific gene variants that predict drug response to particular agents. This review identifies the major genetic variants influencing antihypertensive response that have emerged from this growing body of work. For novel genetic variants without a previously known biologic basis in blood pressure, it is crucial to validate initial findings in subsequent studies. This information may eventually lead to a more personalized approach to hypertension management that will improve blood pressure control and patient outcomes. The integration of this large amount of data and its real world application will be highly challenging, but strategies to accomplish this are discussed.

The controls of depositional environments on reservoir quality have been evaluated in terms of porosity and permeability of the Gabo Field, Niger Delta, Nigeria. Data used in this research include Well logs, Core data and photos, and grain size analysis for Wells 51 and 52 in the study area. Standard methods as applicable in petrophysical and sedimentological analysis has been adopted. Thirteen reservoir units have been identified in wells 51 and 52 which had 5 reservoirs cored each. The lithofacies units of the identified reservoirs across the study area, comprise pebbly sands, coarse -, medium -, fine- and very fine-grained sands, sandy mud, silty sands and heteroliths. The heteroliths – very fine-grained silty muds are highly bioturbated. Ophiomorpha and skolithos are the major trace fossils with sedimentary structures (ripple lamination, wavy lenticular and planar beds, cross bedded sands, coarsening and fining upward). The facies associations interpreted for the study area are Channel and Coastal barrier systems and the environment of deposition as distributary channel, upper and lower shoreface. The sedimentary processes that deposited facies ranged from high energy regimes, reworking by waves to low energy with periodic influx of silts and muds. The average porosity and permeability for reservoirs in Well 51 is 16.7% and 1317 Md, reservoirs in Well 52 is 28.2% and 2330Md whereas porosity range for the study area is 2% - 32% and permeability is 1.2 – 10600 Md. The reservoir quality reservoir of the sand units in Well 51 (7, 9 and 13) and Well 52 (5, 7, 9, 11 and 13) is excellent - good, this is because of the dynamics environments of deposition (upper shoreface and distributary channel) as well as the mechanisms that play out during deposition such as bioturbation, sorting, sedimentary structures formed. Whereas the poor quality across the reservoirs especially the lower shoreface and prodelta facies is as result of lack bioturbation, connectivity, multiplicity of burrows that may have been plugged by clay and intercalation of shale and sand (heteroliths). This research has shown that environments of deposition have direct influence the reservoir quality in terms of porosity and permeability.

There have been a great number of investigations about the influence of weak magnetic fields on biological systems, such as isolated cells and whole organisms. This is also a subject of considerable medical concern since old epidemiologic observations have indicated a possible tumorigenic effect of these fields. Their mechanism of action, however, is not firmly established. A large number of biological effects of electromagnetic fields have been attributed either to the production of reactive oxygen species (ROS) or to the entrance Ca²⁺ in the cell. A new biochemical pathway is proposed that covers these two possibilities: the primary effect of the magnetic field would be by the mechanism of radical pairs resulting in the production of ROS; these could activate the ion channels TRPM2 producing cellular inflow of Ca²⁺, which would induce the calcium dependent effects. Thus, a large number of biological effects observed up to the present could be explained.

The purpose of this work is to optimize angular extrusion for sever plastic deformation of tubular specimens. A finite element model (FEM) was built in Deform-3D^® for three extrusion dies and analyzed. The dies were ECAP (135°), TCAP with external groove of 90° (denoted as TCAP-e) and TCAP with internal groove of 90° (denoted as TCAP-i). The analysis for process parameters (such as coefficient of friction-μ, die angles-ѱ and φ, temperature - T, and radius ratio-R) showed that TCAP-i was the optimal die in processing Al6063 tubes based on strain and load distribution of the model. The TCAP-i die model was further optimized for different parameters namely die angles, coefficient of friction, deformation ratio and temperature. The results showed that at constant process temperature of 25 °C, the optimal TCAP-i has the following parameters: φ₂=80⁰, Ѱ₁=30⁰, Ѱ₂=80⁰, Ѱ₃=30⁰, μ =0.4 and R =1.5.

In airborne sensor networks (ASNs), the media access control (MAC) protocol is facing with serious unfairness problem due to the traditional protection mechanism of air-to-air communications among aircrafts. Actually by using the binary exponential back-off algorithm at high traffic loads to minimize collisions among users, the latest successful node can always benefit from this kind of MAC to obtain channel resources. Moreover, when taking the existence of the hidden nodes in ASNs into account, the inaccurate traffic load information will further aggravate the system’s unfairness. In this paper, a neighbor-channel-aware (NCA) protocol is proposed to improve the fairness of MAC protocol in ASNs. In the proposal, the NCA frame is firstly added and exchanged between neighbor nodes periodically, which helps to resolve the inaccurate traffic load information, so as to avoid reducing the probability of successful message transmission. Then a traffic-loading based back-off algorithm is involved to make the neighbor nodes cooperatively adjust the inter-frame space (IFS) interval to further reduce the unfairness. The simulation results show that, the proposed MAC protocol can guarantee the satisfied fairness, simultaneously avoiding heavy network overloads to protect key messages’ successful transmissions in ASNs.

Abstract: Congenital hyperinsulinism (CHI) is a rare disorder of glucose metabolism and is the most common cause of severe and persistent hypoglycemia (hyperinsulinemic hypoglycemia, HH) in the neonatal period and childhood. Most cases are caused by mutations in the ABCC8 and KCNJ11 genes that encode the ATP-sensitive potassium channel (KATP). We present the correlation between genetic heterogeneity and the variable phenotype in patients with early-onset hyperinsulinemic hypoglycemia caused by ABCC8 gene mutations. In the first patients, which presented persistent severe hypoglycemia since the first day of life, molecular genetic testing revealed the presence of a homozygous mutation in the ABCC8 gene [deletion in the ABCC8 gene c.(2390+1_2391-1)_(3329+1_3330- 1)del] correlated with a diffuse form of hyperinsulinism (the parents being healthy heterozygous carriers). In the second patient, the onset was on the third day of life with severe hypoglycemia, and genetic testing identified a heterozygous mutation in the ABCC8 gene c.1792C>T (p.Arg598*) inherited on the paternal line, which led to the diagnosis of focal form of hyperinsulinism. To locate the focal lesions, (18)F-DOPA (3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine) PET/CT was recommended (an investigation that cannot be carried out in the country), but the parents refused to carry out the investigation abroad. In this case, early surgical treatment could have been curative. In addition, the second child also presented secondary adrenal insufficiency requiring replacement therapy. At the same time, she developed early recurrent seizures that required antiepileptic treatment. We emphasize the importance and of molecular genetic testing for diagnosis, management and genetic counseling in patients with HH.

This study introduces a low-cost solution provided by a specialized source measure unit (SMU), offering an alternative to conventional source meter units. Through precise IV curve measurements for graphene-channel FETs, the SMU demonstrates its capability in accurately characterizing these devices with minimal noise and high accuracy. This cost-effective solution presents a promising avenue for researchers and developers seeking reliable tools for sensor development and characterization, providing valuable insights into the behavior of graphene-channel FETs and the effect of surface illumination without the need for expensive equipment. Additionally, the SMU was validated with known passive and active components, along with probe station integration for microscale connection, ensuring its effectiveness in capturing accurate measurements. The SMU’s focus on collecting IV curves, coupled with its ability to identify device defects, such as Schottky junctions, contributes to its utility in quality testing for semiconductor devices. Its low-cost nature makes it accessible for various research endeavors, enabling efficient data collection and analysis for graphene-based sensor applications.

Originally developed as a chemotherapeutic agent, miltefosine (hexadecylphosphocholine) is an inhibitor of phosphatidylcholine synthesis with proven antiparasitic effects. It is the only oral drug approved for the treatment of Leishmaniasis and American Trypanosomiasis (Chagas Disease). Although its precise mechanisms are not yet fully understood, miltefosine exhibits broad-spectrum anti-parasitic effects primarily by disrupting the intracellular Ca2+ homeostasis of the parasites while sparing the human hosts. In addition to its inhibitory effects on phosphatidylcholine synthesis and cytochrome c oxidase, miltefosine has been found to affect the unique giant mitochondria and the acidocalcisomes of parasites. Both of these crucial organelles are involved in Ca2+ regulation. Furthermore, miltefosine has the ability to activate a specific parasite Ca2+ channel that responds to sphingosine, that is different to its L-type VGCC human ortholog. Here, we aimed to provide an overview of recent advancements of the anti-parasitic mechanisms of miltefosine. We also explored its multiple molecular targets and investigated how its pleiotropic effects translate into a rational therapeutic approach for patients afflicted by Leishmaniasis and American Trypanosomiasis. Notably, miltefosine's therapeutic effect extends beyond its impact on the parasite to also affect positively the host's immune system. These findings enhance our understanding on its multi targeted mechanism of action. Overall, this review sheds light on the intricate molecular actions of miltefosine highlighting its potential as a promising therapeutic option against these debilitating parasitic diseases.

Hypertension is a frequent risk factor for cardiovascular diseases and the prevalence rate is continuously rising. Multiple pathophysiological mechanisms are responsible for hypertension, necessitating a combination of drugs from different classes for best management. Combination therapy is five times more effective in decreasing blood pressure compared to escalating the dose of a single agent. As per the ACCOMPLISH trial analysis, coupling a renin-angiotensin system inhibitor with a calcium channel blocker is more effective than the combination of a renin-angiotensin system inhibitor with diuretics in reducing major cardiovascular events, cardiovascular-related mortality, and the progression of chronic kidney disease. The renin-angiotensin system can be suppressed by inhibiting the angiotensin-converting enzyme or angiotensin type 1 receptor (AT1R), resulting, in decreased vascular smooth muscle contraction, heart performance, and reduced aldosterone synthesis. Calcium channel blockers work by inhibiting L-type calcium channels, reducing heart performance via negative inotropic, chronotropic, and bathmotropic effects, along with reducing vascular smooth muscle contraction. Diuretics exert their antihypertensive impact by changing body fluid volume and electrolytes. Initially, hypertension treatment commences with a single medication but often, different classes of two or more antihypertensive medications are necessary for achieving the target blood pressure goal. Sometimes, for Resistant hypertension four different classes of antihypertensive medications are necessary to reach the target blood pressure goal.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

A mathematical model that comprehensively captures the real behavior of riverbed deformation, encompassing all pertinent effects, is developed. The underwater slope reformation process, with the generatrix aligned along the flow velocity in the model, is considered. A numerical model is introduced to calculate the flow involving a deformable bottom, and the model's validation is established through rigorous analysis of experimental findings. The research firmly confirms the suitability of the proposed mathematical and numerical model for describing deformations in uneven and unsteady river flows, including the movement of dredging slots and channel quarries. The model's minimal equation count and reliance on empirical constants demonstrate the model's efficiency. The model's predictions align strongly with experimental data, although optimal values of empirical coefficients vary slightly across different experiments. Hence, there is a call for further investigation to derive more universally applicable closure relationships for the model. The importance of validating the model with reliable field data and its potential extension to accommodate hydraulically diverse soils is emphasized. Such an extension is feasible due to the concentration transfer equation, enabling independent calculations for particle fractions of varying sizes as long as the total particle concentration in the stream remains within reasonable limits. This dedicated research contributes significantly to understanding riverbed deformations and advancing accurate modeling and management of riverine environments.

The partial information decomposition (PID) framework is concerned with decomposing the information that a set of random variables has with respect to a target variable into three types of components: redundant, synergistic, and unique. Classical information theory alone does not provide a unique way to decompose information in this manner and additional assumptions have to be made. Inspired by Kolchinsky's recent proposal for measures of intersection information, we introduce three new measures based on well-known partial orders between communication channels and study some of their properties.

This paper is our attempt on the basis of physical theory to bring more clarification on the question ``What is life?'' formulated in the well-known book of Schr\"odinger in 1944. According to Schr\"odinger, the main distinguishing feature of biosystem's functioning is the ability to preserve its order structure or, in the mathematical terms, to prevent increasing of entropy. Since any biosystem is fundamentally open, it is natural to use open system's theory. However, Schr\"odinger's analysis shows that the classical theory is not able to adequately describe the order-stability in a biosystem. Schr\"odinger should also appeal to the ambiguous notion of negative entropy. We suggest to apply the quantum theory. As is well-known, behaviour of the quantum von Neumann entropy crucially differs from behaviour of the classical entropy. We consider a complex biosystem $S$ composed of many subsystems, say proteins, or cells, or neural networks in the brain, i.e., $S=(S_i).$ We study the following problem: if the composed system $S$ can preserve the ``global order'' in the situation of increase of local disorder and if $S$ can preserve its entropy while some of $S_i$ increase their entropies We show that within quantum information theory the answer is positive. The significant role plays entanglement of the subsystems states. In the absence of entanglement, increasing of local disorder generates disorder increasing in the compound system $S$ (as in the classical regime).

Vertical-channel organic dual-gate/base transistors would be highly interesting since vertical organic transistors are the fastest organic transistors demonstrated today. However, incorporating a dual gate/base structure into an ultra-short channel vertical architecture represents a substantial challenge. Here, we successfully realize a new device concept of vertical organic permeable dual-base transistors (OPDBTs), where either of both base electrodes can be used to change the on-currents and tune the threshold voltages. The optimized devices yield a high on-current density of 1.54 A cm^-2 and a large current gain of 9.2×10⁵, corresponding to a high transmission value of 99.998%. The detailed operation mechanisms are investigated by calibrated TCAD simulations with the Poole-Frenkel mobility model, Gaussian density of states and tunneling model. Finally, high-performance logic circuits, e.g. inverter, NAND/AND computation functions are demonstrated with one single OPDBT operating at supply voltages of < 2.0 V. We believe that OPDBTs offer a compact and technologically simple hardware platform with excellent application potential for vertical-channel organic transistors in complex logic circuits.

Acute ischemic strokes are the third leading cause of death and the leading cause of neurological disability worldwide. The oxygen and glucose deprivation associated with ischemic strokes not only leads to neuronal cell death, but also increases the inflammatory response and decreases functional output of the brain. The only intervention approved by US Federal Drug and Food Administration for treatment of ischemic strokes is tissue plasminogen activator (tPA), however, such treatment can only be given within 4.5 hours of the onset of stroke-like symptoms. This narrow time-range limits its application, and it also might induce detrimental rather than beneficial effects to stroke patients by treatment of the tPA. In order to reduce the infarct volume of an acute ischemic stroke while increasing the time period for treatment, emerging therapies reveal great potential by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors with monoclonal antibody (MAB). With successfully application in the treatment of cancer patient by MAB, in this review, we will focus on recent advances on stroke therapy by using MAB on the treatment of stroke by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors. Therefore, developing specific MAB targeting the signaling pathway of stroke will contribute to stroke therapy.

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

In this work modeling and analysis of an integrated opto-fluidic sensor, with a focus on achievement of single mode optical confinement and continuous flow of micro particles in the microfluidic channel for Lab-on-a Chip (LOC) sensing application is presented. This sensor consists of integrated optical waveguides, microfluidic channel among other integrated optical components. A continuous flow of micro particles in a narrow fluidic channel is achieved by maintaining the two sealed chambers at different temperatures and by maintaining a constant pressure of 1Pa at the centroid of narrow fluidic channel geometry. The analysis of silicon on insulator (SOI) integrated optical waveguide at an infrared wavelength of 1550nm for single mode sensing operation is presented. The optical loss is found to be 0.0005719dB/cm with an effective index of 2.2963. The model presented in this work can be effectively used to detect the nature of micro particles and continuous monitoring of pathological parameters for sensing applications.

Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

Finding a good MIMO system model also major issue in Wireless Communication system. It is facing with so many problem, one of the major problem is finding good system model in terms of capacity and transmitting antenna system. In this paper, we analyze the channel capacity of various MIMO system model with some constant SNR level and outage probability. We establish a novel idea for MIMO system models as consider as 2^N- MIMO system model and find-out change in channel capacity when different transmitting antennas with constant SNR and outage probability. The channel capacity ratio CC_R is presented here on the basis of 2^N- MIMO channel capacity model. Number of transmitted antenna presented in MIMO system is increases is well-known however paper shows change in capacity in simple form.

In this paper, we study the effect of parasitic channel on electrical characteristics and power consumptions of vertically stacked gate-all-around (GAA) silicon nanosheet (NS) MOSFETs of the bulk and silicon-on-insulator (SOI) substrates. Through deliberate control of the bottom parasitic channel coverage, we systematically assess its influence on DC, AC, and RF characteristics including power consumption. The observed findings highlight a significant differentiation among the bottom parasitic channels: GAA (i.e., control sample with 100% coverage), omega-shaped gate NS (70% and 80% coverages), and FinFET (60% coverage). Compared with the device with a 60% coverage channel, the device with a 100% coverage channel possesses 3520% and 8030% normalized leakage current improvement for both NFET and PFET under the bulk substrate, respectively. Compared with bulk-substrate devices, the SOI-substrate devices further significantly improve the leakage current. Due to enhanced off-state current leakages in the 100% covered bulk-substrate device, the static power demonstrates a notable improvement (about 98.1%), compared to 60% covered devices. Hence, the utilization of a 60% covered channel will result in a degradation of both device and circuit performance. The observation of GAA NS MOSFET indicates that an increase in the bottom parasitic channel coverage ratio leads to a positive impact on power consumption and leakage currents. The examination presented here is useful in the fabrication of stacked GAA NS MOSFETs.

The only cases where exact distributions of estimates are known is for samples from exponential families, and then only for special functions of the parameters. So statistical inference was traditionally based on the asymptotic normality of estimates. To improve on this we need the {\it Edgeworth expansion} for the distribution of the standardized estimate. This is an expansion in $n^{-1/2}$ about the normal distribution, where $n$ is typically the sample size. The 1st few terms of this expansion were originally given for the special case of a sample mean. In earlier work we derived it for {\it any } standard estimate, hugely expanding its application. We call an estimate $\hat{w}$ of an unknown vector $w\in R^p$, a {\it standard estimate}, if $E\ \hat{w}\rightarrow w$ as $n\rightarrow \infty$, and for $r\geq 1$ the $r$th order cumulants of $\hat{w}$ have magnitude $n^{1-r}$ and can be expanded in $n^{-1}.$ Here we give another huge extension. We give the expansion of the distribution of {\it any smooth function} of $\hat{w}$, say $t(\hat{w})\in R^q,$ giving its distribution to $n^{-5/2}$. We do this by showing that $t(\hat{w})$, is a standard estimate of $t(w)$. This provides far more accurate approximations for the distribution of $t(\hat{w})$ than its asymptotic normality. %NOT USED: The building blocks of the Edgeworth expansions are the {\it cumulant coefficients } of the estimate. These cumulant coefficients are also needed for bias reduction, Bayes estimates and confidence regions. We give {\it chain rules} for the cumulant coefficients of $t(\hat{w})$ in terms of those of $\hat{w}$ and the derivatives of $t(w)$, up to those needed for 5th order Edgeworth expansions for $t(\hat{w})$ and its {\it tilted expansion}, useful for the tail of the distribution.

Malaria, leishmaniasis, and African trypanosomiasis are protozoan diseases that constitute a major global health problem, especially in developing countries; however the development of drug resistance coupled with the toxicity of current treatments have hindered their management. The implication of certain enzymes (dihydrofolate reductase, DHFR) or proteins (potassium channels) in the pathogenesis of these protozoan diseases is undeniable. In this study, a series of three DHFR inhibitors (6-5 fused heterocyclic derivatives X, Y and Z) and one K+ channel blocker (E4031) were screened for their inhibitory effect on Leishmania donovani, Plasmodium falciparum, and Trypanosoma brucei. Resazurin assay was used to assess antitrypanosomal and antileishmanial activities of test compounds, whereas the antimalarial activity was appraised through SYBR Green I test. Moreover, cytotoxicity of test compounds was evaluated on Vero, Raw 264.7 and HepG-2 cells using the resazurin-based test, whilst their pharmacokinetic properties were predicted using the online tool pkCSM. As a result, compound Y revealed a selective (selectivity index range: 2.69 - &gt;61.4; Vero, Raw 264.7 and HepG-2 cells) and broad-spectrum antiprotozoal activity against L. donovani promastigotes (IC50: 12.4 µM) and amastigotes (IC50: 4.28 µM), P. falciparum (IC50: 0.028 µM), and T. brucei brucei (IC50: 0.81 µM). In addition, compound X inhibited the growth P. falciparum (IC50: 0.0052 µM) and T. brucei brucei (IC50: 6.49 µM). In silico screening of the active antiprotozoal compounds revealed positive drug-likeness scores as none of Lipinski's rule of five’s criteria was violated by these compounds. However, in-depth pharmacokinetic and mechanistic studies are warranted to support discovery of novel antiprotozoal agents against malaria, leishmaniasis, and African trypanosomiasis by repurposing K+ channel blocker and DHFR inhibitors.

The phenomenon of seat occupancy in university libraries is a prevalent issue. However, existing solutions, such as software-based seat reservations and sensors-based occupancy detection, have proven to be inadequate in effectively addressing this problem. In this study, we propose a novel approach: a serial dual-channel object detection model based on Faster RCNN. Furthermore, we develop a user-friendly web interface and mobile APP to create a computer vision-based platform for library seat occupancy detection. To construct our dataset, we combine real-world data collection with UE5 virtual reality. The results of our tests also demonstrate that the utilization of personalized virtual dataset significantly enhances the performance of the convolutional neural network (CNN) in dedicated scenarios. The serial dual-channel detection model comprises three essential steps. Firstly, we employ Faster RCNN algorithm to determine whether a seat is occupied by an individual. Subsequently, we utilize an object classification algorithm based on transfer learning, to classify and identify images of unoccupied seats. This eliminates the need for manual judgment regarding whether a person is suspected of occupying a seat. Lastly, the web interface and APP provide seat information to librarians and students respectively, enabling comprehensive services. By leveraging deep learning methodologies, this research effectively addresses the issue of seat occupancy in library systems. It significantly enhances the accuracy of seat occupancy recognition, reduces the computational resources required for training CNNs, and greatly improves the efficiency of library seat management.

In this paper, possibilities for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented and reasons for realizing and utilizing of extended dynamic wavelength and bandwidth algorithms for NG-PON2 networks are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in details, focused on the importance of the decision criterion optimization. For achieving better bandwidth utilization of dedicated wavelengths, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to ONU units and on the optimization of the decision criterion. For analyzing the novel extended DWBA algorithm utilizing for various wavelength allocation cases possible in NG-PON2 networks, a simulation program with the enhancement of the EDBA algorithm is realized. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid TWDM technique.

Channel estimation is an important module to enhance the performance of orthogonal frequency division multiplexing (OFDM) systems. However, the presence of a large amount of noise in multipath fading time-varying channels significantly affects the channel estimation accuracy and thus the recovery quality of the received signals. Therefore, this paper proposes a double-threshold (DT) channel estimation method based on adaptive frame statistics (AFS). The method first adaptively determines the number of statistical frames based on the temporal correlation of the received signals, and preliminarily detects the channel structure by analyzing the distribution characteristics of multipath sampling points and noise sampling points during adjacent frames. Subsequently, a multi-frame averaging technique is used to expand the distinction between multipath and noise sampling points. Finally, the DT is designed to better recover the channel based on the preliminary detection results. Simulation results show that the proposed adaptive frame statistics-double-threshold (AFS-DT) channel estimation method is effective and has better performance compared with many existing channel estimation methods.

This study posits that for appropriately explaining the complex charland (mid-channel island) processes and formulating policy and planning measures, a comprehensive understanding of the dynamic characteristics of the geomorphological, ecological, and human systems holistically is essential. This is also valid for the territorial and maritime areas of Bangladesh. The objectives of this study are: (i) to analyze the salient features and characteristics of the geomorphological and riparian systems of the Bengal Delta; (ii) to analyze the evolutionary discourse of the legal systems concerning eroded (diluvion) and accreted (alluvion) land in Bangladesh; and (iii) to assess characteristics of coping and adaptation strategies of the charland inhabitants. The findings reveal that the delta-building processes, characterized by the dynamic shifts of river channels, and erosion and accretion of charlands have made the land and water systems of the territory very dynamic and unstable – resulting in consistent displacement of settlers and serious deterioration of their socioeconomic status. The historical evolution of land laws and regulations concerning the accreted land favoured vested interests. As no effective institutional framework and structure presently exists in Bangladesh for resettlement planning, formulation of a comprehensive national resettlement policy is therefore urgently needed.

The power of the river does not always work to the benefit of living things; rather, it has the ability to destroy human society and has negative effects on the environment. River Teesta has a prodigious significance on the riverine dweller and its changing precarious behaviour has repercussions on the lives of millions. Utilizing satellite images and 41 years of temporal analysis, the mapping of channel extraction and channel shifting has been demonstrated. Delineating the exact channel boundary is a laborious operation, but MNDWI technique is really valuable in this situation to produce valuable results. Descriptive statistics are used to analyze the Teesta River's active flow line migration trend and channel migration behaviour. A particular river's oscillating character over time has both beneficial and detrimental power, destroying important resources for environmental sustainability and human society while also providing fertile mother earth as a source of wealth. As a result, another goal of the current study was to determine how vulnerable riverine residents were. A livelihood vulnerability index (LVI) based on the riverine inhabitants' exposure, sensitivity, and capacity for adaptation was created. According to the findings, the river's erratic behaviour is putting the people who live beside it in danger. Therefore, it is vitally necessary to implement a capable management strategy to stop bank failure at the Teesta-Dharala confluence in order to save the riverine residents.

Recently, there has been increasing attention toward inhaled nanoparticles (NPs) to develop in-halation therapies for diseases associated with the pulmonary system and investigate the toxic ef-fects of hazardous environmental particles on human lung health. Taking advantage of microfluidic technology for cell culture applications, lung-on-a-chip devices with great potential in replicating the lung air-blood barrier (ABB) have opened new research insights in preclinical pathology and therapeutic studies associated with aerosol NPs. Surprisingly, the air interface in such devices, which makes them tremendously unique among the other common liquid-based cellular mi-crosystems and enables exposure of cultivated cells to the drug/toxic aerosols, has been largely disregarded. Accordingly, there exists a significant research gap in the comprehensive under-standing of the NPs’ dynamics in the lung-on-a-chip devices, which is momentous to control the injection of aerosols to the target area and attain a desired physiochemical efficacy. To address this research gap, a numerical parametric study is presented to provide a deep insight into the dynamic behavior of the airborne NPs in a gas-liquid dual-channel lung-on-a-chip device with a porous membrane separating the channels. A finite element multi-physics model is developed to enable a particle tracing investigation simultaneously in both air and medium phases to replicate the in vivo conditions avoiding laborious and costly experimental trials. The results include the impact of fluid flow as well as geometrical properties on the distribution, deposition, and translocation of the NPs with diameters ranging from 10 nm to 900 nm in the lung-on-a-chip. The obtained results strongly suggest the aerosol injection of NPs instead of the aqueous solution for more efficient deposition on the substrate of the air channel and higher translocation to the media channel. The current study proposes to optimize the affecting parameters to control the injection and delivery of aerosol par-ticles into the lung-on-chip device depending on the objectives of biomedical investigations and provides optimized values for some specific cases. Therefore, this study can assist scientists and researchers in complementing their experimental investigation in future preclinical studies on pulmonary pathology associated with inhaled hazardous and toxic environmental particles, as well as therapeutic studies for developing inhalation drug delivery.

Tri-dimensional (3D) cell aggregates or spheroids are considered to be closer to physiological conditions than traditional 2D cell culture. Mesenchymal stem cells (MSCs) assembling in spheroids have increased the survival of transplanted cells. The regulation of the biological processes that maintain crucial physiological reactions of MSCs is closely related to the functioning of ion channels. The pattern of expression, role and regulatory mechanisms of ion channels could be significantly different in 3D compared to 2D culture, and, thus, needed to be properly analyzed on the level of ionic currents. We developed a specific approach that allowed us to register, for the first time, endogenous ion channels in endometrial MSCs (eMSCs) assembled in spheroids. Particularly, using the single-channel patch-clamp technique, we have recorded the activity of ion channels and observed their functional interplay in mechanosensitive clusters. Our experimental protocol could be applied for identification and studying of ion channels in 3D cell cultures.

Neurological complications of infection by the mosquito-borne Zika virus (ZIKV) include Guillain-Barré syndrome (GBS), an acute inflammatory demyelinating polyneuritis. GBS was first associated with recent ZIKV epidemics caused by the emergence of ZIKV Asian lineage in South Pacific. Here, we hypothesize that ZIKV-associated GBS relates to a molecular mimicry between viral envelope E (E) protein and neural proteins involved in GBS. Analysis of ZIKV epidemic strains showed that glycan loop (GL) region of the E protein includes an IVNDT motif which is conserved in voltage-dependent L-type calcium channel subunit alpha-1C (Cav1.2) and Heat Shock 70 kDa protein 12A (HSP70 12A). Both VSCC-alpha 1C and HSP70 12A belong to protein families which have been associated with neurological autoimmune diseases in central nervous system. The purpose of our in silico analysis is to point out that IVNDT motif of ZIKV E-GL region should be taken in consideration for the development of safe and effective anti-Zika vaccines by precluding the possibility of adverse neurologic events including autoimmune diseases such as GBS.

As e-commerce services and Internet technology have rapidly developed in recent years, many services and applications integrating these technologies can now be completed online. These commercial activities include online auctions, online ticketing and online payments. The client shops from the store online, andthe store delivers the goods to the client. The goods can be divided into digital products without entities, as well as actual entities. If it is a physical product, the store will deliver the package to the client through itslogistics. However, there have been many cases of switched goods purchased by clients in recent years. Earlier, some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content. Only the sender and the receiver would know that the secret information was hidden in the signature. So the privacy of this subliminal message couldbe ensured. We apply this concept to the logistics environment to design secure logistics architecture with subliminal messages. The client can check the subliminal message of the received package, and know whether the package has been switched by malicious people. In addition, the proposed scheme also applies sensor technology;the client can check the GPS location, the temperature and humidity at any time during the delivery process. So intelligent logisticswouldthereby be achieved. This paper proposes an intelligent and secure package sensoring logistics system based on a subliminal channel. The proposed architecture uses the related mechanisms tosolve the problems of a logistics system, including how to achieve mutual authentication, data integrity, anti-switch package, package location and status tracing, resisting replay attacks, forward and backward secrecy, and non-repudiation issues.

Micro channel tube (MCT) is widely employed in industry due to its excellent efficiency in heat transfer. An MCT is commonly produced through extrusion within a porthole die, where severe plastic deformation is inevitably involved. Moreover, the plastic deformation, which dramatically affects the final property of the MCT, varies significantly from location to location. In order to understand the development of the microstructure and its effect on the final property of the MCT, the viscoplastic self-consistent (VPSC) model, together with the finite element analysis and the flow line model, is employed in the current study. The flow line model is used to reproduce the local velocity gradient within the complex porthole die, while VPSC model is employed to predict the evolution of the microstructure accordingly. In addition, electron backscatter diffraction (EBSD) measurement and mechanical tests are used to characterize the evolution of the microstructure and the property of the MCT. The simulation results agree well with the corresponding experimental ones. The influence of the material’s flow line on the evolution of the orientation and morphology of the grains, and the property of the produced MCT are discussed in detail.

Equal-Channel Angular Pressing (ECAP) is a method used to introduce severe plastic deformation into a metallic billet without changing its geometry. In special cases strain localization occurs and a pattern consisting of regions with high and low deformation (so-called shear and matrix bands) can emerge. This paper studies this phenomenon numerically adopting two-dimensional finite element simulations of one ECAP pass. The mechanical behavior of aluminum is modeled using phenomenological plasticity theory with isotropic or kinematic hardening. The effects of the two different strain hardening types are investigated numerically by systematic parameter studies: While isotropic hardening only causes minor fluctuations in the plastic strain fields, a material with high initial hardening rate and sufficient strain hardening capacity can exhibit pronounced localized deformation after ECAP. The corresponding finite element simulation results show a regular pattern of shear and matrix bands. This result is confirmed experimentally by ECAP-processing of AA6060 material in a severely cold worked condition, where microstructural analysis also reveals the formation of shear and matrix bands. Excellent agreement is found between the experimental and numerical results in terms of shear and matrix band width and length scale. The simulations provide additional insights regarding the evolution of the strain and stress states in shear and matrix bands.

Channel bends are one of the most important characteristic features of natural streams. These bends often create the conditions for a hyporheic zone, which has been recognized as a critical component of stream ecosystems. The streambed vertical hydraulic conductivity (K_v), vertical hydraulic gradient (VHG) and Darcian flux (DF) in the hyporheic zone were estimated at 61 locations along a channel bend of the Beiluo River during July 2015 and January 2016. All the streambed attributes showed great spatial variability along the channel bend. Both upward fluxes and downward fluxes occurred during the two test periods, most of studied stream sections were controlled by downwelling, indicating stream water discharge into the subsurface. The average downward flux was higher at the downstream side than at the upstream side of the channel bend, especially in July 2015. The distribution of streambed sediment grain size has a significant influence on the variability of K_v; high percentages of silt and clay sediments generally lead to low K_v values. Higher K_v at the depositional left bank at the upstream site shifted toward the erosional right bank at the downstream site, with K_v values positively correlated with the water depth. This study suggested that the variabilities of K_v and VHG were influenced by the stream geomorphology and that the distribution of K_v was inversely related, to a certain extent, to the distribution of VHG across the channel bend. K_v and VHG were found to have opposite effects on the DF, and the close relationship between K_v and DF indicated that the water fluxes were mainly controlled by K_v.

Elevated blood glucose levels, known as glycemia, play a significant role in sudden cardiac arrest, often resulting in sudden cardiac death, particularly among those with diabetes. Understanding this link has been a challenge for healthcare professionals, leading many research groups to investigate the relationship between blood glucose levels and cardiac electrical activity. Our hypothesis suggests that glucose-sensing mechanisms in cardiac tissue could clarify this connection. To explore this, we adapted a single-compartment, in-silico model of the human atrial node's action potential. We incorporated glucose-sensing mechanisms with voltage-gated sodium ion channels using ordinary differential equations. Parameters for the model were based on existing experimental studies to mimic the impact of glucose levels on atrial node action potential firing. Simulations using voltage clamp and current clamp techniques showed that elevated glucose levels decreased sodium ion channel currents, leading to a reduction in the sinoatrial node action potential frequency. In summary, our model provides a cellular-level understanding of how high glucose levels can lead to bradycardia and sudden cardiac death.

This paper presents a comprehensive evaluation of metal foam employment within polymer electrolyte fuel cells (PEFCs) and compares it with conventional serpentine channels from both experiment viewpoints and computational fluid dynamics simulation. The experiments are designed to study the effects of material, area density, compression ratio, and final thickness of metal foam. Additionally, the influence of housing plate material and relative humidity (RH) is also tested for the first time. The results reveal that at RH=75-100%, the best distributor design is nickel foam with a compression ratio of 70%, a final thickness of 0.5mm, and SS-304 housing plate, which delivers 3110 mA cm^-2 as limiting current density that is scarce in the literature. The PEFC with this foam distributor shows a 10% improvement in maximum power density and 45% in limiting current density compared to the serpentine channel case. While at RH=30%, the same foam flow field with a final thickness of 1mm is a superior option. The experiments also indicate that maximum power density increases by 23% as the compression ratio rises from 0 to 70%, while reducing final thickness from 1 to 0.5 mm causes a 19% enhancement in cell performance. Simulation results reveal that metal foam is more successful in evenly reactant distribution so that the average oxygen mass fraction at the cathode catalyst layer is increased by 38% in the metal foam case compared to the serpentine channel.

In this manuscript, we reassess the data on beta-amyloid-induced changes of intracellular ions concentrations published previously by Abramov et al. (2003, 2004). Their observations made using high-resolution confocal microscopy with fast temporal resolution of images formed by fluorescent ion-sensitive fluorescent probes in living cells represent an unequivocal support for the amyloid channel theory. However, closer look reveals multiple facts which cannot be explained by channel formation in plasma membrane. Recently proposed amyloid degradation toxicity hypothesis provides the interpretation to these facts by considering that channels are formed in the lysosomal membranes.

Neuroscience is a vast discipline that deals with the anatomy, biochemistry, molecular biology, physiology and pathophysiology of central and peripheral nerves. Advances made through basic, translational, and clinical research in the field of neuroscience have great potential for long-lasting and beneficial impacts on human health. The emerging field of biological therapy is intersecting with the disciplines of neuroscience and rheumatology, creating new horizons for interdisciplinary and applied research. Biological drugs, growth factors, neuropeptides and monoclonal antibodies are being developed and tested for the treatment of painful arthritic and rheumatic diseases. This concise communication focuses on the solutions provided by the fields of neuroscience and neuroimmunology for real-world clinical problems in the field of rheumatology, focusing on synovial joint pain and the emerging biological treatments that specifically target pathways implicated in osteoarthritis pain in peripheral nerves.

For voltage-gated Ca2+ channel (VGCC), its α2δ subunits are traditionally considered to be auxiliary subunits that regulates VGCC trafficking to the plasma membrane. The antiepileptic, antinociceptive and anxiolytic gabapentin (GBP) has previously been shown to bind the VGCC α2δ subunits with high affinity to disrupt VGCC trafficking. Yet, the interaction between GBP and α2δ still remains poorly understood from a structural point of view. For instance, it is not clear yet what the structural implication is of α2δ-1-bound GBP against VGCC trafficking. With a set of experimental data-driven structural analysis of the VGCC α2δ-1 and its ligand GBP, this article postulates for the first time that: 1), α2δ-1 bound GBP stabilizes the α2δ-1-GBP complex structure; 2), α2δ-1 bound GBP restrains the conformational flexibility of α2δ-1; 3), α2δ-1-bound GBP establishes an electrostatic axis consisting of Q535 (Gln535)-R241 (Arg241)-GBP (gabapentin)-D452 (Asp452), which constitutes an energetically favourable contribution towards the structural stability of the α2δ-1-GBP complex and helps restrains the conformational flexibility and local structural rigidification of α2δ-1; and 4), GBP-induced local conformational inflexibility and structural rigidification of α2δ-1 is one key step in the pharmacological disruption of VGCC trafficking by GBP.

It is shown that the termination of the channeling of the fundamental radiation mode in the waveguide can be observed upon heating of an optical integrated circuit based on proton exchange channel waveguides formed in a lithium niobate single crystal. This process is reversible, but restoration of waveguide performance takes tens of minutes. The effect of the waveguide disappearance is observed upon rapid heating (5 °C/min) from a low temperature (minus 40 °C). This effect can lead to a temporary failure of navigation systems using fiber optic gyroscopes with modulators based on a lithium niobate crystal

This paper has two major parts. In the first part histogram equalization for the image enhancement was implemented without using the built-in function in MATLAB. Here, at first, a color image of a rat was chosen and the image was transformed into a grayscale image. After this conversion, histogram equalization was implemented on the grayscale image. Later on, in the same image for each RGB channel, histogram equalization was implemented to observe the effect of histogram equalization on each channel. In the end, the histogram equalization was implemented to this specific color image of a rat. In the second part, for the grayscale image in part 1, the desired histogram of another colored image of a rat was introduced and histogram specification was implemented on the original colored image.

Among the most important variables in the design of falling film microreactors (FFMRs) is the liquid film thickness as well as the gas/liquid interfacial area, which dictate the mass and heat transfer rates. In a previous work conducted in our lab the characteristics of a free-falling Newtonian liquid film have been studied and appropriate correlations have been proposed. In this work the geometrical characteristics of a non-Newtonian shear thinning liquid, flowing in an inclined open microchannel, have been experimentally investigated and design correlations that can predict with reasonable accuracy the features of a FFMR have been proposed. The test section used was an open μ-channel with square cross section (Wo=1200 μm) made of brass which can be set to various inclination angles. The liquid film characteristics were measured by a non-intrusive technique that is based on the features of a μ-PIV system. Relevant CFD simulations revealed that the volume average dynamic viscosity over the flow domain is practically the same as the corresponding asymptotic viscosity value, which can thus be used in proposed the design equations. Finally, a generalized algorithm for the design of FFMRs, containing non-Newtonian shear thinning liquids, is suggested.

This paper has two major parts. In the first part histogram equalization for the image enhancement was implemented without using the built-in function in MATLAB. Here, at first, a color image of a rat was chosen and the image was transformed into a grayscale image. After this conversion, histogram equalization was implemented on the grayscale image. Later on, in the same image for each RGB channel, histogram equalization was implemented to observe the effect of histogram equalization on each channel. In the end, the histogram equalization was implemented to this specific color image of a rat. In the second part, for the grayscale image in part 1, the desired histogram of another colored image of a rat was introduced and histogram specification was implemented on the original colored image.

Vegetation has a significant influence on velocity distribution and turbulent energy in a confluence channel. A laboratory measurement with ADV was used to investigate the flow through a Y-shaped confluence channel partially covered with rigid vegetation on its inner bank. In this study, the flow velocities in cases with and without vegetation were measured by the ADV in a Y-shaped confluence channel. The results clearly show that the existence of non-submerged rigid plants has changed the internal flow structure, that the velocity in the non-vegetated area is greater than in the vegetated area, and that there is a large exchange of mass and momentum between the vegetated and non-vegetated areas. The velocity on both sides is significantly reduced when vegetation is present. In the vicinity of tributaries, due to the presence of vegetation, the high-velocity area moved rapidly to the middle of the non-vegetated area, and the secondary flow phenomenon disappeared. In the mainstream, when vegetation was present, circulation disappeared, and the degree of lateral mixing decreased. The presence of vegetation caused a great change in the internal flow structure and made the flow in non-vegetated areas more intense.

We propose a wave-like design on the surface of cathode channels (wave form cathode channels) to improve oxidant delivery to gas diffusion layers (GDLs) [1-2]. We performed experiments using PEMFCs combined with wave form surface design on cathodes. We varied the factors of the distance between wave-bumps (the Adhesive distance, AD), and the size of the wave-bumps (the Expansion ratio, ER). The ADs are 3, 4, and 5 times the size of the half-circle bump’s radius, and the ERs are 1/1.5, 1/2, and 1/3 times the channel’s height. We evaluated the performances of the fuel cells, and compared the current-voltage (I-V) relations. For comparison, we prepared PEMFCs with conventional flat-surfaced oxygen channels. Our aim in this work is to identify fuel cell operation by modifying the surface design of channels, and ultimately to find the optimal design of cathode channels that will maximize fuel cell performance.

Satellite derived bathymetry methods over coastal areas were born to deliver basic and useful information like bathymetry. However, the process is not straightforward, the main limitation being the need of field data. The Self-calibrated Spectral Supervised Shallow-water Modeler (4SM) method was tested to obtain coastal bathymetry without the use of any field data. Using LANDSAT-8 multispectral images from 2013 to 2016, a bathymetric time series was produced. Groundtruthed depths and an alternative method, Stumpf’s Band Ratio Algorithm, were used to verify the results. Retrieved (4SM) vs groundtruthed depths scored an average r2 (0.90), and a low error (RMSE = 1.47 m). Also 4SM showed, over the whole time series, the same average accuracy of the control method (40%). Advantages, limitations and operability under complex atmosphere and water column conditions, and high and low-albedo bottom processing capabilities of 4SM are discussed. In conclusion, the findings suggest that 4SM is equally accurate as the commonly used Stumpf’s method, the only difference being the independence of 4SM to previous field data, and the potential to deliver bottom spectral characteristics for further modelling. 4SM represents a significative advance in coastal remote sensing potential to obtain bathymetry and optical properties of the marine bottom.

The development of new diabetes drugs continues to be explored. Loureirin B, a flavonoid, extracted from Dracaena cochinchinensis, has been confirmed to increase insulin secretion and decrease blood glucose levels. For understanding the mechanism, a series of experiments had been employed based on computational methods and cell experiments. The insulin secretion significantly increased with the incubation of 0.01μM loureirin B for 4 hours. The viability of Ins-1 cells showed no significant difference with the treatment of loureirin B. Through computational methods, we hypothesized that loureirin B could interacts with K_ATP channels to promote insulin secretion. In cell experiments, it could be found that the current of K_ATP channel of Ins-1 cells was inhibited by the effect of loureirin B. After then, the voltage-dependent calcium channels were activated, the increase of Cx43 protein expression might mediate the Ca²⁺ to the intracellular. In summary, it could be concluded that loureirin B promoted insulin secretion mainly through inhibiting K_ATP current, the influx of Ca²⁺ to the Intracellular and the expression of Cx43.

The smart management of water resources is an increasingly important topic in today's society. In this context, the paradigm of Smart Water Grids (SWGs) aims at a constant monitoring through a network of smart nodes deployed over the water distribution infrastructure. In such a way, a continuous assessment of water quality and state of health of the pipeline infrastructure can be achieved, allowing an early detection of leaks and water contamination. Acoustic wave-based technology has arisen as a viable communication technique among the nodes of the network. Such technology can be suitable to replace traditional wireless networks in SWGs, as the acoustic channel is intrinsically embedded in the water supply network. However, the fluid-filled pipe is one of the most challenging media to be employed for data communication. This paper aims at reviewing those works dealing with acoustic-based communication networks in real large-scale urban water supply networks. An overview on the characteristics, trends and design challenges of existing works is provided as a guideline for future research.

With the urgent need of precise positioning faced by internet of things (IoT) applications, the universality and cost of indoor positioning devices become key factors. Since the 5G network has been widely deployed, new opportunity is brought by tightly fusing the traditional low-cost sensors, i.e., the magnetometer. In this study, using 5G channel state information (CSI) and geomagnetic data, a multi-input convolutional neural network (CNN) localization system was proposed. First, to generate a data tensor that is easy for CNN processing, the raw data was reconstructed individually. Then, to comprehensively incorporate the features of 5G CSI and geomagnetic strength data, the ReLU function was chosen as the activation function of the convolutional layer. After that, a multi-input CNN was trained using the incorporated geomagnetic strength and CSI amplitude in the off-line side, and the trained CNN was recorded as a location fingerprint, which can be used for the user position prediction. Finally, in the online side and using a multi-input CNN, the 2-D coordinates are estimated and tested indoors in a typical conference room scenario. The results showed that longer sampling time of fingerprint data result in better uniqueness of the reference point, while the data collection time of locating points does not need to be long. Taking the positioning efficiency and accuracy into consideration, a sampling time of 3s at the reference point and 0.2s at the locating point are recommended. The positioning accuracy using the proposed method was 1.41 m, with an improvement of 22.9% compared with the 5G positioning, and an improvement of 18.0% compared with the 5G and geomagnetic fusing positioning using single CNN.

In this paper, we develop a tractable mathematical model and emulation framework for communicating information through water using acoustic signals. Water is considered as one of the most complex mediums to model owing to its vastness and variety in characteristics depending on the scenario, what kind of water-body (lakes, rivers, tanks, sea etc.) and geographical location of the water-body is considered. Our proposed mathematical model involves the concept of damped harmonic oscillators to represent the medium (water) and Milne’s oscillator technique to map the interaction between the acoustic signal and water. Wave equations formulated for acoustic pressure and acoustic wave velocity are used to characterize the travelling acoustic signal. Signal strength, phase shift and time-delay generated from the mathematical model are fed to a Simulink-based emulator framework to generate channel samples and channel impulse responses. The emulator uses wide sense stationary uncorrelated scattering (WSSUS) assumption and finite sum-of-sinusoids (SOS) with uniformly distributed phase to generate the channel samples. Using the emulator platform it is possible to generate amplitude variation profile, Doppler shift and spread experienced by any travelling signal through different underwater communication scenarios. Such an emulator platform can be used to simulate different communication scenarios, underwater network topologies, data to train different learning models and predict performance of different modulation, multiplexing, error correction and multi-access techniques for underwater acoustic communications (UWAC) systems.

We conducted the meander evolution experiments incorporating the effects of riparian vegetation and the series of upper vortex flow disturbances induced by a scour pit simultaneously. Two employed nonlegume plants with salinity and alkalinity resistance, had uniform degrees of seedling normal growth and different lengths of root networks. Our results show that riparian vegetation in general can consolidate the single-thread channel planform without branching outward under the flooding flow conditions. Transverse point bars on inner banks were instead by downstream scroll bars in overall channel for long, unless the coupling of riparian vegetation and flood scour. Shallow-rooted plant was inadequate to resist the inner-bank cutting effect brought by the upper vortex flow. Deep-rooted plant can stabilize the bank-lines and thalweg significantly, but that was susceptible to locally low vegetation coverage. Using evolutionary spectral analysis based on thalweg, we found streamwise high-frequency distribution of bed topography mainly concentrated downstream the bifurcation interface in unvegetated scenario when faced with a flood, shrank to the upper isolated turning interface in shallow-rooted scenario, and conversely stood out along the bare roots disturbed region in deep-rooted scenario. This experimental study expands a much wider understanding of vegetation effects in hydro-bio-geomorphological systems engineering.

It is expected that scholars will continue to strengthen the depth and breadth of theoretical research on RIS, so as to provide a higher theoretical upper bound for the engineering application of RIS. While making breakthroughs in academic research, great progress has been made in engineering application research and industrialization promotion. This article will provide an overview of RIS engineering applications, mainly including the typical features, typical classifications, and typical deployment scenarios of RIS. Then the challenges and candidate solutions of the RIS are systematically and deeply analyzed, involving the cascade channel decoupling for solving the RIS beamforming, the influences and solutions of RIS regulation constraints, RIS system architecture of network controlled mode, the integrated channel regulation and information modulation, TDD mechanism used for RIS. Future trends and challenges are also provided.

This research focuses on the customer orientation of insurance brokers, whose activity is regulated by the Law of 26/2006 of July 17 on the mediation of private insurances and reinsurances. The goal is to ascertain whether the intermediation inherent in the insurance broker’s activity, which implies a customer-oriented service, entails a positive behaviour that transcends the immediate environment, reaching society. This study presents a comparative analysis between the insurance brokerage society, characterised by providing a personalised customer service, and banks’ advisory services on insurance. To this end, we study the evolution of the total volume of business and new production, compared for a portfolio of insurance products. The results presented in this research suggest that the customer values the advisory service provided by the broker. However, for a particular business segment in standardised insurance products and products related to banking assets, customers are more likely to resort to the bank’s services. In addition, the results indicate that the commission percentages applied by the entities operating in the banking insurance channel exceed those perceived by the insurance broker. With all this, intermediation in the development of the insurer’s activity can entail an ethical and social behaviour that involves customer-orientation and, possibly, social service, which does not always benefit the insurer.

The target area of the present study is the entrance to the Sulina channel in the Black Sea, the zero-kilometer of the Danube River. This represents the southern gate of the seventh Pan-European transport corridor and is subjected to high navigation traffic. The coastal environment at the Danube’s mouth is very often subjected to strong environmental conditions inducing high risks for navigation hazards. From this perspective, the objective of the present work is to provide a more comprehensive picture concerning the past and future expected dynamics of the environmental matrix in this area, including especially wind and wave conditions. An analysis of some in situ measurements performed at the zero kilometer of the Danube is first carried out for the 15 years 2009-2023. A second analysis is based on data provided by regional climate wind models. Two 30-year periods are considered, the recent past (1976-2005), when also comparisons with ERA5 reanalysis data were performed, and the near future (2041-2070), when two different models and three climate scenarios were considered. Finally, using as a forcing factor each of the wind fields before analyzed, simulations with a spectral wave model were carried out and the nearshore wave conditions were evaluated. The results show that both extreme wind and wave conditions are expected to be slightly enhanced in the future. Strong wind fields are characteristic in this area, with wind gusts exceeding on average with more than 70% the maximum hourly averaged wind speed. As regards the waves, due to the complex nearshore phenomena, considerable enhancements in terms of significant wave heights are induced. Furthermore, there is also a high risk of rogue wave’s occurrence.

This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework's capabilities. Calibration and verification demonstrate the models' effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory's neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.

Experimental tests and numerical analyses were carried out on short, thin-walled channel columns with modified cross-sectional shape. The columns were loaded with an axial compressive force applied at the center of gravity of the cross section. Tests were carried out on a universal testing machine, while numerical analyses were performed in ANSYS software. The purpose of the tests was to determine the values of critical forces for the compressed columns and to determine the values of maximum forces at which failure of the columns occurs. Critical forces were determined based on the strain-averaged method. Based on the study, it was found that the strength and resistance to loss of stability of columns is primarily affected by their stiffness, and therefore by the shape of the cross-sections. In addition, for short columns, it seems more important to determine the value of maximum forces than the values of critical forces.

Low-complexity ultrasound systems are increasingly desired for wearable point-of-care ultra-sound and massive-channel ultrasound for 3-D matrix imaging. However, the system complexity is closely associated with the imaging capabilities, remaining as a challenge. To resolve this limitation, this study revisits the general structures of analog and digital beamformers and in-troduces a hybrid approach to implement efficient ultrasound systems. The suggested hybrid beamforming takes two stages, where the first analog stage partially beamforms M-channel RF signals to N sum-out data (M-to-N beamforming), and the second digital stage beamforms N partial sums to single final beamformed data (N-to-1 beamforming). Our approach was systematically designed and implemented, which was demonstrated with a customized 64-channel 1-D phased array using a tissue mimicking phantom. The demonstrated results indicate that the analog-digital hybrid beamforming can be applied to any kind of arrays for sophisticated 3-D imaging and tiny wearable ultrasound applications.

The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal. The mechanism employs a binary exponential backoff (BEB) algorithm in the medium access control (MAC) layer. Such an algorithm increases the backoff interval whenever a collision is detected to minimize the probability of subsequent collisions. However, the expansion of the backoff interval causes degradation of the radio spectrum utilization (i.e., bandwidth wastage). That problem worsens when the network has to manage the channel access to a dense number of stations, leading to a dramatic decrease in network performance. Furthermore, a wrong backoff setting increases the probability of collisions such that the stations experience numerous collisions before achieving the optimal backoff value. Therefore, to mitigate bandwidth wastage and, consequently, maximize the network performance, this work proposes using reinforcement learning (RL) algorithms, namely Deep Q Learning (DQN) and Deep Deterministic Policy Gradient (DDPG), to tackle such an optimization problem. As for the simulations, the NS-3 network simulator is used along with a toolkit known as NS3-gym, which integrates a reinforcement-learning (RL) framework into NS-3. The results demonstrate that DQN and DDPG have much better performance than BEB for static and dynamic scenarios, regardless of the number of stations. Moreover, the performance difference is amplified as the number of stations increases, with DQN and DDPG showing a 27% increase in throughput with 50 stations compared to BEB. Furthermore, DQN and DDPG presented similar performances.

This paper studies the performance improvement of the IEEE 802.15.4 nonbeacon-enabled mode originated by the inclusion of the Request-To-Send/Clear-To-Send (RTS/CTS) handshake mechanism resulting in frame concatenation. Under IEEE 802.15.4 employing RTS/CTS, the backoff procedure is not repeated for each data frame sent but only for each RTS/CTS set. The maximum throughput and minimum delay performance are mathematically derived for both the Chirp Spread Spectrum and Direct Sequence Spread Spectrum Physical layers for the 2.4 GHz band. Results show that the utilization of RTS/CTS significantly enhances the performance of IEEE 802.15.4 applied to healthcare in terms of bandwidth efficiency.

Land Surface Temperature (LST) estimation has been studied for several purposes, while the optimal method of estimating the LST has not been criticized yet. This research explores the optimum method in Land Surface Temperature (LST) estimation using LANDSAT-8 imagery data. Four different LST retrieval approaches, the Radiative Transfer Equation-based method (RTE), the Improved Mono-Window method (IMW), the Generalized Single-Channel method (GSC), and the Split-Window algorithm (SW), were calculated to present the LSTs over Buriram Town Municipality, Thailand. The calculated LSTs from these four methods were compared with the ground-based temperature data, taken on the same date and time of the employed LANDSAT-8 images. For this reason, the optimum method of the LST calculation was justified by considering the lowest normalized root means square error (NRMSE) values. As a result, the SW algorithm presents an optimum method in LST estimation. Regarding the SW, this algorithm requires not only the atmospheric profiles during satellite acquisition but also the retrieval of several coefficients. Besides, the LST retrieval method based on the SW algorithm is sensitive to water vapor content and coefficients. Although the SW algorithm is an optimum method explored in this study, it is emphasized that the adjustable values of coefficient response to the atmospheric state may be recommended. With these conditions, the SW algorithm can generate the land-surface temperature over the mixed land-use and land cover on the LANDSAT-8 images.

The KcsA is a prokaryotic potassium-oriented channel, which is sourced from the Streptomyces lividans soil bacteria. From extensive studies that have been carried over the KcsA potassium channel, it has been proved that various factors enable the gating and shuttling of the potassium ions into and out of the cells. Some of the factors include the different concentration of protons in the inside and outside membrane. The other factor is the existence of the selectivity filter equipped in the exit of channel pore, which enables the movement of the K⁺ ions. Not only are potassium ions present in the channel but also sodium ions. Potassium and sodium ions are the ions that are essential in the conductivity of a cell because of their charge. An intuitive idea about why K⁺ ions are at least 10,000 times more permeant than Na⁺ ions is presented in various entities. The hypothesis is that the selectivity ratio is probably related to the successive entry of Na⁺ ions, based on the premise that the ratio seems to be relevant to unpredictable quantities caused by Brownian corrosion of ions.

Significant amounts of anthropogenic radionuclides were introduced in ocean waters following nuclear atmospheric tests and development of the nuclear industry. Dispersion of artificial dissolved radionuclides has been extensively measured for decades over the European continental shelf. The radionuclide measurement and release fluxes databases provided here represent an exceptional opportunity to validate dispersion hydrodynamic models. MARS hydrodynamic model have been applied at different scales to reproduce in realistic conditions the measured dispersion. Specific methods have been developed to obtain qualitative and quantitative results and perform model/measurement comparisons. Model validation concerns short to large scales with dedicated surveys following the dispersion: it was performed within two and three dimensions framework and from minutes and hours following a release up to several years. Results are presented concerning the dispersion of radionuclides in marine systems deduced from standalone measurements, or according to model comparisons. It allows characterising dispersion over the continental shelf, pathways, transit times, budgets and source terms. This review exhibits the main features retained from the point of view of radiotracers, hydrodynamic models and model/measurement methods with perspectives of applications in other areas or oceanographic domains.

The purpose of the study is to control the ratio of programs of different genres when forming the broadcast grid in order to increase and maintain the rating of the channel. In the multichannel environment, television rating control consists of selecting such content, ratings of which are completely restored after advertising. A hybrid approach combining the benefits of semantic training and fuzzy relational equations in simplification of the expert recommendation systems construction is proposed. The problem of retaining the television rating can be attributed to the problems of fuzzy resources control. The increase or decrease trends of the demand and supply are described by primary fuzzy relations. The rule-based solutions of fuzzy relational equations connect significance measures of the primary fuzzy terms. Rules refinement by solving fuzzy relational equations allows avoiding labor-intensive procedures for the generation and selection of expert rules. The solution set generation corresponds to the granulation of the television time, where each solution represents the time slot and the granulated rating of the content. In automated media planning, generation of the weekly TV program in the form of the granular solutions provides the decrease of the time needed for the programming of the channel broadcast grid.

This paper proposes a cognitive radio engine platform for making exploitation of available frequency channels usable for a tactical wireless sensor network in presence of incumbent communication devices known as the primary user (PU) required to be protected from undesired harmful interference. In the field of tactical communication networks, it is desperate to find available frequencies for opportunistic and dynamic access to channels in which PU is in active. This paper introduces a cognitive engine plaform for determining available channels on the basis of case-based reasoning technique deployable as core functionality on cognitive radio engine to enable dynamic spectrum access (DSA) with high fidelity. Towards this, this paper introduces a plausible learning engine to characterize channel usage pattern to extract best channel candiates for the tactical cognitive radio node (TCRN). Performance of the proposed cognitive engine is verified by conducting simulation tests which confirm the reliability in functional aspect of the proposed cognitive engine covering the learning engine as well as the case-based reasoning engine with showing how well TCRN can avoid the collision against the PU operation considered as the etiquette secondary user (SU) should have.

Cellular-based machine-to-machine (M2M) communication is expected to facilitate services for the Internet of Things (IoT). However, because cellular networks are designed for human users, they have some limitations. Random access channel (RACH) congestion caused by massive access from M2M devices is one of the biggest factors hindering cellular-based M2M services because the RACH congestion causes random access (RA) throughput degradation and connection failures to the devices. In this paper, we show the possibility exploiting the capture effects, which have been known to have a positive impact on the wireless network system, on RA procedure for improving the RA performance of M2M devices. For this purpose, we analyze an RA procedure using a capture model. Through this analysis, we examine the effects of capture on RA performance and propose a Msg3 power-ramping (Msg3 PR) scheme to increase the capture probability (thereby increasing the RA success probability) even when severe RACH congestion problem occurs. The proposed analysis models are validated using simulations. The results show that the proposed scheme, with proper parameters, further improves the RA throughput and reduces the connection failure probability, by slightly increasing the energy consumption. Finally, we demonstrate the effects of coexistence with other RA-related scheme through simulation result.

Among others, UWB-based multi anchor localization systems have been established for industrial indoor localization systems. However, multi anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can be reduced. Our UWB Single Anchor Localization System (SALOS) successfully pursues this approach. The idea behind SALOS is to create a localization system with a sophisticated signal modeling. Therefore, neither measured reference like fingerprinting nor training is required for position estimation. Although SALOS has been implemented and tested successfully already in an outdoor scenario with multipath propagation, it has not yet been evaluated in indoor environment with challenging and hardly predictable multipath propagation. For this purpose, we have developed new algorithms for the existing hardware mainly a three-dimensional statistical multipath propagation model for arbitrary spatial geometries. The signal propagation between the anchor and predefined candidate points for the tag position is modeled in path length and complex-valued receive amplitudes. For position estimation, these modeled signals are combined to multiple sets and compared to UWB measurements via a similarity metric. In the end, a majority decision of multiple position estimates is performed. For evaluation, we implement SALOS in a modular fashion and install the system in a building. For a fixed grid of 20 positions, SALOS is evaluated in terms of position accuracy. The system results in correct position estimations for more than 73% of the measurements.

Wall Shear Stress (WSS) abnormalities in carotid artery blood flow are key hemodynamic factors leading to arterial endothelial damage, atherosclerotic plaque formation, and carotid artery stenosis. Precise simulation of carotid artery blood flow WSS in vitro play an important role in understanding the underlying hemodynamic mechanism of carotid artery stenosis. This study presents a design for a microfluidic cell culture chamber with a variable cross-section and a step structure, leveraging microfluidic technology and principles of fluid dynamics. We propose an optimization strategy for microchannel dimensions based on Computational Fluid Dynamics (CFD) simulations. This strategy aims to replicate the distinct WSS waveform features found at various locations within the carotid bifurcation as observed in vivo. Our simulations indicate that with a step height of 0.09 mm, a width of 4 mm for the initial segment, and 5 mm for the subsequent wider channel, the device can effectively model the characteristics of low oscillatory WSS seen at sites of carotid sinus stenosis. Furthermore, it accurately represents the high-magnitude pulsatile WSS waveforms in the more uniform arterial sections downstream of the carotid sinus. The study also reveals that vortex formation and variations in low oscillatory WSS within the stepped section of the microchannel correlate with the step's height and width, as well as with the dimensions of the wider channel section. An increase in step width leads to a decrease in both the vortex area and the magnitude of negative WSS oscillations. When the step height is less than 0.03 mm, vortex formation is inhibited, challenging the simulation of low oscillatory WSS patterns. The variable cross-section microfluidic channel developed in this study provides a platform for simulating carotid artery WSS waveforms and facilitates research into the interplay between low oscillatory WSS at sites of carotid sinus stenosis and arterial endothelial dysfunction.

Deep learning methods have been widely used in PolSAR image classification. To learn the polarimetric information, many deep learning methods expect to learn high-level semantic features from original PolSAR data. However, only original data cannot learn multiple scattering features and complex structures for extremely heterogeneous terrain objects. In addition, deep learning methods always cause edge confusion due to the high-level features. To overcome these shortages, we propose a double-channel CNN network combined with an edge-preserving MRF model(DCCNN-MRF) for PolSAR image classification. Firstly, to combine complex matrix data and multiple scattering features together, a double-channel convolution network(DCCNN) is developed, which consists of a Wishart-based complex matrix and multi-feature subnetworks. The Wishart-based complex matrix network can learn the statistical characteristics and channel correlation well, and the multi-feature network can learn high-level semantic features well. Then, a unified network framework is designed to fuse two kinds of features to enhance advantageous features and reduce redundant ones. Finally, an edge preserving MRF model is designed to combine with the DCCNN network. In the MRF model, a sketch map-based edge energy function is designed by defining adaptive weighted neighborhood for edge pixels. Experiments are conducted on four real PolSAR data sets with different sensors and bands. Experimental results demonstrate the effectiveness of the proposed DCCNN-MRF method.

In this paper, we investigate the use of fat tissue as a communication channel between in-body, implanted devices at R-band frequencies (1.7–2.6 GHz). The proposed fat channel is based on an anatomical model of the human body. We propose a novel probe that is optimized to efficiently radiate the R-band frequencies into the fat tissue. We use our probe to evaluate the path loss of the fat channel by studying the channel transmission coefficient over the R-band frequencies. We conduct extensive simulation studies and validate our results by experimentation on phantom and ex-vivo porcine tissue, with good agreement between simulations and experiments. We demonstrate a performance comparison between the fat channel and similar waveguide structures. Our characterization of the fat channel reveals propagation path loss of 1.4 dB and 3.8 dB per 20 mm for phantom and ex-vivo porcine tissue, respectively. These results demonstrate that fat tissue can be used as a communication channel for high data rate intra-body networks.

It was recently studied how to achieve the optimal degrees of freedom (DoF) in a multi-antenna full-duplex system with partial channel state information (CSI). In this paper, we revisit the DoF of a multiple-antenna full-duplex system using opportunistic transmission under the partial CSI, in which a full-duplex base station having M transmit antennas and M receive antennas supports a set of half-duplex mobile stations (MSs) having a single antenna each. Assuming no self-interference, we present a new hybrid opportunistic scheduling method that achieves the optimal sum DoF under an improved user scaling law. It is shown that the optimal sum DoF of 2M is asymptotically achievable provided that the number of MSs scales faster than SNR^M, where SNR denotes the signal-to-noise ratio. This result reveals that in our full-duplex system, better performance on the user scaling law can be obtained without extra CSI, compared to the prior work that showed the required user scaling condition (i.e., the minimum number of MSs for guaranteeing the optimal DoF) of SNR^2M−1.

In recent years, semantic communication has received significant attention from both academia and industry, driven by the growing demands for ultra-low latency and high-throughput capabilities in emerging intelligent services. Nonetheless, a comprehensive and effective theoretical framework for semantic communication has yet to be established. In particular, finding the fundamental limits of semantic communication, exploring the capabilities of semantic-aware networks, or utilizing theoretical guidance for deep learning in semantic communication are very important yet still unresolved issues. In general, the mathematical theory of semantic communication and the mathematical representation of semantics are referred to as semantic information theory. In this paper, we introduce the pertinent advancements in semantic information theory. Grounded in the foundational work of Claude Shannon, we present the latest developments in semantic entropy, semantic rate-distortion, and semantic channel capacity. Additionally, we analyze some open problems in semantic information measurement and semantic coding, providing a theoretical basis for the design of a semantic communication system. Furthermore, we carefully review several mathematical theories and tools and evaluate their applicability in the context of semantic communication. Finally, we shed light on the challenges encountered in both semantic communication and semantic information theory.

Keywords: Pulp cell, Periodontal cell, Micro-Arc Oxidation (MAO), Sever Plastic deformation (SPD), Equal Channel Angular Pressing (ECAP), AlamarBlue, ELISA, trypsin

Enabling D2D communication in the mm-Wave band has many obstacles which must be mitigated. The primary concern is the introduction of interference from various sources. Thus, we focused our work on the performance of decode and forward (DF) relay assisted D2D communication in the mm-Wave band for increasing the coverage probability and energy efficiency (EE). Three modes are proposed for D2D communication to prevail. Bit-wise binary XOR operation is executed at the relay node which increases the security feature. Radius of coverage expression is derived which indicates the switching of the modes. The diffused incoherent scattering power is also considered as a part of power consumption. Furthermore, a unique relay selection scheme, Dynamic relay selection (DRS) method is proposed to select the optimal relay for information exchange. Comparison of the proposed DF relay scheme with amplify and forward (DF) scheme is also shown. Finally, simulation results prove the efficacy of the proposed work.

The radio operation in wireless sensor networks (WSN) in the Internet of Things (IoT) applications are the most common source for power consumption. However, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. ContikiMAC is a low-power Radio Duty-Cycle protocol in Contiki OS used in WakeUp mode, which is a clear channel assessment (CCA) to check radio status periodically. The time spent to check the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in Radio Duty-Cycles and ContikiMAC. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Then, we propose lightweight CCA (LW-CCA) as an extension to ContikiMAC to reduce the percentage of Radio Duty-Cycles in false WakeUps and idle listenings by using dynamic received signal strength indicators (RSSI) status check time. The simulation results in the Cooja simulator show that LW-CCA reduces about 8% energy consumption in nodes while maintaining up to 99% of the packet delivery rate (PDR).

A diffusion welding of coarse-grained and ultrafine-grained (UFG) specimens of titanium near-α alloy Ti-5Al-2V used in nuclear power engineering was made by Spark Plasma Sintering. The failure of the welded specimens in the conditions of hot salt corrosion and of electrochemical corrosion were shown to have preferentially intercrystalline character. In the case of presence of macrodefects, crevice corrosion of the welded joints was observed. The resistance of the alloys against the intercrystalline corrosion was found to be determined by the concentration of vanadium at the titanium grain boundaries, by the size and volume fraction of the β-phase particles and by the presence of micro- and macropores in the welded joints. The specimens of the welded joints of the UFG alloy have higher hardness, hot salt corrosion resistance and the electrochemical corrosion.

The radio activity in Wireless Sensor Networks (WSN) and Internet of Things (IoT) applications are the most common reason for power consumption. However, recognizing and controlling the factors affecting radio activity can be valuable for managing node power. ContikiMAC is a low-power Radio Duty-Cycle protocol in Contiki OS that uses Clear Channel Assessments (CCA) to check radio status periodically. The time taken to check the radio in receive mode WakeUp, is one of the most important reasons for power consumption which in most the cases can lead to negative WakeUp in Radio Duty-Cycles and ContikiMAC especially. Here, we present a detailed analysis of idle listening time factors on the ContikiMAC. Then, we propose Light Weight CCA(LW-CCA) as an extension to ContikiMAC to reduce power consumption by reducing the radio check time in receive mode WakeUp’s, while maintaining up to 99% the Packet Delivery Rate (PDR). The simulation results show that the proposed method reduces significantly energy consumption in nodes compared to ContikiMAC and thus it helps maintain a high network performance.

Traditional high pressure mechanical compressors account for over half of the car station’s cost, have insufficient reliability and are not feasible for a large-scale fuel cell market. An alternative technology, employing a two-stage, hybrid system based on electrochemical and metal hydride compression technologies, represents an excellent alternative to conventional compressors. The high-pressure stage, operating at 100-875 bar, is based on a metal hydride thermal system. A techno-economic analysis of the metal hydride system is presented and discussed. A model of the metal hydride system was developed, integrating a lumped parameter mass and energy balance model with an economic model. A novel metal hydride heat exchanger configuration is also presented, based on mini-channel heat transfer systems, allowing for effective high-pressure compression. Several metal hydrides were analyzed and screened, demonstrating that one selected material, namely (Ti_0.97Zr_0.03)_1.1Cr_1.6Mn_0.4, is likely the best candidate material to be employed for high-pressure compressors under the specific conditions. System efficiency and costs were assessed based on the properties of currently available materials at industrial levels. Results show that the system can reach pressures on the order of 875 bar with thermal power provided at approximately 150 °C. The system cost is comparable with the current mechanical compressors and can be reduced in several ways as discussed in the paper.

Loss of photoreceptors in retinal degenerative diseases also impacts the inner retina: bipolar cell dendrites retract, neurons rewire and protein expression changes. ON-bipolar cells represent an attractive target for optogenetic vision restoration. However, above-described maladaptations may negatively impact the quality of restored vision. To investigate this question, we employed human post-mortem retinas and transgenic rd1_Opto-mGluR6 mice expressing the optogenetic construct Opto-mGluR6 in ON-bipolar cells and carrying the retinal degeneration rd1 mutation. We found significant changes in delayed rectifier potassium channel expression in ON-bipolar cells of degenerative retinas. In particular, we found an increase in Kv1.3 expression already in early stages of degeneration. Immunohistochemistry localized Kv1.3 channels specifically to OBC axons. In whole-cell patch-clamp experiments, ON-bipolar cells in the degenerated murine retina were less responsive, which could be reversed by application of the specific Kv1.3 antagonist Psora-4. Notably, Kv1.3 block significantly increased the amplitude and kinetics of Opto-mGluR6-mediated light responses in ON-bipolar cells of the blind retina and increased the signal-to-noise ratio of light-triggered responses in retinal ganglion cells. We propose that reduction of Kv1.3 activity in the degenerated retina, either by pharmacological block or by KCNA3 gene silencing, could improve the quality of restored vision.

Due to the special characteristics of the shooting distance and angle of remote sensing satellites, the pixel area ratio of ship targets is small and the feature expression is insufficient, which leads to unsatisfactory ship detection performance and even situations such as missed detection and false detection. In this study, we propose an improved-YOLOv5 algorithm. The improvement strategies mainly include: (1) Add the Convolutional Block Attention Module (CBAM) into the Backbone to enhance the extraction of target-adaptive optimal features; (2) Introduce cross-layer connection channel and lightweight GSConv structure into the Neck to achieve higher-level multi-scale feature fusion and reduce the number of model parameters; (3) The Wise-IoU loss function is used to cal-culate the localization loss in the Output, and assign reasonable gradient gains to cope with dif-ferences in image quality. In addition, during the preprocessing stage of experimental data, a me-dian and bilateral filter method is used for noise reduction to reduce interference from ripples and waves and highlight the information of ship features. The experimental results show that Im-proved-YOLOv5 has a significant improvement in recognition accuracy compared to various mainstream target detection algorithms; Compared to the original YOLOv5s, the mean Average Precision (mAP) has improved by 3.2% and the Frames Per Second (FPN) has accelerated by 8.7%.

Human Face and facial parts are the most significant parts as it reveals a person’s true identity. It plays an important role in various biometric applications like crowd analysis, human tracking, photography, cosmetic surgery, etc. There are many techniques are available to detect a facial image. Among them, skin detection is the most popular one. The aim of this paper is to detect first the person's identity from facial image and finally check any spot present the the detected person. The first step is to detect the maximum skin region based on a combination method of RGB and HSV color space model. Next it is to verify the skin areas of human through machine learning approach. The Aggregated Channel Features (ACF) detector is used to identify the different facial parts like eye pairs, nose, and mouth. Bootstrap aggregation decision tree classifier is applied to classify the person’s identity based on Histogram Oriented Gradient (HOG) features value. The experimental results show that the proposed method gives the average 97% accuracy.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (Ca_Vs). Calcium entering through Ca_Vs is key for multiple neuronal processes. In this review, we will summarize recent findings that link Ca_Vs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of Ca_Vs structure, classification, function, expression and pharmacology. Next, we will summarize tools and databases to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in Ca_V genes when available. We will review pharmacological evidence of the use of Ca_V modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of Ca_Vs.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

In this paper, we proposed a novel saddle type FinFET (S-FinFET) to effectively solve problems occurring under the capacitor node of dynamic random-access memory (DRAM) cell and showed how its structure was superior to conventional S-FinFETs in terms of short channel effect (SCE), subthreshold slope (SS), and gate-induced drain leakage (GIDL). The proposed FinFET exhibited 4 times lower Ioff than modified S-FinFET called RFinFET with more improved DIBL characteristics while minimizing Ion reduction compared to RFinFET. Our results also confirmed that the proposed device showed improved DIBL and Ioff characteristics as gate channel length decreased.