Distinct Phases Research Articles

Medics as influencers: a historical analysis of British Army military medical exercises in Kenya over two decades

IntroductionAnnual British Army medical training exercises have run in Kenya since the early 1990s, initially with a dual purpose—to deliver the Kenyan Extended Programme of Immunisation (in remote locations) and...

Bibliometric Analysis of Forensic Human Remains Identification Literature from 1991 to 2022.

To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification research. The data retrieved and extracted from the Web of Science Core Collection (WoSCC), the core database of the Web of Science information service platform (hereinafter referred to as "WoS"), was used to analyze the trends and topic changes in research on forensic identification of human remains from 1991 to 2022. Network visualisation of publication trends, countries (regions), institutions, authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10. A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained. The journal with the largest number of publications was Forensic Science International (164 articles). The country (region) with the largest number of published papers was China (90 articles). Katholieke Univ Leuven (Netherlands, 21 articles) was the institution with the largest number of publications. Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation, and the most commonly studied remains were teeth. The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing. However, the scope of both international and domestic collaborations remains limited. Traditionally, human remains identification has primarily relied on key areas such as the pelvis, skull, and teeth. Looking ahead, future research will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.

Families adapting to COVID-19 in urban Bangladesh: "It felt like the sky fell apart and we were in shock".

The COVID-19 epidemic has especially impacted the urban population in Bangladesh. Studies on COVID-19 have primarily focused on the patient's perspective. It is important to understand the experience of family members who adopt caregiving roles, as the experience of COVID-19 also impacts, and is impacted by, household members. This study aimed to explore the challenges, preventative practices, health-seeking behaviour, and perspectives of navigating the health care system from the perspective of family members of persons who had recovered from COVID-19 during its initial outbreak in Bangladesh. Participants of this qualitative study were family members (n = 7) of persons who had recovered from COVID-19 (either suspected or confirmed). Semi-structured in-depth interviews were conducted over telephone. Thematic analysis was used to analyse the data. Analysis revealed three key themes: changes in everyday practices and choice of health care, challenges and constraints, and unexpected positive outcomes. All the themes had temporal dimension to them with four distinct phases: early stage of COVID-19, strict lockdown phase, COVID-19 diagnosis and illness period and post COVID-19 recovery. The importance of maintaining social contact for psychological wellbeing during critical times was evident in the study. Online communication and social media enabled participants to remain 'socially connected' which further supported their mental health. Increased attention to hygiene practices both before, during and subsequent to COVID-19 infections within families was reported. Physical distancing in case of a suspected or confirmed COVID-19 case was found logistically and socially impractical in a densely populated city.

Microstructure and thermoelectric properties of as-cast Ag2Te/AgBiTe2 and Ag2Te/Bi2Te3 two-phase alloys

The microstructure and thermoelectric properties of Ag2Te/AgBiTe2/Bi2Te3 eutectic alloys in the Ag-Bi-Te system were investigated in the present study. A self-consistent, thermodynamically optimized database of the Ag-Bi-Te system was developed to explain the microstructural features in the investigated alloys. Samples namely B0 (Bi2Te3 – 0 at.% Ag), B1 (Bi2Te3 – 5 at.% Ag), B2 (Bi2Te3 – 18.35 at.% Ag), B3 (Bi2Te3 – 28.35 at.% Ag), and B4 (Bi2Te3 – 38.35 at.% Ag) were synthesized by flame melting. Scanning electron micrographs of alloys reveal lamellar eutectic structures in which alloys B1 and B2 exhibit two distinct phases, consisting of β-Bi2Te3 and AgBiTe2, whereas alloys B3 and B4 display phase compositions corresponding to Ag2Te and AgBiTe2 phases. The X-ray diffraction reveals that the solidified alloys have hexagonal (AgBiTe2, Bi2Te3) and cubic β-Ag2Te crystal structures. The Scheil cooling calculations of these alloys using the developed thermodynamic database explain the microstructural features of the alloys. Furthermore, the mechanical characteristics of eutectic alloys B1 and B3 demonstrated improved hardness values, measuring 1.1 GPa and 1.2 GPa, respectively. Moreover, the transport characteristics show favourable attributes for thermoelectrics in high-temperature applications. It is important to highlight that all these alloys showcase transport properties that are highly advantageous for thermoelectrics. Notably, alloy B2 distinguishes itself with a remarkable ZT value of 0.42 at 540 K.

Prediction of water anomalous properties by introducing the two-state theory in SAFT.

Water is one of the most abundant substances on earth, but it is still not entirely understood. It shows unusual behavior, and its properties present characteristic extrema unlike any other fluid. This unusual behavior has been linked to the two-state theory of water, which proposes that water forms different clusters, one with a high density and one with a low density, which may even form two distinct phases at low temperatures. Models incorporating the two-state theory manage to capture the unusual extrema of water, unlike traditional equations of state, which fail. In this work, we have derived the framework to incorporate the two-state theory of water into the Statistical-Associating-Fluid-Theory (SAFT). More specifically, we have assumed that water is an ideal solution of high density water molecules and low density water molecules that are in chemical equilibrium. Using this assumption, we have generalized the association term SAFT to allow for the simultaneous existence of the two water types, which have the same physical parameters but different association properties. We have incorporated the newly derived association term in the context of the Perturbed Chain-SAFT (PC-SAFT). The new model is referred to as PC-SAFT-Two-State (PC-SAFT-TS). Using PC-SAFT-TS, we have succeeded in predicting the characteristic extrema of water, such as its density and speed of sound maximum, etc., without loss of accuracy compared to the original PC-SAFT. This new framework is readily extended to mixtures, and PC-SAFT-TS manages to capture the solubility minimum of hydrocarbons in water in a straightforward manner.

Post-Pandemic Legislative Transition Analysis in China’s Metropolises: Street Vending between Prohibition and Legalization

The governance of the street vendor economy has always been an important part of the social grass-roots governance. To stimulate the economy and ensure employment in the post-COVID-19 pandemic era, the Chinese government's policy towards the street vendor economy has transitioned from prohibition to legalization. This paper traces the three distinct historical phases of China's economic policy concerning street stalls in the 21st century, shedding light on the resistance encountered during the process of legalization. Subsequently, it uses policy comparative analysis to explain the legislative transition and the underlying reasons for these changes in three major Chinese metropolises: Shenzhen, Shanghai, and Beijing. The results show that the city's legislative turning and diversion strategies cannot achieve the expected effect. So the paper proffers suggestions for future policy-making. The suggestions include Person-centered place designation, flexible time, and rights protection policy.

S3L: Spectrum Transformer for Self-Supervised Learning in Hyperspectral Image Classification

In the realm of Earth observation and remote sensing data analysis, the advancement of hyperspectral imaging (HSI) classification technology is of paramount importance. Nevertheless, the intricate nature of hyperspectral data, coupled with the scarcity of labeled data, presents significant challenges in this domain. To mitigate these issues, we introduce a self-supervised learning algorithm predicated on a spectral transformer for HSI classification under conditions of limited labeled data, with the objective of enhancing the efficacy of HSI classification. The S3L algorithm operates in two distinct phases: pretraining and fine-tuning. During the pretraining phase, the algorithm learns the spatial representation of HSI from unlabeled data, utilizing a masking mechanism and a spectral transformer, thereby augmenting the sequence dependence of spectral features. Subsequently, in the fine-tuning phase, labeled data is employed to refine the pretrained weights, thereby improving the precision of HSI classification. Within the comprehensive encoder–decoder framework, we propose a novel spectral transformer module specifically engineered to synergize spatial feature extraction with spectral domain analysis. This innovative module adeptly navigates the complex interplay among various spectral bands, capturing both global and sequential spectral dependencies. Uniquely, it incorporates a gated recurrent unit (GRU) layer within the encoder to enhance its ability to process spectral sequences. Our experimental evaluations across several public datasets reveal that our proposed method, distinguished by its spectral transformer, achieves superior classification performance, particularly in scenarios with limited labeled samples, outperforming existing state-of-the-art approaches.

Analytical utility of periodizing capitalist history: Neoliberalism, social welfare spending, and income inequality in the United States

This article critiques policies aimed at income redistribution within the framework of Marx’s critique of political economy. The ‘Neoliberal’ characterization of capitalist history, the tendency to divide capitalism into distinct sub-periods or phases, continues to play a significant role for describing changes to social policy in the United States. Prominent academics and public intellectuals continue to hold spirited debates over whether or not welfare spending in the United States has become less generous over the years, owing to increasing ‘neoliberalization’ of the American economy. This mixed-methods research paper analyzes trends in social welfare spending and income inequality for the United States. To supplement the analysis, a novel dataset on Distributional National Accounts from the Bureau of Economic Analysis is also analyzed. Evidence suggests previous concerns in the literature are unfounded and are not borne out by empirical evidence.

Tectono-Metamorphic Evolution of the Cretaceous Kluane Schist, Southwest Yukon

Abstract A wealth of information regarding the Mesozoic evolution of the Northern Canadian and Alaskan Cordillera is held within a series of variably metamorphosed and deformed rocks that formed in Jura-Cretaceous basins. Located at the interface between the pericratonic Intermontane and exotic Insular terranes, these basinal rocks are key to understanding the timing and tectonic style of Insular terrane accretion, a topic of longstanding debate. This study unravels the structural and metamorphic evolution of one of these basins, the Kluane Basin, within southwest Yukon Territory. The Kluane Schist is the primary assemblage of the Kluane Basin. It consists of metamorphosed and deformed low-Al pelites that were intruded by granodioritic plutons of the Paleocene Ruby Range batholith. Previous workers have suggested the variable metamorphic character of the Kluane Schist represents an extensive and static thermal aureole related to Ruby Range batholith emplacement. Our work, however, indicates that the Kluane Schist experienced Buchan-style metamorphism coeval with protracted deformation and can be divided into seven distinct petrologic zones, which, based on their unique combination of mineral assemblage and structure, are incompatible with static thermal metamorphism. Instead, we propose the Kluane Schist experienced two distinct metamorphic phases: (1) an early greenschist-facies phase that resulted in the development of a bedding-parallel chlorite-muscovite-titanite fabric, preserved by its lowest-grade units, and (2) a later amphibolite-facies phase that manifests as the progressive transposition of the earlier chlorite-muscovite-titanite fabric into a penetrative biotite-rich schistosity that transitions upgrade into a segregated gneissic fabric comprised of biotite-cordierite and plagioclase-quartz (± sillimanite-K-feldspar-melt). By integrating the results of detailed petrography and petrological modeling, we demonstrate that the second main metamorphic phase experienced by the Kluane Schist preserves a record of pressures and temperatures that align with other Buchan-style terranes worldwide. Our data defines a field gradient across the Kluane Schist ranging from 3.0–3.5 kbar at 375–400 °C to 4–4.5 kbar at 700–750 °C. This record of a coupled Buchan-style metamorphic-deformational evolution and tops-to-the SW non-coaxial shear structures is consistent with the override of the thermally mature Yukon-Tanana terrane as the principal driver of Kluane Schist metamorphism, with some limited heat likely contributed by the late-syn- to post-tectonic intrusion of the Ruby Range batholith.

Seismic scattering regimes from multiscale entropy and frequency correlations

SUMMARY Seismic-wave scattering is observed, to variable degrees, on Earth, its moon and Mars. Current scattering models and data processing typically rely on two end-member phenomena: weak, single- or multiple-scattering events (ballistic) on the one hand, or intense scattering such that the wavefield retains no path information or bearing on its origin (diffuse).This study explores the existence of scattering behaviour intermediate between these end-members, as well as the properties of heterogeneous media that facilitate a transition between them. We apply multiscale entropy and frequency-correlation analysis to seismic coda, and observe a distinct transitional behaviour is present within a part of the investigated parameter space. Analysis of terrestrial, lunar and Martian seismograms further demonstrate the applicability of these new methods across a wide range of scattering behaviours, while also highlighting their shortcomings. Results from the planetary data indicate partially non-diffuse behaviour and low complexity within specific bandwidths of lunar wavefields, potentially contradicting the current paradigm that lunar wavefields are diffuse, and require continued study. Furthermore, Martian seismograms are shown to possess greater statistical entropy than lunar seismograms and diffuse energy properties, yet still display distinct phase arrivals, suggesting substantial scattering and transitional scattering behaviour on Mars. The robust, comparative nature of multiscale entropy and frequency-correlation analysis, applied to idealised simulation as well as three separate planetary bodies, provides a promising framework for future exploration of scattered wavefields across ballistic, transitional and diffuse regimes, that complements existing methods.

Investigation of Multi-Stage Visual Servoing in the context of autonomous assembly

This paper introduces a novel strategy, Multi-Stage Based Visual Servoing (MSBVS), to tackle the significant challenge of planning complex trajectories in robotic systems without hand–eye calibration, particularly in some assembly tasks. The MSBVS strategy decomposes a complete visual servoing process into three distinct phases, each characterized by unique functionalities. By assigning specific image features and control objectives to each phase, the strategy indirectly facilitates the planning and tracking complex trajectories. Furthermore, a novel image feature, the vanishing angle, is introduced, enhancing the precision in representing an object’s spatial position. Subsequently, a robotic vision system is established, and real-time simulations and experiments are performed to verify the efficacy of the MSBVS strategy. The results show that MSBVS efficiently plans and executes complex trajectories in robotic assembly tasks.

Exploring the dynamics of bigdata adoption in the Indian food industry with fuzzy analytical hierarchical process

PurposeThe main aim of this study is to identify and prioritize the factors that influence the adoption of big data analytics (BDA) within the supply chain (SC) of the food industry in India.Design/methodology/approachThe study is carried out in two distinct phases. In the first phase, barriers hindering BDA adoption in the Indian food industry are identified. Subsequently, the second phase rates/prioritizes these barriers using multicriteria methodologies such as the “analytical hierarchical process” (AHP) and the “fuzzy analytical hierarchical process” (FAHP). Fifteen barriers have been identified, collectively influencing the BDA adoption in the SC of the Indian food industry.FindingsThe findings suggest that the lack of data security, availability of skilled IT professionals, and uncertainty about return on investments (ROI) are the top three apprehensions of the consultants and managers regarding the BDA adoption in the Indian food industry SC.Research limitations/implicationsThis research has identified several reasons for the adoption of bigdata analytics in the supply chain management of foods in India. This study has also highlighted that big data analytics applications need specific skillsets, and there is a shortage of critical skills in this industry. Therefore, the technical skills of the employees need to be enhanced by their organizations. Also, utilizing similar services offered by other external agencies could help organizations potentially save time and resources for their in-house teams with a faster turnaround.Originality/valueThe present study will provide vital information to companies regarding roadblocks in BDA adoption in the Indian food industry SC and motivate academicians to explore this area further.

Optimization of elution conditions and comparison of emerging biocompatible columns on the resolving power and detection sensitivity of oligonucleotides by ion-pairing reversed-phase liquid chromatography mass spectrometry

A generic performance comparison strategy has been developed to evaluate the impact of mobile-phase additives (ion-pairing agent / counter ion systems), distinct stationary phases on resulting resolving power, and MS detectability of oligonucleotides and their critical impurities in gradient IP-RPLC. Stationary-phase considerations included particle type (core-shell vs. fully porous particles), particle diameter, and pore size. Separations were carried out at 60°C to optimize mass transfer (C-term). The incorporation of an active column preheater mitigated thermal mismatches, leading to narrower peaks and overcoming peak splitting. Acetonitrile as organic modifier outweighed methanol in terms of peak-capacity generation and yielded a 30% lower back pressure. Performance screening experiments were conducted varying ion-pairing agents and counter ions, while adjusting gradient span achieved an equivalent effective retention window. Hexafluoromethylisopropanol yielded superior chromatographic resolution, whereas hexafluoroisopropanol yielded significantly higher MS detection sensitivity. The 1.7 µm core-shell particle columns with 100 Å pores provided maximum resolving power for small (15–35 mers) oligonucleotides. Sub-min analysis for 15–35 polyT ladders was achieved operating a 50 mm long column at the kinetic performance limits. High-resolution separations between a 21-mer modified RNA sequence oligonucleotides and its related (shortmer and phosphodiester) impurities and complementary strand were obtained using a coupled column set-up with a total length of 450 mm.

Abstract P07: Identification of the unique preleukemic bone marrow niche in acute myeloid leukemia

Abstract P07: Identification of the unique preleukemic bone marrow niche in acute myeloid leukemia

Biofilm viability and microbial community of non-inoculated moving bed biofilm reactor in Nile tilapia Oreochromis niloticus cultivation

The aim of this study was to evaluate two moving bed biofilm reactors (MBBR) without nitrifying bacteria inoculation. Biofilms and viable bacterial colonies were evaluated after 124 days. MBBR bioreactors received water from Oreochromis niloticus fish farming and water quality parameters were monitored daily. Four distinct phases with different fish stocking density were established.: phase 1 (2.40 kg m−3), phase 2 (4.95 kg m−3), phase 3 (8.71 kg m−3) and phase 4 (12.23 kg m−3). The successful maturation of the bioreactors occurred around on the 100th experimental day when the nitration rate increased to 57 % in MBBR1 and 38 % in MBBR2. 105 species were identified in the biofilms, which were grouped into 65 genera, three of which were essential: Pseudomonas (21.7 %), Nitrospira (15.1 %) and Gemmobacter (11.2 %). MBBR start-up without bacterial inoculation is time-consuming, however, strengthened by important nitrifying groups.

Heterogeneous precipitate microstructure design in β-Ti alloys by regulating the cooling rate

Cooling after solutionizing or aging plays a crucial role in heat treatment and can greatly influence the final precipitate microstructure and mechanical properties of titanium (Ti) alloys. In this study, we employ phase field simulations to strategically engineer heterogeneous precipitate microstructures in near β-Ti alloys by manipulating the cooling rate, which leads to different phase transition mechanisms. By varying the cooling rate within the temperature range of 900 ∘C to 500∘C, we identify four distinct microstructures: uniformly distributed fine congruent αc plates and fine α precipitates, heterogeneous and hierarchical α precipitates, and uniformly distributed coarse α precipitates. Further analysis reveals that these diverse precipitate microstructures originate from three distinct phase transition mechanisms, i.e., congruent transition, pseudospinodal decomposition, and classical nucleation and growth, each activated at different temperatures during continuous cooling. Utilizing the insights from the simulations, we successfully produce microstructures in Ti-5Al-5Mo-5V-3Cr-1Zr (Ti55531) with heterogeneous α precipitates by applying intermediate cooling rates (∼0.01∘C/s), which activate classical nucleation and growth as well as pseudospinodal decomposition. These samples exhibit exceptional comprehensive mechanical properties, including an ultimate strength of approximately 1260 MPa and a total elongation of around 14 %. This investigation provides valuable guidance for designing novel heterogeneous precipitate microstructures by simply controlling the cooling rate, leading to significant enhancements in the mechanical properties of β-Ti alloys.

Auto-BCS: A Hybrid System for Real-Time Breast Cancer Screening from Pathological Images.

Breast cancer is recognized as a prominent cause of cancer-related mortality among women globally, emphasizing the critical need for early diagnosis resulting improvement in survival rates. Current breast cancer diagnostic procedures depend on manual assessments of pathological images by medical professionals. However, in remote or underserved regions, the scarcity of expert healthcare resources often compromised the diagnostic accuracy. Machine learning holds great promise for early detection, yet existing breast cancer screening algorithms are frequently characterized by significant computational demands, rendering them unsuitable for deployment on low-processing-power mobile devices. In this paper, a real-time automated system "Auto-BCS" is introduced that significantly enhances the efficiency of early breast cancer screening. The system is structured into three distinct phases. In the initial phase, images undergo a pre-processing stage aimed at noise reduction. Subsequently, feature extraction is carried out using a lightweight and optimized deep learning model followed by extreme gradient boosting classifier, strategically employed to optimize the overall performance and prevent overfitting in the deep learning model. The system's performance is gauged through essential metrics, including accuracy, precision, recall, F1 score, and inference time. Comparative evaluations against state-of-the-art algorithms affirm that Auto-BCS outperforms existing models, excelling in both efficiency and processing speed. Computational efficiency is prioritized by Auto-BCS, making it particularly adaptable to low-processing-power mobile devices. Comparative assessments confirm the superior performance of Auto-BCS, signifying its potential to advance breast cancer screening technology.

Effects of sexual counseling on sexual function and sexual quality of life of women with permanent intestinal ostomy.

Patients with an intestinal ostomy may experience significant sexual dysfunction that may have adverse impacts on quality of life. Appropriate sexual health counseling can be beneficial for these patients. This study was conducted to determine the effect of sexual counseling on the sexual function and sexual quality of life of women with a permanent intestinal ostomy. For this experimental study, 60 female patients with a permanent intestinal ostomy were selected through convenience sampling and then randomly assigned to either the intervention or control groups. Patients in the intervention group received four 90-minute individual counseling sessions based on the PLISSIT (permission [P], limited information [LI], specific suggestions [SS], and intensive therapy [IT] model over a period of 4 weeks). The control group underwent routine training. Data were collected by use of a demographic information questionnaire, the Female Sexual Function Index, and the Sexual Quality of Life Female questionnaire. Both groups completed the questionnaires before and after the intervention. Study outcomes were the resulting data for the Female Sexual Function Index and the Sexual Quality of Life Female questionnaire. The results revealed a significant increase in the mean score of sexual function in the intervention group after counseling (P = .001). No significant difference was observed in the mean score of sexual quality of life between the 2 groups before the intervention (P > .05). In contrast, a significant increase was noted in the intervention group's sexual quality of life after the intervention (P = .001). The results indicate a need to sexual counseling interventions directed toward sexual function and sexual quality of life in women with permanent intestinal ostomy. Study strengths include utilization of the PLISSIT model for sexual counseling as an invaluable roadmap for healthcare professionals, systematically addressing patient needs within a tailored framework, and prescribing appropriate strategies over 4 distinct phases. Limitations include the use of convenience sampling and no follow-up duration. This study demonstrated the efficacy of counseling in enhancing sexual well-being of women with permanent intestinal ostomy.

Enhancing Nitrate Reduction to Ammonia Through Crystal Phase Engineering: Unveiling the Hydrogen Bonding Effect in δ-FeOOH Electrocatalysis.

Crystal phase engineering has emerged as a powerful tool for tailoring the electrocatalytic performance, yet its impact on nitrate reduction to ammonia (NRA) remains largely uncharted territory. Herein, density functional theory (DFT) calculations are performed to unravel the influence of the crystal phase of FeOOH on the adsorption behavior of *NO3. Inspiringly, FeOOH samples with four distinct crystal phases (δ, γ, α, and β) are successfully synthesized and deployed as electrocatalysts for NRA. Remarkably, among all FeOOH samples, δ-FeOOH demonstrates the superior NRA performance, achieving a NH3 Faradic efficiency ( ) of 90.2% at -1.0V versus reversible hydrogen electrode (RHE) and a NH3 yield rate ( ) of 5.73mg h-1 cm-2 at -1.2V. In-depth experiments and theoretical calculations unveil the existence of hydrogen bonding interaction between δ-FeOOH and *NOx, which not only enhances the adsorption of *NOx but also disrupts the linear relationships between the free energy of *NO3 adsorption and various parameters, including limiting potential, d-band center (εd) and transferred charge from FeOOH to *NO3, ultimately contributing to the exceptional NRA performance.

Insights into processes and consequent metal(loid) behavior in dredged estuarine sediments upon electrokinetic treatment

The use and reuse of natural and waste materials after treatment has become increasingly crucial as a means of achieving sustainable and environmentally-friendly solutions, and is part of a broader trend towards embracing circular economy principles. This study aims to understand the behavior of different elements (metal(loid)s and non-metals) and minerals during and after electrokinetic remediation (EKR) and to develop an effective approach to monitor its progress and overcome unwanted occurrences. In this regard, estuarine sediments, collected from Tancarville (Seine River estuary, France), were electrokinetically treated using a 64 L laboratory reactor; treatment was done 8 h per day for 21 days. The physico-chemical properties (pH, electric conductivity, and oxido-reduction potential) and current were monitored during treatment. The spatial evolution of the physico-chemical, physical (grain size distribution), mineral (mainly carbonates), organic, and elemental (As, Ca, Cl, Mg, Na, Pb, Sr, Zn, and Zr) characteristics was studied to assess the treatment efficiency. The results showed that the acidic conditions in the anodic sediments caused the dissolution of carbonates (calcite, dolomite, and aragonite), resulting in a considerable reduction in As, Zn, and Pb. Additionally, Cl as well as electric conductivity were significantly reduced from most sediments, which is essential in agricultural practices. Furthermore, materials had precipitated and settled in the anolyte and catholyte chambers, which acted as sorbents for elements that were released from the sediments (mainly Zn and As). Finally, three distinct phases occurred during treatment and were mainly linked to the current intensity and electric conductivity on the one hand, and the dissolution of carbonates and metal(loid) release on the other. This approach can be used to treat sediments and other media to improve the overall efficiency of remediation processes and create an end product with desired characteristics.