Standard Process Research Articles

Effects of standard fish processing practices on livelihood status of fish processors in Lagos and Osun States

Effects of standard fish processing practices on livelihood status of fish processors in Lagos and Osun States

Silica Waveguide Thermo-Optic Mode Switch with Bimodal S-Bend.

A silica waveguide thermo-optic mode switch with small radius bimodal S-bends is demonstrated in this study. The cascaded multimode interference coupler is adopted to implement the E11 and E21 mode selective output. The beam propagation method is used in design optimization. Standard CMOS processing of ultraviolet photolithography, chemical vapor deposition, and plasma etching are adopted in fabrication. Detailed characterizations on the prepared switch are performed to confirm the precise fabrication. The measurement results show that within the wavelength range from 1530 to 1575 nm, for the E11 mode input, the switch exhibits an extinction ratio of ≥13.1 dB and a crosstalk ≤-22.8 dB at an electrical driving power of 284.8 mW, while for the E21 mode input, the extinction ratio is ≥15.5 dB and the crosstalk is ≤-18.1 dB at an electrical driving power of 282.4 mW. These results prove the feasibility of multimode S-bends in mode switching. The favorable performance of the demonstrated switch promises good potential for on-chip mode routing.

The Socioeconomic Impact of Transport Costs for Adult Patients Requiring Haemodialysis: A Mixed Methods Study.

Patients requiring haemodialysis often perceive the cost of their travels to the dialysis centres as a significant burden. The study aimed to collect a first Swiss national data set on transport costs and assess their impact on patients and their relatives. In addition to interviews with patients, a quantitative survey was developed and distributed online using a voluntary sampling strategy. Data were analysed by means of descriptive statistics. A Sounding Board of patients, relatives, and healthcare professionals accompanied all steps of the project. A total of 6 dialysis patients were interviewed; 437 respondents of the national survey met the inclusion criteria. Patients travel a median distance of 7.5 km to their dialysis centres. For 78% of them, the journey takes up to 30 min, and nearly half use their private car as their main mode of transport. The median annual transport costs are CHF 2925 (mean = CHF 5041). Approximately half of the patients perceive transport costs as a burden or limitation, yet only about 30% receive financial support, for which there is no standard process. Patients requiring financial support reported difficulties navigating the system. This study highlighted that many dialysis patients are burdened by transport costs and receive limited financial support and counselling services. Implementation of a standardised process for financial support should be explored.

Grouping based calculus for propositional linear temporal logic

In this paper, the authors research the problem of loops in linear temporal logic PLTL. The task involves defining the standard rule application process for the derivation procedure (as used in [4] and [5]), determining and proving properties for the absence of a loop beneath some sequent, and creating a new calculus G*TL, which uses the proposed sequent grouping method, along with the method of marks (similar marking concepts were proposed in [5] and [6]). A new type of structural rule (GROUP), along with a modification of the rule (∘) to (∘*) is introduced. Finally, it is shown that the loop checking mechanism used in calculus G*TL is efficient, comparing it with other known calculi for logic PLTL.

INTEGRATED FINANCIAL REPORTING – STEP FORWARD IN SATISFYING THE INFORMATION NEEDS OF STAKEHOLDERS?!

The turbulent beginning of the 21st century, characterized by, among other things, financial scandals related to the operations of several well-known corporations, as well as the world economic crisis imposed the need for companies to provide stakeholders (external and/or internal), and especially current and potential investors, with additional information related to broader social and environmental aspects of their business. For this purpose, the concept of corporate social responsibility and integrated reporting has been developing for the last thirty years, as a tool that should meet the growing needs for financial and non-financial information. The most important accounting authorities (Financial Accounting Standards Board – FASB and International Accounting Standards Board – IASB), as well as the corresponding bodies within the European Union, are trying to regulate this matter with documents (codes, initiatives, directives, recommendations, etc.) with the aim of defining rules that will help the management of corporations to meet the growing information needs of stakeholders. Through a critical analysis of the positive and negative sides of the mentioned documents, comparing them with the existing regulations in the Republic of Serbia, we determined that the proponents of the concept of integrated reporting face challenges similar to those that characterize the process of standardization, harmonization and convergence of international accounting regulative (IAS/IFRS). Namely, there is an evident need for integrated reporting to be part of the annual financial report, but the structure and information that should be contained in those reports differ, which reduces their usability. Even Directive 2014/95/EU, which represent the only document on which the expert public agreed, failed to overcome the mentioned problems, so the need to revise this document is a confirmation that additional efforts are needed to increase the comparability, reliability and relevance of these reports. On the other hand, the adoption of IAS/IFRS that would deal exclusively with integrated reporting could contribute to the further development of this concept, because the inclusion of environmental accounting in the provisions of several current IAS/IFRS represents a solid basis for the creation of quality information on business sustainability, but their further shaping and publication depends on the degree of corporate awareness in that field, specific regulatory requirements of individual countries, as well as the level of accounting culture, which in our conditions is not at an enviable level. There is also a fear that too long harmonization, similar to IAS/IFRS, will create a kind of "vicious circle" in which the possibility or need to revise one of the related documents or possibly an accounting standard will be practically impossible due to their interdependence and intertwining with the provisions of other regulations.

HSPA: High-Throughput Sparse Polynomial Multiplication for Code-based Post-Quantum Cryptography

Increasing attention has been paid to code-based post-quantum cryptography (PQC) schemes, e.g., HQC (Hamming Quasi-Cyclic) and BIKE (Bit Flipping Key Encapsulation), since they’ve been selected as the fourth-round National Institute of Standards and Technology (NIST) PQC standardization candidates. Though sparse polynomial multiplication is one of the critical components for HQC and BIKE, hardware-implemented high-performance sparse polynomial multiplier is rarely reported in the literature (due to its high-dimension and sparsity of polynomials involved in the computation). Based on this consideration, in this article, we propose two novel H igh-throughput S parse P olynomial multiplication A ccelerators (HSPA) for the mentioned two code-based PQC schemes. Specifically, we have designed the two accelerators based on two different implementation strategies targeting potential applications with different resource availability, i.e., one accelerator deploys a memory-based structure for computation while the other does not need memory usage. We have proposed three layers of coherent interdependent efforts to obtain the proposed accelerators. First, we have proposed two implementation strategies to execute the targeted sparse polynomial multiplication, i.e., a new parallel segment based accumulation (PSA) approach and a novel permutating-with-power (PWP)-based method. Then, the proposed two hardware accelerators are presented with detailed structural descriptions. Finally, field-programmable gate array (FPGA)-based implementation is presented to showcase the superior performance of the proposed accelerators. A proper comparison is also carried out to confirm the efficiency of the proposed designs. For instance, the proposed accelerator (using memory-based structure) has 56.84% and 80.25% less area-delay product (ADP) than the existing memory-based design (an extended high-speed version) on the UltraScale+ device, respectively, for n =17,669 and ω =75 (HQC) and n = 12,323 and ω =142 (BIKE). The proposed design strategy fits well with the two targeted code-based PQC schemes, which can be extended further to construct high-performance hardware cryptoprocessors. We hope the results of this work will be useful for the ongoing NIST PQC standardization process.

Full Key-Recovery Cubic-Time Template Attack on Classic McEliece Decapsulation

Classic McEliece is one of the three code-based candidates in the fourth round of the NIST post-quantum cryptography standardization process in the Key Encapsulation Mechanism category. As such, its decapsulation algorithm is used to recover the session key associated with a ciphertext using the private key. In this article, we propose a new side-channel attack on the syndrome computation in the decapsulation algorithm that recovers the private key, which consists of the private Goppa polynomial g and the permuted support L. The attack relies on both practical aspects and theoretical contributions, namely that the side-channel distinguisher can accurately discriminate elements of the permuted support L, while relying only on a standard noisy Hamming weight leakage assumption and that there exists a cubic-time algorithm that uses this information to recover the private Goppa polynomial g. Compared with previous work targeting the Classic McEliece private key, this drastically improves both on the assumptions made in the attacker model and on the overall efficiency of the key-recovery algorithm. We have carried out the attack in practice on a microcontroller target running the reference implementation of Classic McEliece, and make the full attack source code available.

FalconSign: An Efficient and High-Throughput Hardware Architecture for Falcon Signature Generation

Falcon is a lattice-based quantum-resistant digital signature scheme renowned for its high signature generation/verification speed and compact signature size. The scheme has been selected to be drafted in the third round of the post-quantum cryptography (PQC) standardization process due to its unique attributes and robust security features. Despite its strengths, there has been a lack of research on hardware acceleration, primarily due to its complex calculation flow and floating-point operations, which hinders its widespread adoption. To address this issue, we propose FalconSign, a high-performance, configurable crypto-processor designed to accelerate Falcon signature generation on FPGA/ASIC through algorithmhardware co-design. Our approach involves a new scheduling flow and architecture for Fast-Fourier Sampling to enhance computing unit reuse and reduce processing time. Additionally, we introduce several optimized modules, including configurable randomness generation units, parallel floating-point processing units, and an optimized SamplerZ module, to improve execution efficiency. Furthermore, this paper presents a finely optimized hardware accelerator for the Falcon scheme. Our FPGA implementation results demonstrate a throughput improvement of approximately 5.1 x compared to state-of-the-art designs, with 2.8x/4.5x/4.2x/3.2x fewer in the area (LUTs/FFs/DSPs/BRAMs)-time product, for NIST security level V. The crypto-processor occupies an area of 0.71 mm2 and achieves 5.2k OPS at throughput on the TSMC 28nm process for NIST security level I.

Embodiment of Light‐Mediated Main‐Chain Scissionable Functionality While Preserving the Structure of Conventional Photoimaging Copolymer

AbstractThe rational design and development of a main‐chain scissionable functional copolymer platform is reported by incorporating a photocleavable nitrobenzyl ester group into the middle of the copolymer backbone while fully preserving its overall structure and function for photopatterning applications on delicate organic semiconductor films. As a model system, a positive‐tone photoimaging fluoroalkyl copolymer is used containing a photoisomerizable spiropyranyl unit. The nitrobenzyl ester functionality degrades under UV light and enhances solubility modulation and photopatternability by reducing chain length. This behavior is systematically studied across copolymers with varying, yet narrowly distributed, molecular weights. To further improve the sensitivity of the photoimaging copolymer, it is demonstrated that minimal structural modification of the cleavable group, specifically altering the positions of the methoxy and nitro groups, are highly effective. Finally, a square array of a chemically susceptible organic electron transport material, suitable for organic light‐emitting diodes (OLEDs), is fabricated using the copolymer through conventional lithography and pattern transfer processes. This work highlights the importance of rationally designing main‐chain scission‐type light‐sensitive materials that maintain the core structure of conventional materials, making them highly compatible and desirable for standard organic electronic device fabrication processes.

Klasifikasi Tingkat Depresi pada Anak dengan Menggunakan Algoritma Neural Network

Depression in children is an increasingly concerning mental health issue worldwide, with significant impacts on their social, academic, and emotional development. Early detection and prevention of depression are crucial for reducing long-term effects and improving children's quality of life. Conventional methods such as clinical observation and interviews have limitations, particularly regarding subjectivity and resource requirements. Therefore, this study develops a predictive model based on machine learning using a neural network algorithm to classify depression levels in children more accurately and promptly. The model utilizes data from various sources, including body humidity, body temperature, and step count, to detect signs of depression automatically and objectively. This research employs the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology, encompassing business understanding, data understanding, data preprocessing, modeling, model evaluation, and deployment stages. The dataset comprises 2001 entries with three main features, classified into three depression levels: normal, low, and high. The neural network used in the modeling demonstrates excellent performance, with accuracy nearly reaching 100% and loss values decreasing to almost zero. The model is then implemented in a web-based application designed to assist end users, such as parents and teachers, in classifying children's depression levels. Although the application does not yet have an integrated database, testing shows classification results consistent with the existing dataset, confirming its potential as a tool for early detection of depression in children.

Reverse-time migration of mobile marine vibrator data

Marine vibrators are viable alternatives to seismic air guns in ocean-bottom acquisition due to their less adverse impact on the environment, their ability to generate lower frequency content, and their suitability for simultaneous acquisition. However, mobile marine vibrators introduce a unique set of processing and imaging challenges for ocean-bottom acquisition, the main examples of which are the Doppler effect and the time-dependent source-receiver offsets, which are not features of conventional marine acquisitions. Standard seismic data processing and imaging techniques assume stationary sources and are not fully suitable for mobile marine vibrator data without modifications. Not accounting for source motion in seismic imaging introduces phase change and mispositioning of imaged structures. Further, ignoring source-motion effects in imaging workflow may lead to the estimation of inaccurate migration velocity models or imply the use of incorrect migration velocity, e.g., in seismic-to-well ties. We develop a reverse-time migration (RTM) approach that accounts for the source-motion effects and is capable of producing accurate subsurface images, closely matching stationary acquisition and imaging results. Synthetic examples illustrate the ability of the proposed method to construct accurate subsurface RTM images even for source velocities higher than those commonly used in typical marine acquisitions. Our approach is not limited to imaging mobile marine vibrator data in ocean-bottom acquisition, but is also applicable to mobile streamer data using marine vibrators or seismic air-gun sources.

Damage characterization of AlSi10Mg plates subjected to rigid impacts up to 300 m/s: comparison between subtractive and additive manufacturing

Mechanical structures built using the additive manufacturing (AM) process are generating significant interest due to their ability to design structural components with complex geometries. Indeed, additive processes, by adding material layer by layer, enables the creation of geometries that would be unfeasible using standard processes. However, while mechanical tests have extensively validated the use of conventional processes, the characterization of parts generated by less conventional processes, such as additive manufacturing, remains open to discussion. Specifically, will a part manufactured by AM meet the specifications in terms of mechanical strength? This paper contributes to answering this question by comparing identical AlSi10Mg plates manufactured using the AM process with a LASER powder bed fusion (L-PBF) machine (additive) and by conventional subtractive process (SM), subjected to high-velocity impacts. The impacts have been conducted on additive and subtractive 70*150*2 mm plates up to 300 m/s.” Based on measurements of projectile impact and residual velocities, as well as the study of deformation profiles of the different plates, the damage domains were identified. These tests highlighted significant differences between the different processes.

Characterization of Bimetallic Pd-Fe Nanoparticles Synthesized in Escherichia coli.

Biologically mediated nanoparticle (NP) synthesis offers a reliable and sustainable alternative route for metal NP production. Compared with conventional chemical and physical production methods that require hazardous materials and considerable energy expenditure, some microorganisms can reduce metal ions into NPs during standard metabolic processes. However, to be considered a feasible commercial option, the properties and inherent activity of bio-NPs still need to be significantly improved. In this work, we present an Escherichia coli-mediated synthesis method for catalytically active Pd-Fe NPs. The produced biogenic Pd-Fe NPs with varying Fe content were characterized using complementary analytical techniques to assess their size, composition, and structural properties. In addition, their catalytic performance was assessed by using standardized chemical reactions. We demonstrate that the combination of Pd with Fe leads to synergistic effects that enhance the catalytic performance of Pd NPs and make biogenic Pd-Fe NPs excellent potential substitutes for currently used catalysts. Briefly, the apparent rates for the model reaction of 4-nitrophenol reduction to 4-aminophenol catalyzed by Pd-based nanoparticles were as high as 0.1312 min-1 using bimetallic Pd-Fe NPs, which is far superior to the rates of monometallic Pd NPs counterparts. This study provides a feasible strategy for the synthesis of multimetallic Pd-based NPs using common microbial processes. It emphasizes the potential of biogenic Pd-Fe NPs as efficient and sustainable catalysts for hydrogenation reactions, offering an environmentally friendly synthesis for various applications, including wastewater treatment and the production of fine chemicals.

A Preliminary Numerical Thermal Analysis of an Endometrial Ablation Procedure Based on Foley’s Catheter

Dysfunctional uterine bleeding (DUB) is an ailment affecting a substantial number of women during a significant part of their reproductive years. This condition usually leads to discomfort, mild or severe pain, or, in some extreme cases, anemia. It may be caused by diverse factors such as hormonal issues, structural abnormalities, or even cancer in a woman’s reproductive tract. A typical DUB treatment requires a pharmacological approach through the prescription of drugs. Nonetheless, some patients require a more involved treatment calling for surgical procedures. In order to avoid hysterectomy, which is the complete removal of the uterus, the medical community has devised, over the years, alternative surgical schemes to handle DUB issues. One such treatment is the “endometrial ablation technique” where the inner lining of the uterus is subjected to a controlled destruction by using a hot, approximately constant-temperature fluid inside a balloon, which is placed in contact with the uterine wall of the patient. As a means to avoid the high costs associated with such devices, the medical community has proposed a similar treatment in which the fluid inside the balloon is no longer held at a high constant temperature but rather diminishes as the treatment progresses. The main purpose of this contribution is to critically assess the effectiveness of this second, low-cost endometrial ablation treatment. Consequently, a mathematical model is devised in which Pennes’ bioheat equation is employed to predict the transient temperature field of the uterine wall together with an energy balance that yields the temperature of the saline solution inside the thermal balloon, throughout the duration of the treatment. These equations aresolved by utilizing the finite volume method and the numerical predictions are verified by comparing the present results with similar cases from the literature. Once the verification phase is authenticated, the uterine wall and fluid balloon transient temperature fields are obtained for typical situations reported in the medical literature. On general grounds, the simulations indicate that the extent of the affected tissue is strongly dependent on the volume,on the type of fluid inside the thermal balloon, and on the magnitude of the perfusion of the uterus. Moreover, it was found that the proposed low-cost treatment can indeed be a successful alternative to the standard endometrial ablation process under some viable circumstances that are described in the contribution.

Enhancing Carbon Trading Mechanisms through Innovative Collaboration: Case Studies from Developing Nations

Against a backdrop of global climate change mitigation efforts, carbon trading has emerged as a critical mechanism, yet developing countries often lack the necessary infrastructure and collaborative frameworks. The research investigates how intermediaries facilitate stakeholders and employ innovative practices to foster effective carbon trading markets. Methodologically, it employs a qualitative approach, conducting in-depth case studies of four intermediaries through 32 semi-structured interviews and archival document. Findings underscore the pivotal role of digital platforms in enabling real-time trading, rigorous standardization processes to ensure market credibility, and multi-stakeholder engagement strategies that promote inclusive participation. This research contributes to the theoretical understanding of carbon trading by illustrating how digital platforms and technological integration enhance resource acquisition and allocation. It emphasizes the significance of standardization and verification processes in building trust among stakeholders, crucial for effective supply chain collaboration. Practically, the study highlights the benefits of these approaches in enhancing market efficiency and transparency. It also underscores the importance of multi-stakeholder engagement strategies and strategic alliances for creating resilient and inclusive carbon trading markets, offering actionable insights for stakeholders and policymakers alike.

Spray drying process challenges and considerations for inhaled biologics.

Spray drying presents numerous advantages over other drying technologies, particularly for inhaled biologics because of the fine-tuned particle attributes requirements. To fully leverage these benefits, it is crucial to address several process challenges and considerations throughout the end-to-end spray-drying process, including stages prior to, during, and post- drying. This review provides a detailed overview of the challenges associated with spray-drying of biologics along with the aspects of protein degradation. Furthermore, it delineates the entire spray-drying process, comprising feed solution preparation, spray drying, and bulk powder handling, along with protein degradation mechanisms and analytical tools for protein and aerosol performance assessment. Pertaining to inhaled biologic products, this review also sheds light on major bottlenecks and potential challenges, particularly during scale-up. While some challenges are yet to be conclusively addressed, potential control and mitigation strategies from industry perspective are presented and examined. Lastly, the review briefly explores trending topics in this field that could add value to the standard spray-drying process and may be incorporated in future drying technologies.

Matter-antimatter (a)symmetry in de Sitter Universe

We investigate the matter-antimatter properties of elementary systems, modeled as free quantum fields, within the global structure of de Sitter spacetime. By leveraging the distinctive causal and analytic properties of de Sitter spacetime, we propose that matter-antimatter asymmetry could emerge as an observer-dependent effect shaped by time orientation within a local causal patch, rather than as a fundamental property of de Sitter Universe itself. This kinematic perspective complements, rather than replaces, standard dynamical processes —such as baryon number violation, violation, and nonequilibrium processes— that fulfill Sakharov's criteria. Within this framework, the limited presence of antimatter in our predominantly matter-filled Universe, specifically within the causal patch of de Sitter spacetime under consideration, may arise from these mechanisms, though through pathways distinct from conventional interpretations.

“Developing a manual clinical trials screening process in a diverse southern gynecologic oncology practice”

ObjectiveThere is no standard clinical trial screening process in gynecologic oncology. In our low resource, highly diverse gynecologic oncology patient population, we sought to create an equitable, adaptable, manual screening process. MethodsOur objective is to describe our clinical trial screening process and success in improving trial enrollment. An Institutional Review Board (IRB) approved quality improvement (QI) project was implemented in July 2022 to evaluate trial access. Screenable events were defined. Potential patients were those with a screenable event: new patients or diagnoses, regimen changes, progressions, and recurrences. Events were categorized into screen positive or screened no trial available. Screen positives were further categorized as screen positive, enrollment failure events or enrollments. Data about patients were collected via weekly research team meetings. Monthly meetings occurred to review progress. The data were compared to trials available, number of patients with trail available, and those that enrolled. Reasons for enrollment fails were tracked. ResultsOver time, “screen no trial available” (SNTA) rates stayed stable, but enrollment rates increased. Patient preference accounted for 32.8 % of enrollment failures (n = 42), pre-existing symptoms 23.4 % (n = 30), and location 21.1 % (n = 27). During increased employee turnover, there was a rise in enrollment fails due to staffing (n = 6, 4.7 %). We describe an effective process of clearly defining and tracking our patient population and ‘screenable events’ for which all patients are screened and offered trial participation if eligible. ConclusionsWe show that we improved understanding of the patient population, built a clinical trial portfolio better matched to population served, exceeded national averages for enrolling patients on trials, and are improving number eligible.

A Hardware-Efficient Novelty-Aware Spike Sorting Approach for Brain-Implantable Microsystems.

Unsupervised spike sorting, a vital processing step in real-time brain-implantable microsystems, is faced with the prominent challenge of managing nonstationarity in neural signals. In long-term recordings, spike waveforms gradually change and new source neurons are likely to become activated. Adaptive spike sorters combined with on-implant training units effectively process the nonstationary signals at the cost of high hardware resource utilization. On the other hand, static approaches, while being hardware-friendly, are subjected to decreased processing performance in such recordings where the neural signal characteristics gradually change. To strike a balance between the hardware cost and processing performance, this study proposes a hardware-efficient novelty-aware spike sorting approach that is capable of dealing with both variated spike waveforms and spike waveforms generated from new source neurons. Its improved hardware efficiency compared to adaptive ones and capability of dealing with nonstationary signals make it attractive for implantable applications. The proposed novelty-aware spike sorting especially would be a good fit for brain-computer interfaces where long-term, real-time interaction with the brain is required, and the available on-implant hardware resources are limited. Our unsupervised spike sorting benefits from a novelty detection process to deal with neural signal variations. It tracks the spike features so that in case of detecting an unexpected change (novelty detection) both on and off-implant parameters are updated to preserve the performance in new state. To make the proposed approach agile enough to be suitable for brain implants, the on-implant computations are reduced while the computational burden is realized off-implant. The performance of our proposed approach is evaluated using both synthetic and real datasets. The results demonstrate that, in the mean, it is capable of detecting 94.31% of novel spikes (wave-drifted or emerged spikes) with a classification accuracy (CA) of 96.31%. Moreover, an FPGA prototype of the on-implant circuit is implemented and tested. It is shown that in comparison to the OSORT algorithm, a pivotal spike sorting method, our spike sorting provides a higher CA at significantly lower hardware resources. The proposed circuit is also implemented in a 180-nm standard CMOS process, achieving a power consumption of 1.78[Formula: see text][Formula: see text] per channel and a chip area of 0.07[Formula: see text]mm2 per channel.

Experimental Liouvillian exceptional points in a quantum system without Hamiltonian singularities

Abstract Hamiltonian exceptional points (HEPs) are spectral degeneracies of non-Hermitian Hamiltonians describing classical and semiclassical open systems with losses and/or gain. However, this definition overlooks the occurrence of quantum jumps in the evolution of open quantum systems. These quantum effects are properly accounted for by considering quantum Liouvillians and their exceptional points (LEPs). Specifically, an LEP corresponds to the coalescence of two or more eigenvalues and the corresponding eigenmatrices of a given Liouvillian at critical values of external parameters (Minganti et al 2019 Phys. Rev. A 100 062131). Here, we explicitly describe how standard quantum process tomography, which reveals the dynamics of a quantum system, can be readily applied to detect and characterize quantum LEPs of quantum non-Hermitian systems. We conducted experiments on an IBM quantum processor to implement a prototype model with one-, two-, and three qubits simulating the decay of a single qubit through competing channels, resulting in LEPs but not HEPs. Subsequently, we performed tomographic reconstruction of the corresponding experimental Liouvillian and its LEPs using both single- and two-qubit operations. This example underscores the efficacy of process tomography in tuning and observing LEPs even in the absence of HEPs.