Current Time Research Articles

Effect of the pulsed current of on-chip thermoelectric cooler on temperature response during thermal shock in localized cooling

On-chip thermoelectric cooling (TEC) emerges as a promising solution to address the issue of localized chip overheating, effectively mitigating thermal shock induced by local heat flow conduction and enhancing both reliability and performance of chips. In this study, a three-dimensional numerical model is developed to investigate the effectiveness of on-chip thermoelectric cooler’s pulse current in mitigating temperature fluctuations caused by thermal shock at hot spots. The influence of the magnitude and lag time of the pulse current on the temperature fluctuation of Si chip during thermal shock is analyzed. The calculation results show that the implementation of on-chip TEC can effectively mitigate the issue of localized temperature overheating caused by thermal shock. By adjusting the maximum and minimum current of the on-chip thermoelectric cooler, it is possible to mitigate the fluctuation amplitude of chip temperature induced by thermal shock at the hot spot. The findings also indicate that the lag time between input current and thermal shock can lead to an increase in the maximum temperature of the chip. In addition, experimental results using commercially thermoelectric cooler also show that when the input current of TEC is pulse current, the temperature fluctuation caused by thermal shock can be reduced better.

Fast Start-Up Control of Both-Side Current Without Overshoot Focusing on Rectification Timing for Dynamic Wireless Power Transfer Systems

The paper proposes a method to improve the tran- sient characteristics of current overshoot and oscillation at the start of power transmission for a dynamic wireless power transfer system. The system is important to reduce the settling time as short as possible without current overshoots for a stable power supply. However, conventional methods to suppress current overshoot have a slow response on the secondary side. This paper proposes the superposition of primary and secondary responses. The proposed method controls the secondary voltage by comparing the steady-state current with the current value on the secondary side. The method can effectively suppress the oscillations in the transient response by applying the secondary voltage at the appropriate timing. This paper also studied the ro- bustness of constraints based on model analysis and experimental verification. In the experiments, the proposed method reduces the current overshoot and the settling time of the secondary current, and maximizes the receiving energy.

Review—Nanosystems-Enhanced Electrochemical Biosensors for Precision in One Health Management

One Health is a comprehensive and cohesive strategy that seeks to effectively manage and enhance the well-being of people, animals, and ecosystems in a sustainable manner. Electrochemical biosensors are indispensable vectors for One Health management, with diverse applications across industrial process control, environmental monitoring, healthcare, microbiology, and quality assurance. The integration of nanotechnology has propelled innovative sensing algorithms, enhancing the efficiency and precision of biosensors. Nanoscale material integration amplifies their ability to detect molecules and single biomolecules with nano-biosensors utilizing nanoparticles, nanowires, carbon nanotubes (CNTs), nanorods, and quantum dots. Nanomaterials, distinguished by surface functionalities, tunability of physical/chemical properties, high detection sensitivity, large surface area, stability, and thermal/electrical conductivity, are instrumental in architecting nano-biosensors. The main limitations in current times are scalability, cross-sensitivity, complex immobilization pathways, and the toxicity factor of nanosensors, which are hazardous for the ecosystem as well as humans. This review explores the fundamentals of nanotechnology-enabled electrochemical biosensors, encompassing their composition, manufacturing materials, and diverse applications, highlighting their necessity in advancing biosensor technology to control environmental contamination/human diseases in order to manage One Health.

Improved optical performance in circular-grating distributed feedback nanoplasmonic lasers

Optical modes control has been driven from vertical cavity surface emitting lasers (VCSELs) applications with multi-mode operation such as optical fiber communication or optical sensing. Optical gain materials coupling with optical resonators provides an effective way to tuning the optical mode of VCSELs. In this paper, a kind of novel circular-grating distributed feedback (CGDFB) nanoplasmonic laser is designed by using a special semiconductor nanorods array VCSEL coupled optically with a second-order distributed feedback (DFB) circular grating. In the device, the mode field is cooperatively controlled by the confinement of surface plasmon around the nanorod cavity and the spatial tuning with the DFB circular grating. By optimizing the design on the device comprehensively, the CGDFB nanoplasmonic laser exhibits the optimum lasing performance with a single-longitudinal mode peak at 511.2 nm with a side-mode suppression ratio of 45 dB. The 3 dB line-width is compressed to 1.98 p.m. at a driven current of four times of the threshold current of 124 mA. A six-fold rotational symmetric far-field mode corresponding to the third-order Laguerre Gaussian azimuth mode is produced by the DFB circular grating. This work paves a fundamental way for the mode engineering design of novel nanolaser in the technical applications of optical communication, sensing and integrated photonics.

Predicting the Rate of Degradation Related to Oxygen Electrode Delamination in Solid Oxide-Ion Electrolyzers

One of the leading causes for the performance degradation in H2-producing solid oxide electrolytic cells (SOECs) is the gradual delamination of oxygen electrode (OE) from the electrolyte under a strong anodic polarization. Identification of the key factor that controls the rate of OE delamination is of paramount importance to achieve long-term stable operation of SOECs. Here we show from thousands of hours of testing data that the exchange current density (i°) of OE can be leveraged as a predictor for the rate of delamination. To obtain i°, we apply DC-biased electrochemical impedance spectroscopy on a three-electrode symmetrical cell to measure polarization resistance (Rp) of OE as a function of current density (i) and time (t). The collected Rp-i-t raw data are then converted to overpotential (η)-i-t, from which i° is extracted from the “low-field” approximation. An analytical relationship between i° and time-to-delamination (TTD) is further established from the established i°-i-t relationship. We show that under a constant anodic polarization current density i, the greater the ratio i/i°, the faster the delamination. Therefore, we conclude that the exchange current density of an OE, i°, can be used to predict the rate of OE degradation in solid oxide-ion electrolyzers.

Multi-Think Transformer for Enhancing Emotional Health

The smart healthcare system not only focuses on physical health but also on emotional health. Music therapy, as a non-pharmacological treatment method, has been widely used in clinical treatment, but music selection and generation still require manual intervention. AI music generation technology can assist people in relieving stress and providing more personalized and efficient music therapy support. However, existing AI music generation highly relies on the note generated at the current time to produce the note at the next time. This will lead to disharmonious results. The first reason is the small errors being ignored at the current generated note. This error will accumulate and spread continuously, and finally make the music become random. To solve this problem, we propose a music selection module to filter the errors of generated note. The multi-think mechanism is proposed to filter the result multiple times, so that the generated note is as accurate as possible, eliminating the impact of the results on the next generation process. The second reason is that the results of multiple generation of each music clip are not the same or even do not follow the same music rules. Therefore, in the inference phase, a voting mechanism is proposed in this paper to select the note that follow the music rules that most experimental results follow as the final result. The subjective and objective evaluations demonstrate the superiority of our proposed model in generation of more smooth music that conforms to music rules. This model provides strong support for clinical music therapy, and provides new ideas for the research and practice of emotional health therapy based on the Internet of Things.

Driving factors on unemployment in Iran’s provinces: Do temporal and spatial dynamics matter?

Unemployment is an important index describing an economic situation and the development of societies. The existence of unemployment means a loss of production factor that is not savable and irrecoverable. Therefore, it is essential to proper planning and policymaking to control and reduce unemployment, and it is necessary to conduct extensive studies on unemployment. Since there is a probability of autocorrelation between the unemployment rate of provinces, it is necessary to pay attention to spatial dynamics. In addition, controlling unemployment requires a long‐run policy, and it cannot be reduced over periods as short as 1 year. Correspondingly, unemployment in a province can be expected to be dynamic by nature and dependent on the unemployment in the previous period. Thus, temporal dynamics should be considered when examining unemployment’s driving factors. To do that, this study seeks to identify the driving factors of unemployment by emphasizing temporal and spatial dynamics in 28 of Iran’s provinces for the period 2001–2019 using the dynamic SAR model. The result indicates that the lag time of unemployment positively affects unemployment in the current time. Additionally, the unemployment of neighbors has a negative and statistically significant impact on the unemployment of provinces. The effects of GDP per capita, government budget per capita, human capital, inflation rate, industrial concentration, the share of the added value by agriculture in GDP, and the share of value added by services in GDP on the unemployment rate are negative and statistically significant.

Micro-particle injection experiments in ADITYA-U tokamak using an inductively driven pellet injector

A first-of-its-kind, inductively driven micro-particle (Pellet) accelerator and injector have been developed and operated successfully in ADITYA-U circular plasma operations, which may ably address the critical need for a suitable disruption control mechanism in ITER and future tokamak. The device combines the principles of electromagnetic induction, pulse power technology, impact, and fracture dynamics. It is designed to operate in a variety of environments, including atmospheric pressure and ultra-high vacuum. It can also accommodate a wide range of pellet quantities, sizes, and materials and can adjust the pellets’ velocities over a coarse and fine range. The device has a modular design such that the maximum velocity can be increased by increasing the number of modules. A cluster of lithium titanate/carbonate (Li2TiO3/Li2CO3) impurity particles with variable particle sizes, weighing ∼50–200 mg are injected with velocities of the order of ∼200 m s−1 during the current plateau in ADITYA-U tokamak. This leads to a complete collapse of the plasma current within ∼5–6 ms of triggering the injector. The current quench time is dependent on the amount of impurity injected as well as the compound, with Li2TiO3 injection causing a faster current quench than Li2CO3 injection, as more power is radiated in the case of Li2TiO3. The increase in radiation due to the macro-particle injection starts in the plasma core, while the soft x-ray emission indicates that the entire plasma core collapses at once.

Clinicodemographic profile of orbital exenteration in a tertiary eye care center - A 20-year experience.

This study aimed to determine the clinical indications for orbital exenteration, demographic profile of these patients, and clinicopathologic correlations in the current times and to compare these results with previous published data. It was a retrospective study. All exenterations performed at a tertiary eye care center over a period of 20 years (from January 2001 to June 2020) were retrospectively evaluated. Patient records were reviewed to obtain demographic data, presenting symptoms and their duration, laterality, and clinical and histopathologic diagnosis. A total of 352 cases (males:females = 222:130) who underwent exenteration were identified. Patients age ranged from 11 months to 87 years (mean: 43.86 years, median: 50 years). The most common indication for exenteration was found to be eyelid malignancy in 54.36%, followed by retinoblastoma in 18.75% and primary orbital tumors in 14.49%. Out of 156 cases of eyelid malignancies requiring exenteration, squamous cell carcinoma (SCC) was the most common histologic subtype ( n = 94, 60.26%), followed by sebaceous gland carcinoma ( n = 40, 25.64%) and basal cell carcinoma ( n = 20, 12.82%). The most common primary orbital tumors requiring exenteration were adenocystic carcinoma of the lacrimal gland in adults and rhabdomyosarcoma in the pediatric age group. Benign conditions requiring exenteration included fulminant fungal orbital infections and lymphangioma among others. The number of exenterations performed have significantly increased in terms of absolute numbers. However, the ratio of exenteration to other tumor-related surgeries, mainly excision biopsy, has reduced compared to that reported from a previous study. The most common indication in our study remains eyelid malignancy followed by intraocular malignancy. However, SCC has emerged as the most common tumor histologic subtype requiring exenterations.

Knowledge Evaluation on Weather Forecast and Agro-advisory Services to Farmers in Srikakulam District of Andhra Pradesh, India

Weather is the major factor for crop growth and yield. Farmers were more interested on the current real time weather parameters such as rainfall, humidity in air , air temperature, direction and speed of the wind, Knowing of weather forecast is useful to reduce the yield loss and to obtain more yield with high remunerative price. The precise real time data at exact time allows the farmers to plan field management practices like choosing of correct crops, land preparation, field operations like spraying of pesticides and herbicides, irrigation, fertilizer application, harvest, drying and post harvest operations to reduce the crop damage and economic losses. The District Agromet unit (DAMU) located at KVK, Amadalavalasa is sending timely weather advisories to farmers of Srikakulam district based on the forecast issued by IMD. A total number of 1080AgroAdvisory Service (AAS) bulletins were prepared by using DSS software and disseminated to the registered farmers through whatsapp and other social media during 2022-2023. A random sample survey was conducted to study the impact of agro-advisory services to farmers based on weather forecast issued by DAMU, Srikakualm. The sample size was 60 farmers belong to different villages of Amadalavalasa and Srikakulam blocks of Srikakulam district. The study Results revealed that spotlight on illiterate farmers is much more significant and dispersal of advisories in audio or visual format is more comfortable and easy to understand. The results of the survey exposed that among the total farmers the farmers follow for sowing are 45 percent, for spraying operations are 11 percent, for harvest and drying are 62 per cent. Finally this study confirms that the farmers were more concentrate on sowing, harvest and drying related to weather forecast. Hence finally realized that farmers should follow forecast data of weather from choice of crop and its management practices to after harvest operations to get enhanced productivity and also superior net returns.

Attentional bias for hands: Cascade dual‐decoder transformer for sign language production

AbstractSign Language Production (SLP) refers to the task of translating textural forms of spoken language into corresponding sign language expressions. Sign languages convey meaning by means of multiple asynchronous articulators, including manual and non‐manual information channels. Recent deep learning‐based SLP models directly generate the full‐articulatory sign sequence from the text input in an end‐to‐end manner. However, these models largely down weight the importance of subtle differences in the manual articulation due to the effect of regression to the mean. To explore these neglected aspects, an efficient cascade dual‐decoder Transformer (CasDual‐Transformer) for SLP is proposed to learn, successively, two mappings SLPhand: Text → Hand pose and SLPsign: Text → Sign pose, utilising an attention‐based alignment module that fuses the hand and sign features from previous time steps to predict more expressive sign pose at the current time step. In addition, to provide more efficacious guidance, a novel spatio‐temporal loss to penalise shape dissimilarity and temporal distortions of produced sequences is introduced. Experimental studies are performed on two benchmark sign language datasets from distinct cultures to verify the performance of the proposed model. Both quantitative and qualitative results show that the authors’ model demonstrates competitive performance compared to state‐of‐the‐art models, and in some cases, achieves considerable improvements over them.

Protecting occupant in autonomous vehicle accident with rotating seat and belt airbag

In autonomous vehicle, since that occupants no long need to operate the vehicle, they will have time to relax and entertain or communicate with other people. In order to improve the collision safety of the occupants who move freely and have different seat orientation angles in autonomous vehicle, a protection strategy based on the cooperative control of the rotating seat and belt airbag to avoid occupant injuries is proposed: in the pre-crash phase, the occupant on a rotated seat is repositioned into a close-to-standard frontal facing position, while the belt airbag deploys; in the crash phase, the fully deployed belt airbag cushions and absorbs occupant impact with the support of the occupant’s legs to reduce injury. Firstly, the current prediction time for unavoidable collisions in self-driving cars is about 350 ms, therefore, the airbag can be inflated by enlarging the inflation duration to reduce its impact during deployment. Due to the fixed installation position of the dashboard airbag, which cannot accompany the deficiency of seat movement, a new type of belt airbag is designed; Then, the simulation models of ±45° and ±90° seat orientation were established to study the injury mechanism and kinematic response of occupants with different seat orientations in frontal crashes; Finally, the simulation models of active rotating seat with belt airbag were established to study the kinematic response and injury risk of occupants with rotating seat and belt airbag protection strategy. The belt airbag with a capacity of 65 L developed in this paper could effectively protect occupants in a frontal collision at an inflation time of 200 ms and a total inflation mass of 31.4 g; The occupant safety strategy based on rotating seat and belt airbag can effectively reduce the risk of collision injury of occupants with different seat orientations in autonomous vehicle.

Recent Research in Wire Cut Electrical Discharge Machining Process

A product's shape and size are developed through the manufacturing process, which is essential to all sectors. With its unique thermal machining technique, Wire Cut Electrical Discharge Machining (WEDM), items with sharp edges and varied hardness that prove challenging to produce using conventional machining methods can be precisely machined. Utilizing the widely used non-contact material removal technique, the practical technology of the WEDM process is based on the typical EDM sparking phenomenon. When the process was first introduced, WEDM has developed from a crude way to make tools and dies to the best way to produce micro-scale parts with the highest level of surface finish quality and dimensional accuracy. This paper reviews the extensive amount of research done from the EDM process to the development of the WEDM. It reports on the WEDM research that involves optimizing the process parameters and examining the impact of various factors on productivity and machining performance. The impact of multiple WEDM process input parameters, including wire speed, peak current, pulse on and off times, and peak on material removal rate (MRR), surface roughness (Ra), and micro structural analysis, on various process output responses is reviewed in this study.

Reduction of the environmental and health consequences of cigarette butt recycling by removal of toxic and carcinogenic compounds from its leachate.

Cigarette butt is a hazardous waste, and its management faces many challenges. The generation of leachate containing many pollutants including heavy metals is one of the limitations of recycling cigarette butts. The aim of this study was to reduce organic compounds and heavy metals in leachate resulting from cigarette butt recycling in an electrocoagulation reactor. For this purpose, two samples, including freshly smoked cigarette butts and littered cigarette butts, were processed and the treatment of leachate resulting from them was studied in an electrocoagulation reactor. The efficiency of leachate treatment was investigated in the treatment time of 10-40min and current intensity of 20-100mA. The results showed that the minimum reduction of chemical oxygen demand and turbidity was 25.3% and 33.4%, respectively. Increasing the current intensity and treatment time increased the efficiency of removing turbidity and chemical oxygen demand up to 47.1% and 41.2%, respectively, in optimum conditions. The reduction of nickel, chromium, cadmium, and lead in the lowest current density and minimum treatment time was more than 90%, which increased to more than 99% with the increase of the current density and treatment time. The use of electrocoagulation is a suitable solution to reduce heavy metals in leachate resulting from cigarette butt recycling, while the proper reduction of organic compounds in this type of leachate requires further treatment processes.

Microwave Synthesizer: A Biomedical Engineering Technique With Advanced Applications

Abstract: In current times, all major discoveries are believed to occur at the intersections of various fields of science. In such a manner, perhaps the main creative region joining material science, biology and medication is the utilization of microwave advances. In such a way, the motivation behind this work was to explain the useful conceivable outcomes of diagnostic, analytical, synthetic and therapeutic microwave advancements. The related exploration and uses of microwave (MW) science are the arising methodologies of modern energy-based green science, on a nuclear and atomic self-aggregating level. As microwaves develop the synthetic response, they have the potential to greatly impact the chemical reaction. This technology has advanced its utilization in the field of research technology, chemical synthesis, diagnostic chemistry, wastewater treatment, and material science. This article cumulates the various available microwave synthesizers in the market with their pros and cons alongside their wide applications.

Comparative Study of Different High Voltage Switches Used in Pulsed High Voltage Application

High-voltage switches play a crucial role in pulsed power applications, where the efficient and reliable control of highvoltage pulses is required. This study aims to compare different types of high-voltage switches commonly used in pulsed power systems including electromechanical switches, vacuum switches, gas-filled switches, triggered spark gaps and solidstate switches. The comparison study focuses on key performance parameters such as voltage handling capability, current carrying capacity, turn-on time, and repetition rates are considered to provide a comprehensive study and analysis of the switch’s suitability for different pulsed power applications. Gas-filled switches such as spark gaps, thyratrons and ignitrons have been used in pulsed power systems due to their high voltage handling capability and low switching losses. However, they suffer from a limited lifetime and require maintenance and periodic replacement. Solid-state switches, i.e. Silicon-Controlled Rectifiers (SCRs), Insulated Gate Bipolar Transistors (IGBTs) and Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) offer advantages in terms of longevity, reliability, and reduced maintenance. However, they have limitations in high-voltage applications and exhibit higher switching losses. The findings of this comparison study will assist researchers, engineers, and system designers in selecting the most appropriate high-voltage switch for pulsed power applications, considering the specific requirements and constraints of the system. This will ultimately contribute to the advancement and optimization of pulsed power technologies across a wide range of scientific, industrial, and strategic applications.

Dynamic Co-Embedding Model for Temporal Attributed Networks.

In this article, we study the problem of embedding temporal attributed networks, with the goal of which is to learn dynamic low-dimensional representations over time for temporal attributed networks. Existing temporal network embedding methods only learn the representations for nodes, which are unable to capture the dynamic affinities between nodes and attributes. Moreover, existing co-embedding methods that learn the static embeddings of both nodes and attributes cannot be naturally utilized to obtain their dynamic embeddings for temporal attributed networks. To address these issues, we propose the dynamic co-embedding model for temporal attributed networks (DCTANs) based on the dynamic stochastic state-space framework. Our model captures the dynamics of a temporal attributed network by modeling the abstract belief states representing the condition of the nodes and attributes of current time step, and predicting the transitions between temporal abstract states of two successive time steps. Our model is able to learn embeddings for both nodes and attributes based on their belief states at each time step of the temporal attributed network, while the state transition tendency for predicting the future network can be tracked and the affinities between nodes and attributes can be preserved. Experimental results on real-world networks demonstrate that our model achieves substantial performance gains in several static and dynamic graph mining applications compared with the state-of-the-art static and dynamic models.

Energy-Aware Multicriteria Control Performance Assessment

Generally, control system design and the associated assessment of control system quality focuses on cutting-edge performance. Most of the approaches and applied indicators aim for this goal. However, the current times increasingly indicate the need to consider, at least on an equal level, the issue of the resistance of the control system and the energy that it consumes. Indicators for the assessment of the quality of control system operation should take these aspects into account. This study focuses on energy issues. It should be noted that, very often, an actuator device, such as a pump, motor, or actuator, consumes energy. In small single-loop systems, the share of this energy is usually negligible, but in large installations, it begins to reach significant values. This work proposes a multi-criteria assessment of the operation of control systems using information about the control signal. The energy factor can be considered in the form of a quadratic relationship or using the valve travel and valve stroke indicators known in other contexts. The index ratio diagram (IRD) approach is utilized as an energy assessment tool. At the same time, an analysis is carried out showing the impact of energy on other known indicators based on the control error. Finally, a methodology incorporating energy consumed by the control system is proposed.

App-Based Lifestyle Intervention (PINK! Coach) in Breast Cancer Patients-A Real-World-Data Analysis.

Overweight and a lack of physical activity not only increase the risk of recurrence in breast cancer patients but also negatively impact overall and long-term survival, as well as quality of life. The results presented here are the first real-world data from the DiGA PINK! Coach examining the physical activity and BMI of app users. Based on the literature, an approximate weight gain of 10% over 6 months and a decrease in physical activity can be expected. The purpose of this study is to retrospectively investigate the effects of the PINK! Coach in a real-world setting on patients' BMI and physical activity level during acute therapies. such as chemotherapy (CHT) and antihormone therapy (AHT). The PINK! Coach app accompanies breast cancer patients during and after acute therapy to bring about a sustainable lifestyle change. The patients are encouraged to establish a healthy diet, become physically active, and make informed decisions. In this study, real-world data from the app were analyzed over 6 months from baseline to T1 (after 12 weeks) and T2 (after 24 weeks). The patients were under acute therapy or in follow-up care receiving either CHT or AHT. The analyzed data indicate that all patients were able to maintain a consistent BMI over 6 months independent of pre-defined subgroups such as AHT, CHT, or BMI subgroups. In the subgroup of patients undergoing AHT, overweight patients were even able to significantly reduce their BMI by 1-score-point over 6 months (p < 0.01). The subgroup of patients undergoing CHT also showed an significant overall reduction in BMI (p = 0.01). All patients were also able to significantly increase their daily step count as well as their physical activity minutes per day. After the first 12 weeks, 41.4% of patients experienced weight gain, 33.4% were able to maintain their weight, and 24.2% reduced their weight. The presented data provides intriguing insights into the users of the PINK! Coach app and the impact of this usage in regards to BMI and physical activity. At the current time, there are only a few effective concepts for encouraging all breast cancer patients to engage in moderate physical activity and reduce body weight. Often, these concepts apply to selected patient groups. The data presented here include all age groups, tumor stages, and therapies, providing an initial insight into a comprehensive approach. Data over an even longer period would be one way to better contextualize the results in current research.

The enigma of fraud as a unique crime and its resonance for auditing research and practice: unlearned lessons of psychological pathways to fraud

Purpose This study aims to observe people’s decisions to commit fraud. This study is important in the current time because it provides insights into the development of fraudulent intentions within individuals. Design/methodology/approach The information used in this study is derived from semi-structured interviews, conducted with 16 high-ranking officials who are employed in Indonesian local government positions. Findings The study does not have strong evidence to support prior studies assuming that situational factors or social enablers have direct effects on fraud intentions. As suggested, individual factors which are related to moral reasoning (moral judgment and rationalisation) emerge as a consequence of social enablers. The significant role of that moral reasoning is to rationalise any fraud attempt as permissible conduct. As such, when an individual is capable of legitimising his/her fraud attempt into appropriate self-judgement, s/he is more likely to engage in fraudulent behaviours. Practical implications This study offers practical prescriptions in guiding the management to develop strategies to curb fraudulent behaviours. The study suggests that moral cognitive reasoning is found to be a parameter of whether fraud is an acceptable option or not. So, an understanding of observers’ moral reasoning is helpful in predicting the likelihood of fraud within an organisation or in detecting it. Originality/value This study provides a different perspective on the psychological pathway to fraud. It becomes a complement work for the fraud triangle to explain fraudulent behaviours. Specifically, it provides crucial insights into the underlying motivations that lead individuals to accept invitations to engage in fraudulent activities.