Space Resolution Research Articles

Water treatment by cavitation: Understanding it at a single bubble - bacterial cell level

Cavitation is a potentially useful phenomenon accompanied by extreme conditions, which is one of the reasons for its increased use in a variety of applications, such as surface cleaning, enhanced chemistry, and water treatment. Yet, we are still not able to answer many fundamental questions related to efficacy and effectiveness of cavitation treatment, such as: “Can single bubbles destroy contaminants?” and “What precisely is the mechanism behind bubble's cleaning power?”. For these reasons, the present paper addresses cavitation as a tool for eradication and removal of wall-bound bacteria at a fundamental level of a single microbubble and a bacterial cell. We present a method to study bubble-bacteria interaction on a nano- to microscale resolution in both space and time. The method allows for accurate and fast positioning of a single microbubble above the individual wall-bound bacterial cell with optical tweezers and triggering of a violent microscale cavitation event, which either results in mechanical removal or destruction of the bacterial cell. Results on E. coli bacteria show that only cells in the immediate vicinity of the microbubble are affected, and that a very high likelihood of cell detachment and cell death exists for cells located directly under the center of a bubble. Further details behind near-wall microbubble dynamics are revealed by numerical simulations, which demonstrate that a water jet resulting from a near-wall bubble implosion is the primary mechanism of wall-bound cell damage. The results suggest that peak hydrodynamic forces as high as 0.8 μN and 1.2 μN are required to achieve consistent E. coli bacterial cell detachment or death with high frequency mechanical perturbations on a nano- to microsecond time scale. Understanding of the cavitation phenomenon at a fundamental level of a single bubble will enable further optimization of novel water treatment and surface cleaning technologies to provide more efficient and chemical-free processes.

LSOS: An FG Position Method Based on Group Phase Ranging Ambiguity Estimation of BeiDou Pseudolite

Due to the influence of indoor space environments, the carrier phase information obtained by the BeiDou pseudo-satellite often has the issue of cycle slips, which makes the user unable to carry out high-precision positioning. Aiming at the problem of ambiguity resolution (AR) and location in large-scale occluded space (LSOS), a factor graph (FG) position method based on group phase ranging ambiguity estimation of BeiDou pseudolite is proposed. Firstly, by introducing the principle of group phase period quantization and utilizing the multi-frequency characteristic of the BeiDou pseudo-satellite, the carrier phase propagation ambiguity of the BeiDou pseudo-satellite can be estimated quickly. On this basis, by introducing the shuffled frog leading algorithm (SFLA) assisted factor graph optimization location estimation method, the BeiDou pseudo-satellite positioning process in LSOS is realized. The experimental results show that the proposed method can solve the problem of fast estimation of ranging ambiguity of BeiDou pseudolite in LSOS, and the ranging accuracy can be improved to two wavelength ranges. In the further location experiment, it is found that the algorithm can not only guarantee the real-time location output but also improve the location precision to sub-meter level under the multi-frequency combination; the optimal location test precision is 9 cm, the maximum positioning error is 50 cm. This method successfully solves the problem wherein the BeiDou pseudo-satellite cannot provide real-time, continuous, and high-precision positioning in LSOS.

Spatial resolution enhancement of the land surface thermal field imagery based on multiple regression models on multispectral data from various space systems

The methodology has been developed for enhancing the spatial resolution of the land surface thermal field satellite imagery based on the following steps: coupling images in the visible, thermal, and radar ranges into the single multispectral data product; constructing regression models of the images’ relationship; performing the linear regression of the pseudo-thermal product with enhanced spatial resolution from the visible and radar ranges data. The methodology is implemented on the Google Earth Engine open cloud platform using the Earth Engine API and the software scripts created in the JavaScript language with the processing of multispectral image collections of various space systems at specified time intervals. The possibility of practical synthesis of the pseudo-thermal image with an enhanced spatial resolution of 10 m based on the thermal image with the resolution of 100 m and the multispectral composite with the layers’ resolution of 10 m and 30 m is shown. The technology has been developed for synthesis and calibration of the land surface temperature product with enhanced spatial resolution and daily data providing rate based on the brightness temperature product in the B10 band of Landsat 8 and linear regression on the MODIS, ASTER, and Sentinel 1 products with daily to moderate data providing rates. The software in JavaScript has been developed, and technology has been implemented in the interactive web service form with open access on the Google Earth Engine Apps cloud platform. The final data product provides the satisfactory relative root mean square error of the brightness temperature recovery of not more than 6 % according to the reference cross-calibration data of the B10 Landsat 8 band in the moderate thermal field (up to 100° C). The relative root mean square errors of the synthesized data according to the reference data on high-temperature sites (fire, hot lava) up to 28 % are due to the fact that the synthesized product contains information from high-temperature spectral bands (B07-B09 from ASTER), while the reference product (B10 from Landsat 8) does not contain such information. Technology implementation examples show that cross-calibration of the synthesized product can be performed during the year from March to October according to reference thermal images of natural or artificial objects. Objects selected for calibration must have stable thermal characteristics at the time of the satellite flight during the data acquisition period. Keywords: land surface temperature, brightness temperature, space resolution of imagery, multiply linear regression, heterogeneous multispectral data coupling, data providing rate, product cross-calibration, Google Earth Engine.

A time-accurate inflow coupling for zonal LES

Generating turbulent inflow data is a challenging task in zonal large eddy simulation (zLES) and often relies on predefined DNS data to generate synthetic turbulence with the correct statistics. The more accurate, but more involved alternative is to use instantaneous data from a precursor simulation. Using instantaneous data as an inflow condition allows to conduct high fidelity simulations of subdomains of, e.g. an aircraft including all non-stationary or rare events. In this paper, we introduce a toolchain that is capable of interchanging highly resolved spatial and temporal data between flow solvers with different discretization schemes. To accomplish this, we use interpolation algorithms suitable for scattered data in order to interpolate spatially. In time, we use one-dimensional interpolation schemes for each degree of freedom. The results show that we can get stable simulations that map all flow features from the source data into a new target domain. Thus, the coupling is capable of mapping arbitrary data distributions and formats into a new domain while also recovering and conserving turbulent structures and scales. The necessary time and space resolution requirements can be defined knowing the resolution requirements of the used numerical scheme in the target domain.

Onset of Visible Capillary Waves from High-Frequency Acoustic Excitation.

Remarkably, the interface of a fluid droplet will produce visible capillary waves when exposed to acoustic waves. For example, a small (∼1 μL) sessile droplet will oscillate at a low ∼102 Hz frequency when weakly driven by acoustic waves at ∼106 Hz frequency and beyond. We measured such a droplet's interfacial response to 6.6 MHz ultrasound to gain insight into the energy transfer mechanism that spans these vastly different time scales, using high-speed microscopic digital transmission holography, a unique method to capture three-dimensional surface dynamics at nanometer space and microsecond time resolutions. We show that low-frequency capillary waves are driven into existence via a feedback mechanism between the acoustic radiation pressure and the evolving shape of the fluid interface. The acoustic pressure is distributed in the standing wave cavity of the droplet, and as the shape of the fluid interface changes in response to the distributed pressure present on the interface, the standing wave field also changes shape, feeding back to produce changes in the acoustic radiation pressure distribution in the cavity. A physical model explicitly based upon this proposed mechanism is provided, and simulations using it were verified against direct observations of both the microscale droplet interface dynamics from holography and internal pressure distributions using microparticle image velocimetry. The pressure-interface feedback model accurately predicts the vibration amplitude threshold at which capillary waves appear, the subsequent amplitude and frequency of the capillary waves, and the distribution of the standing wave pressure field within the sessile droplet responsible for the capillary waves.

A Robust eLORETA Technique for Localization of Brain Sources in the Presence of Forward Model Uncertainties.

In this paper, we present a robust version of the well-known exact low-resolution electromagnetic tomography (eLORETA) technique, named ReLORETA, to localize brain sources in the presence of different forward model uncertainties. We first assume that the true lead field matrix is a transformation of the existing lead field matrix distorted by uncertainties and propose an iterative approach to estimate this transformation accurately. Major sources of the forward model uncertainties, including differences in geometry, conductivity, and source space resolution between the real and simulated head models, and misaligned electrode positions, are then simulated to test the proposed method. ReLORETA and eLORETA are applied to simulated focal sources in different regions of the brain and the presence of various noise levels as well as real data from a patient with focal epilepsy. The results show that ReLORETA is considerably more robust and accurate than eLORETA in all cases. Having successfully dealt with the forward model uncertainties, ReLORETA proved to be a promising method for real-world clinical applications. eLORETA is one of the localization techniques that could be used to study brain activity for medical applications such as determining the epileptogenic zone in patients with medically refractory epilepsy. However, the major limitation of eLORETA is sensitivity to the uncertainties in the forward model. Since this problem can substantially undermine its performance in real-world applications where the exact lead field matrix is unknown, developing a more robust method capable of dealing with these uncertainties is of significant interest.

Quantum spin Hall insulator on the honeycomb lattice induced by ferromagnetic exchange interaction

We study the many-body instabilities of correlated electrons on the half-filled honeycomb lattice with enhanced exchange coupling. The system is described by an extended Hubbard model including the next-nearest-neighbor Coulomb repulsion (V2) and the nearest-neighbor exchange interaction (J). We use the truncated unity functional renormalization group approach to determine a schematic ground-state phase diagram with higher resolution in the parameter space of V2 and J. In the absence of the on-site repulsion and presence of sizable next-nearest-neighbor repulsion and enhanced nearest-neighbor exchange interaction, we encounter the quantum spin Hall phase, the spin-Kekulé phase, and the three-sublattice and the incommensurate charge-density-wave phases. We propose a scheme for combining consistently the truncated unity functional renormalization group and the mean-field approximation, which is distinct from the conventional one that directly uses the renormalization-group results as an input for the mean-field calculation. This scheme is used to study in detail the quantum spin Hall phase, presenting some characteristics like the bulk gap, the Chern number and the helical edge states.

Measurement of Gas-Phase Velocities in Two-Phase Flow Using Distributed Acoustic Sensing

From wells to refining plants and distribution networks, operations in the oil and gas industry involve the transport of multiphase mixtures through long pipelines. One of the most representative patterns is the so-called slug flow, which is characterized by the intermittent passage of gaseous and liquid structures. The monitoring of slug flows allows for proper control and safety in many operations in the oil and gas industry. In recent years, distributed acoustic sensing (DAS) has emerged as a promising technology for industrial use and is applied here for flow monitoring. Namely, this article introduces the use of DAS for the measurement of slug flow. A number of flow configurations under controlled conditions are investigated. Measurements were carried out in a 9-m horizontal pipeline Section in a flow-loop laboratory. Fiber optics were helically wrapped along the outer surface of the pipeline to promote higher sensitivity at a higher spatial resolution space. The velocity of the gas phase given by the elongated bubbles velocity is estimated from DAS data through radial integration in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${f}$ </tex-math></inline-formula> space and distributed cross correlation methods. Using measurements from a commercial conductance-based sensor as a reference, the results showed the root-mean-square deviation in % (RMSD%) of 8.34% and 12.18%. The cross correlation method has the clear advantage of being able to yield (spatial) distributed data.

Machine learning for prediction of daily sea surface dimethylsulfide concentration and emission flux over the North Atlantic Ocean (1998–2021)

As the most ubiquitous natural source of sulfur in the atmosphere, dimethylsulfide (DMS) promotes aerosol formation in marine environments, impacting cloud radiative forcing and precipitation, eventually influencing regional and global climate. In this study, we propose a machine learning predictive algorithm based on Gaussian process regression (GPR) to model the distribution of daily DMS concentrations in the North Atlantic waters over 24 years (1998–2021) at 0.25° × 0.25° spatial resolution. The model was built using DMS observations from cruises, combined with satellite-derived oceanographic data and Copernicus-modelled data. Further comparison was made with the previously employed machine learning methods (i.e., artificial neural network and random forest regression) and the existing empirical DMS algorithms. The proposed GPR outperforms the other methods for predicting DMS, displaying the highest coefficient of determination (R2) value of 0.71 and the least root mean square error (RMSE) of 0.21. Notably, DMS regional patterns are associated with the spatial distribution of phytoplankton biomass and the thickness of the ocean mixed layer, displaying high DMS concentrations above 50°N from June to August. The amplitude, onset, and duration of the DMS annual cycle vary significantly across different regions, as revealed by the k-means++ clustering. Based on the GPR model output, the sea-to-air flux in the North Atlantic from March to September is estimated to be 3.04 Tg S, roughly 44 % lower than the estimates based on extrapolations of in-situ data. The present study demonstrates the effectiveness of a novel method for estimating seawater DMS surface concentration at unprecedented space and time resolutions. As a result, we are able to capture high-frequency spatial and temporal patterns in DMS variability. Better predictions of DMS concentration and derived sea-to-air flux will improve the modeling of biogenic sulfur aerosol concentrations in the atmosphere and reduce aerosol-cloud interaction uncertainties in climate models.

Diffusion of a disordered protein on its folded ligand.

Intrinsically disordered proteins often form dynamic complexes with their ligands. Yet, speed and amplitude of these motions are hidden in classical binding kinetics. Here, we directly measure the dynamics in an exceptionally mobile high-affinity complex. We show that the disordered tail of the cell-adhesion protein E-cadherin dynamically samples a large surface area of the proto-oncogene β-catenin. Single-molecule experiments and molecular simulations resolve these motions with high resolution in space and time. Contacts break and form within hundreds of microseconds without dissociation of the complex. The energy landscape of this complex is rugged with many small barriers (3 - 4 kBT) and reconciles specificity, high affinity, and extreme disorder. A few persistent contacts provide specificity whereas unspecific interactions boost affinity.

The effect of water level rise on coastal wave Overwash and Inundation of dunes in laboratory

Beach responses to sea level rise are investigated experimentally in laboratory wave flume by detecting the beach profile continuously using video cameras in high space and time resolution. Experiments are conducted to discuss the profile response in three scenarios of water level rise: a step-change in water level, continuous water level rise as well as extremely high water levels to find out the intensification and dissipation of swash motion waves in overwash and inundation hydrodynamic and the retreat of the shoreline due to water level rise. The sediment transport rates are estimated from the detailed monitoring of the beach profiles, from which the responses of the shoreline to the water level rise are examined.The morphological characteristics of the dunes caused by sea-level rise are discussed and it is noted that sea-level rise leads to an increase of more than 40% in sediment loss from sand dunes, while extreme solitary wave conditions are less affected by water level changes. The characteristics of shoreline retreat for different sea levels and wave conditions are analyzed from the experiment data. The developments of shoreline and beach response prediction model using the laboratory experiment data to the sea level rise are discussed for better estimation of the shoreline change to the sea level rise. Meanwhile, the trend of wave energy is consistent with the frequency of profile change as the water level continues to rise. When the water level is high enough close to the dune crest, partially broken waves in nearshore areas transmitted landward with large wave energy quickly destroy the dunes, which is a great threat to the beach ecosystem. There is an inhibitory effect on the morphological changes of the dunes as the water level is high in the back of the dunes.

Cambios y continuidades en las relaciones laborales en tiempos de retroceso Los casos de Brasil y Colombia

This article analyzes the changes in the labor relations systems in Colombia and Brazil, which, due to their labor structures, inheritance of slave systems and deep regional differences, allow us to analyze the capital-labor contradictions in the context of center and center-left governments in The 21st century. In the case of Brazil, after more than a decade of improvements, the turn to the right has generated serious setbacks in individual and collective labor rights. In the case of Colombia, although with greater continuity in neoliberal policies, the shift to the center gave a democratic space for conflict resolution, which closed with the election of a government of the extreme right. In a context of worsening labor conflicts, the reinvention of unions is key to ensure that there are no more losses in terms of labor rights and to press for a new cycle of changes in the face of the possibility of a new political turn to the left in The horizon.

Automatic intraluminal scanning with a steerable endoscopic optical coherence tomography catheter for gastroenterology applications

SignificanceEndoscopic optical coherence tomography (OCT) enables real-time optical biopsy of human organs. Endoscopic probes require miniaturization of optics, which in turn limits field of view. When larger imaging areas are needed such as in the gastrointestinal tract, the operator must manually scan the probe over the tissue to extend the field of view, often resulting in an imperfect scanning pattern and increased risk of missing lesions. Automatic scanning has the potential to extend the field of view of OCT, allowing the user to focus on image interpretation during real-time observations.AimThis work proposes an automatic scanning using a steerable OCT catheter integrated with a robotized interventional flexible endoscope. The aim is to extend the field of view of a low-profile OCT probe while improving scanning accuracy and maintaining a stable endoscope’s position during minimally invasive treatment of colorectal lesions.ApproachA geometrical model of the steerable OCT catheter was developed for estimating the volume of the accessible workspace. Experimental validation was done using electromagnetic tracking of the catheter’s positions. An exemplary scanning path was then selected within the available workspace to evaluate motion performance with the robotized steerable OCT catheter. Automatic scanning is compared to a teleoperated one and a manual scanning with a nonrobotized flexible endoscope. Spectral arc length, scanning area, spacing between scan trajectories, and time are metrics used to quantify performance.ResultsThe available scanning workspace was experimentally estimated to be 255 cm3. The automatic scanning mode provided the highest accuracy and smoothness of motion with spectral arc length of −3.18, covered area of 10.11 cm2, 1.54 mm spacing between 15 sweep trajectories, maximum translation of 27.99 mm, and time to finish of 3.11s.ConclusionsAutomatic modality improved the accuracy of scanning within a large workspace. The robotic capability provided better control to the user to define spacing resolution of scanning patterns.

Arbitration, International Mediation, and the Widening of the Alternative Dispute Resolution Space: Bloated Expectations or a Matter of Time

It is undisputable that dispute does arise from almost every transaction in people’s lives. Consequently, court procedures –litigation- have been developed over the years to ensure there is fairness and justice in resolving disputes arising from such transactions. Well recognized and praised at first, however, litigation got to be extremely difficult as it could not protect parties’ privacy and ensure confidentiality. Moreover, it became incredibly expensive, consumes time and could not provide for a win-win resolution of disputes among other challenges. Thus, ADR became the hope of a common man and last resort for dispute settlement. Although, it remains unclear if Alternative Dispute Resolution (ADR) is as age long as litigation. Nevertheless, ADR could be said to have been resorted to in order to mitigate, water-down and limit the hardship caused by litigation. Today, the globe is at the sojourn oscillating between the relevance of ADR over litigation and vice versa. Hence, a prerequisite to understand whether expanding the space of Alternative Dispute Resolution are bloated expectations or a matter of time. In this paper, arbitration and international mediation will be discussed starting from their historical background and importance. Also, this paper will further examine whether widening the space of Arbitration, International Mediation and ADR in general are bloated expectations or a matter of time.

Efficient time splitting schemes for the monodomain equation in cardiac electrophysiology.

Approximating the fast dynamics of depolarization waves in the human heart described by the monodomain model is numerically challenging. Splitting methods for the PDE-ODE coupling enable the computation with very fine space and time discretizations. Here, we compare different splitting approaches regarding convergence, accuracy, and efficiency. Simulations were performed for a benchmark problem with the Beeler-Reuter cell model on a truncated ellipsoid approximating the left ventricle including a localized stimulation. For this configuration, we provide a reference solution for the transmembrane potential. We found a semi-implicit approach with state variable interpolation to be the most efficient scheme. The results are transferred to a more physiological setup using a bi-ventricular domain with a complex external stimulation pattern to evaluate the accuracy of the activation time for different resolutions in space and time.

The Pierre Auger Observatory: Studying atmospheric electricity with cosmicray detectors

The Pierre Auger Observatory, designed to detect extensive air showers (EAS) generated by ultrahigh-energy cosmic rays, proved to be a unique instrument to study phenomena associated with atmospheric electricity: Terrestrial Gamma-ray Flashes (TGFs) and ELVES. TGFs are the most explosive events emitted by thunderstorms and have usually been observed by spacecraft, but the Auger surface detector has collected events with a morphology very different from that of EAS, that are likely downward TGFs. Ground observations are a crucial addition to detection in space, as detectors are closer to TGF sources, and a single event can be observed with several complementary instruments. In this talk, I will discuss the comparison of the already collected data with simulations as well as the ongoing work to adapt the data-taking system to detect TGFs. I will also discuss the status of the study of ELVES, upper atmospheric optical phenomena associated with thunderstorms, which we have detected since 2013 with the fluorescence detectors. We have recorded with unprecedented time and space resolution both single and double ELVES, the latter being classified using the radial variation of the time gap and the photon flux ratio between flashes. The detection and classification algorithms were improved by detecting ELVES from closer lightning thanks to the three High Elevation Auger Telescopes, which observe the night sky with an enhanced time resolution at elevation angles between 30 and 60 degrees.

Conflict resolution in the educational space of an educational organization: the value aspect

Conflict resolution in the educational space of an educational organization: the value aspect

En-Face Imaging of T Cell-Dendritic Cell Immunological Synapses.

Imaging of the immunological synapse (IS) between dendritic cells (DCs) and T cells in suspension is hampered by suboptimal alignment of cell-cell contacts along the vertical imaging plane. This requires optical sectioning that often results in unsatisfactory resolution in time and space. Here, we present a workflow where DCs and T cells are confined between a layer of glass and polydimethylsiloxane (PDMS) that orients the cells along one, horizontal imaging plane, allowing for fast en-face-imaging of the DC-T cell IS.

MSRF-Net: Multiscale Receptive Field Network for Building Detection From Remote Sensing Images

Extracting buildings from remote sensing images plays an important role in urban development planning, disaster assessment and mapping. Convolutional neural network (CNN) has been widely applied to building extraction because of its powerful deep semantic feature extraction ability. However, existing CNN-based building extraction methods are difficult to accurately extract multiscale buildings with accurate edges because of the limitation of feature receptive fields and the loss of spatial detail information. For the above problems, this paper proposes a multiscale receptive field network (MSRF-Net) to accurately extract multiscale buildings from remote sensing images. MSRF-Net includes multiscale receptive field feature encoder (MRFF-Encoder) and multipath decoder. In the MRFF-Encoder, a multiscale attentional down (MSAD) module and asymmetric residual inception (ARI) module are proposed to capture multiscale receptive field features. In the multipath decoder, convolutions with different kernel size and dilation are used in three parallel paths to learn localization-preserved multiscale features with multiscale receptive field. What’s more, the features of different branches and MRFF-Encoder are fused by the proposed feature combination module, which contribute to capture context information of multiscale receptive field while recovering the resolution of feature space. The experimental results show that compared with the latest MAP-Net, MSRF-Net has achieved F1 score growth of 1.14%, 0.42%, 1.11% and IoU score growth of 1.68%, 0.76% and 1.64% respectively on Massachusetts data set, WHU data set and the Typical Cities Building data set.

Going Green by Adopting and Adapting Arbitration for Environment Related Disputes

Despite the fact that the law has evolved in addressing the array of concerns existing by often immediate and irreversible damage to the soul environment, the working of the law has been plagued by an unsuccessful dispute settlement mechanism with little detailing on its administration. International environmental treaties are gradually making more space for alternative dispute resolution (ADR) methods for dispute settlement. The Permanent Court of Arbitration Environment Arbitration Rules, 2001 are a set of rules with a little novel features addressing concerns which are exclusive for environmental disputes – the role of the nonstate actors and multi-party disputes. The rules are formed in a manner that would make possible for any group of parties to dispute state, NGOs, multinational corporations and even individuals. The policy is also formulated to tackle multi-party disputes. Another important characteristic of these rules are that they also addresses the cost aspect of international dispute settlement process - member states have access to the environment assistance fund. Permanent Court of Arbitration (PCA) and the environment rules fill the place of forum for environmental disputes with expertise. The paper makes no endeavor to state that there is nonexistence of normative structure with reference to dispute resolution in trans-boundary environmental disputes. Rather it aims to demonstrate the normative insufficiency in the methodology adopted to address the content of the dispute resolution mechanisms and present ADR methods as a successful methodology for resolution of environmental disputes. It starts with a concise discussion on the characterization of an environmental dispute and the difficulty in the present legal regime. This is followed by a short overview of the dispute settlement structure in international law. It then discusses the mechanism of conciliation, mandatory and optional, exemplified in the course of a few international environmental instruments. Further there is a dialogue on the Permanent Court of Arbitration Optional Rules for Conciliation in Environmental Disputes, 2001 (Hereinafter rules, 2001). The next part discusses the instrument of arbitration, mandatory and optional, as exemplified through state practice in a few arbitrations like the Mox Plant Arbitration, and the International Tribunal for the Law of the Sea (ITLOS) arbitrations. Additionally there is a conversation on the rules, 2001 and how they could be of importance by customizing them for disputes like the transboundary freshwater disputes. The paper concludes with an assessment of the rules.