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The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data.

This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field.

The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement.

In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology.

This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance.

This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.

Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.

Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.

Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.

Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

This study aims to analyze the connection between servant leadership and the promotive and prohibitive voice behavior of employees. In addition, this study explained how servant leadership affects promotive and prohibitive voice behavior through meaning.

For this study, data were collected from employee–manager dyads employed in the service sector. Each of the waves was initiated two months after the first wave. Finally, 286 useful responses were obtained. The collected data was analyzed through covariance-based structural equation modeling.

Servant leadership is related with meaning, promotive voice behavior and prohibitive voice behavior. Meaning is found to mediate the relationship between servant leadership and the two facets of voice behavior.

To the best of the authors’ knowledge, this study is the first to explore the mediating role of meaning relating servant leadership to promotive and prohibitive voice behavior.

The purpose of this study is to explore the impact of EL style on key variables in health-care settings. Very few studies investigate the impact and outcomes of EL on health-care organizations. Synthesis of evidence will assist health-care leaders in making informed decisions about the outcomes they can expect from practicing EL.

Arksey and O’Malley’s five-stage framework is used for conducting the scoping review. The databases include Scopus, Emerald Insight and Web of Science.

A total of 22 studies were finally considered for scoping review. The data are presented in terms of years, sampling techniques, sample size, data collection methods, and the directional relationship of the variables with EL.

Managers should be trained in EL style as it promotes the sustainability of the environment and organizations. Furthermore, EL should be promoted in health-care organizations as it improves employee resilience and voicing behavior and reduces instances of adverse events and medication errors, thus making the hospital a better and safer place.

This is one of the studies investigating the EL implications for health-care managers.

Inconel 718 is difficult to machine due to its high toughness and study hardenability. Though the use of cutting fluids alleviates the problem, it is not sustainable. So, supply of a small quantity of specialized coolant to the machining zone or use of a solid lubricant is a possible solution. The purpose of the present work is to improve machinability of Inconel718 using graphene nanoplatelets.

In the present study, graphene is used in the machining of Inconel 718 alloy. Graphene is applied in the following two forms: as a solid lubricant and as an inclusion in cutting fluid. Graphene-based self-lubricating tool and graphene added nanofluids are prepared and applied to turning of Inconel 718 at varying cutting velocities. Performances are compared by measuring cutting forces, cutting temperature, tool wear and surface roughness.

Graphene, in both forms, showed superior performance compared to dry machining. In total, 0.3 Wt.% graphene added nanofluids showed the lowest cutting tool temperature and flank wear with 44.95% and 83.37% decrease, respectively, compared to dry machining and lowest surface roughness, 0.424 times compared to dry machining at 87 m/min.

Graphene could improve the machinability of Inconel 718 when used in tools as a solid lubricant and also when used as a dispersant in cutting fluid. Graphene used as a dispersant in cutting fluid is found to be more effective.

Plant-based diets have been related to decreasing morbidity and mortality of many non-communicable diseases. The purpose of this study was to investigate the relationship between plant-based diets and lipid profiles and anthropometric indices.

This cross-sectional study was performed on 236 men and women selected from Shiraz health-care centers. This study used a 168-item food frequency questionnaire to calculate plant-based diet index (PDI), healthy plant-based diet index (hPDI) and unhealthy plant-based diet index (uPDI). Total cholesterol, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol and triglycerides were measured. Furthermore, body mass index, a body shape index and conicity index (CI) were calculated after measuring weight, height and waist circumference.

Higher score of PDI was significantly related to higher triglycerides level (OR = 2.16; 95% CI: 1.04, 4.48; P = 0.03). In the fully adjusted model, there was a significant association between ABSI and hPDI (OR = 4.88; 95% CI: 1.17, 20.24; P = 0.03). A significant inverse association was observed between uPDI and high-density lipoprotein (HDL) (OR = 0.45; 95% CI = 0.21, 0.98; P = 0.03). Also, this study found a decreasing, but insignificant trend in relation of ABSI (OR = 0.72; 95% CI = 0.22, 2.34) and CI (OR = 0.41; 95% CI = 0.06, 0.56) with PDI.

Further studies are needed to explore the association of PDI with anthropometric indices and lipid profile and also to assess the potential causality of the observed associations. Plant-based diets according to their contents could affect triglycerides, HDL and anthropometric properties.

Hence, dietitians should consider the findings of this study such as the inverse effect of unhealthy plant-based diets on HDL and the relation between healthy plant-based diets and WC and abdominal obesity.

This study showed that adherence to a plant-based diet was related to higher triglycerides levels. Also, uPDI was inversely associated with HDL level. Furthermore, participants who adhered more to a healthy plant-based diet had higher abdominal adiposity.

An adaptive slicing algorithm that can vary the layer thickness in relation to local geometry is presented. The algorithm is based on three fundamental concepts: choice of criterion for accommodating complexities of surfaces, recognition of key characteristics and features of the object, and development of a grouping methodology for facets used to represent the object. Four criteria, cusp height, maximum deviation, chord length and volumetric error per unit length, are identified and the layer thickness is adjusted such that one of the four is met. Next, key characteristics of the object, such as horizontal and vertical surfaces, pointed edges and ends, are identified based on the local changes in surface complexity, and slice based feature recognition is introduced to identify the nature of a feature, protrusion or depression, by studying the slice data. Note that the present approach uses information only from the tessellated model, and thus is different from current implementations. Finally, the concept of grouping of the facets based on their vertex coordinates is developed to minimize the number of searches for possible intersection of the facets with a slice plane. The slicing algorithm is interfaced with adaptive laminated machining and the stereolithography process through a CNC post processor and a hatching algorithm respectively. A comparison of the estimated surface quality and build time indicates that adaptive slicing produces superior parts in a shorter build time. The implementation of this work is protected under US Patent laws (Patent # 5,596,504, January 1997).

This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.

Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.

The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.

An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.

This paper aims to study the effects of a diet supplemented with flaxseeds on dyslipidemia, oxidative stress and proinflammatory cytokines, in rats consuming a high-cholesterol diet.

Male Wistar rats (n = 30) weighing (250 ± 5 g) of which 10 were control and 20 were rendered hypercholesterolemic (HC) by feeding a diet enriched with 1% of cholesterol, for 15 days. After this phase, rats were divided into two groups; hypercholesterolemic group (HC) (n = 10), fed 20% casein diet enriched with 1% cholesterol; and hypercholesterolemic rats fed the same diet (n = 10), but additionally supplemented with flaxseeds (Linum usitatissimum) (Lu) powder, i.e. HC-Lu. Animals of the control group (n = 10) were fed the casein diet. All the animals were maintained on the respective diets for four weeks.

This study showed that in HC-Lu as compared to HC group, plasma total cholesterol, triacylglycerols and non-HDL cholesterol concentrations were respectively 2.4-, 1.5- and 3-fold lower. Also, the lipid peroxidation was reduced in red blood cells, organs (liver, heart and aorta) and lipoproteins (HDL2, HDL3 and VDL-LDL). A higher superoxide dismutase activity was observed in liver (+61%), heart (+62%) and aorta (+59%), whereas plasma proinflammatory cytokine (IL-1beta and IL-6) levels were decreased.

These results suggest that flaxseeds help to reduce hypercholesterolemia, oxidative stress and inflammation in patients with hypercholesterolemia.