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Mixed-model and multi-model assembly lines: A systematic literature review on resource management
No full textIn modern dynamic manufacturing context, product personalisation, and the production-line customisation it may require, are crucial sources of competitiveness, making mixed-model and multi-model assembly lines indispensable. The variability resulting from both internal and external factors, along with resource flexibility, plays a critical role in these settings. Nonetheless, systematic analyses of how resources are considered in such environments remain limited, particularly about variability and the interactions among different resource types. Thus, this work conducts a Systematic Literature Review, analysing 63 studies on Mixed-Model Assembly Lines (MMALPs) and Multi-Model Assembly Lines (MuMALPs). The review investigates resource characteristics – such as space, operator skills, costs, or equipment availability – and whether and how variability in operating times or market demand is addressed. The review shows that cost and availability are the most frequently examined resource characteristics, while space remains comparatively underexplored. Line design and line balancing stand out as the primary objectives, typically tackled via integer programming or metaheuristics, whereas machine learning – though less common overall – is more often employed under high-variability conditions. The results offer practical insights for both researchers and practitioners by highlighting the current gaps uncovered by these findings and suggesting avenues that would be particularly valuable to explore in light of the results obtained, thereby underscoring the need for more in-depth research on flexible and reconfigurable lines, as well as broader implementation in real-world applications in MMALPs and MuMALPs
To AI or not to AI? The Hamletian dilemma in Public Organizations’ work processes through a Socio-Technical perspective
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Operational Excellence through drone-based inventory monitoring: a mathematical model proposal
No full textManaging inventories is associated with high costs, which may account for about a third of the total logistics costs. These costs arise from different factors such as the consequences of Inventory Record Inaccuracy (IRI). IRI represents the discrepancies between the physical and digital inventories. These discrepancies generate great labor efforts to solve them, along with write-offs and oversells. This leads to economic and productivity losses. To reduce the impact of IRI, inventories are periodically controlled for audit compliance and correct the physical-digital discrepancies. This is usually done through costly, time-consuming, and labor-intensive approaches. The recent advances in drones have led to their adoption for logistic purposes, including inventory monitoring. Drone-based inventory monitoring entails several benefits compared to conventional approaches such as being automated and quicker. This may result in better accuracy and performance, contributing to operational excellence. Despite this, available literature mainly focuses on the technical and conceptual development of drone-based inventory monitoring systems. Less interest has been devoted to evaluating their economic viability compared to conventional labor-intensive approaches, particularly considering in the analysis reduction in labor and IRI-related issues. To this end, this work aims to develop a mathematical model to compare drone-based inventory monitoring with the labor-intensive conventional technique, considering the presence of write-offs and oversells. The model is tested on two case studies: a manufacturer and a third-party logistics (3PL). Warehouse managers may exploit the model for preliminary assessment of the economic benefits of drone-based inventory monitoring
Sex and Circadian Rhythm Dependent Behavioral Effects of Chronic Stress in Mice and Modulation of Clock Genes in the Prefrontal Cortex
No full textBehavioral stress is a recognized triggering factor for systemic diseases, including psychiatric disorders. The stress response is subjected to circadian regulation and many factors shape the susceptibility to its maladaptive consequences, including the biological sex. Accordingly, circadian dysregulation of the stress response, often occurring in a sexually dimorphic manner, is typically associated with psychiatric disorders. However, the interaction between stress, sex, circadian phases, and behavior is still largely unknown. Here, we used the chronic restraint stress (CRS) model in male and female mice to assess the impact of sex and circadian phases on the behavioral consequences of chronic stress. Animals were stressed either in the light or dark phase, and anxious-/depressive-/anhedonic-like behaviors were assessed. Associated transcriptional changes in clock genes were measured in the prefrontal cortex. A significant interaction of stress, sex, and circadian phase was found in most of the parameters evaluated, with no behavioral response to stress in males stressed in the dark phase, and an exaggerated response in females stressed in the dark phase compared to the light phase. We also found some molecular changes in corticosterone serum levels and expression of clock genes in the prefrontal cortex
Effects of Different Velocity Loss Thresholds in Full Squat With and Without Blood Flow Restriction on Strength Gains, Neuromuscular Adaptations, and Muscle Hypertrophy
No full textThis study aimed to analyze the effects of four full-squat (SQ) training programs that differed in the blood flow condition [free flow (FF) versus restricted (BFR)] and in the velocity loss (VL) induced within the set (20% vs. 40%) on strength gains and muscle hypertrophy. Fifty-two strength-trained men followed an 8-week (16 sessions) SQ training program from 55% to 70% 1-repetition maximum (1RM) (FF20: n = 14; BFR20: n = 13; FF40: n = 12; BFR40: n = 13). The number of sets n = 13 per session and the inter-set recovery periods (2 min) were matched between groups. A 50% arterial occlusion pressure was applied and maintained during the inter-set recovery for BFR groups. The following tests were carried out before and after the training intervention: (1) cross-sectional area of the vastus lateralis (ACSA); (2) countermovement jump; (3) progressive loading SQ test; and (4) fatigue SQ test. No significant BFR × VL × time interactions were observed. For 1RM and strength-derived outcomes from the progressive loading test, significant VL × time interactions (p = 0.01–0.05) in favor of 20% VL groups were found. Regarding jump performance, a significant VL × time interaction (p = 0.02) also favored the 20% VL groups. A BFR × time interaction (p = 0.02) was observed in favor of the BFR condition for ACSA. Prescribing a certain level of effort through VL results in similar jump and strength performance improvements, regardless of blood flow condition, with optimal gains achieved at a moderate VL threshold (20%). Additionally, the BFR condition maximized muscle hypertrophy compared to FF, making it a valuable strategy for muscle growth
Glucagon-like peptide-1 receptor agonist semaglutide through the lens of psychiatry: a systematic review of potential benefits and risks
No full textSemaglutide (SEM), a long-acting glucagon-like peptide-1 receptor agonist, affects neural circuits regulating food intake and satiety, and it provides neuroprotective effects; however, SEM may influence psychological functioning, possibly leading to psychopathological symptoms. This review examines studies on SEM, focusing on its effects on mental health and potential neuropsychiatric side effects. A systematic search in PubMed and Google Scholar was conducted for studies up to March 2025, yielding 342 papers, of which 37 met the eligibility criteria. The selected studies included cohort studies, pharmacovigilance research, open-label studies, and randomized-controlled trials. Findings show that SEM is effective and well-tolerated in various psychiatric populations, with potential benefits in managing binge eating disorder (BED), metabolic disturbances in psychotic disorders, and alcohol use disorder; however, these drugs are also linked to depressive symptoms and suicidal ideation, alongside potential antidepressant effects, though this evidence is preliminary. SEM showed to be of great interest in the treatment of BED, acting not only on weight decrease but also on cognitive symptoms linked to the disease. Similar findings, though preliminary, have been observed for the treatment of alcohol and substance use disorder. The use of SEM in mood disorders, in particular depression, is still controversial
Competenze organizzative e sostenibilità nella leadership scolastica
No full textLa crescente attenzione verso la sostenibilità sollecita una riflessione sui modelli
di governance scolastica e sul ruolo del dirigente, chiamato a integrare
competenze manageriali, sensibilità ecologica e capacità di innovazione
organizzativa. L’introduzione del nuovo sistema di valutazione dirigenziale del
2025 si inserisce in questo scenario, aprendo prospettive di ridefinizione delle
competenze richieste. Le cosiddette green competences possono costituire un
elemento di trasformazione, incidendo sia sulla gestione delle risorse materiali ed
energetiche, sia sulla progettazione educativa partecipata e sulla formazione in
servizio dei docenti. Un approccio orientato alla sostenibilità sembra inoltre favorire percorsi didattici innovativi, capaci di sviluppare negli studenti consapevolezza critica e competenze trasversali in materia ambientale
Measurement of Spatio-Temporal Gait Parameters through a Wearable Device for the Evaluation of the Activity Level of Athletes
No full textWearable technologies support athletes and coaches by providing objective data to enhance performance, prevent injuries, and ptimize training. Magnetic and Inertial Measurement Units (MIMUs) measure spatio-temporal parameters, enabling the analysis of gait events outside laboratory settings. Recently, manufacturers have introduced single-point inertial sensors worn on the upper torso, gaining popularity in sports. Integrating machine learning (ML) algorithms has further revolutionized sport performance analysis. This paper presents the development and validation of a measurement method using a MIMU sensor on the upper torso to estimate gait parameters, particularly stride duration during walking and running. Data from the MIMU device is compared with that from sensorized insoles, and a metrological characterization assesses the device’s accuracy and reliability. Furthermore, the study developed ML models to classify the athlete’s activity level at three intensities: resting, walking (0 < speed ≤ 5 km/h), and running (speed > 5 km/h). Results show that the wearable sensor is accurate (bias: -0.002 s and almost 0 s for left and right feet, respectively) and precise (standard deviation of residuals: 0.07 s and 0.05 s for left
and right feet) in estimating stride duration. Bland-Altman plots confirm agreement with the reference device, and Pearson’s correlation coefficients indicate strong linear correlation (0.94 and 0.97 for left and right feet). The ML-based classifier achieves an overall accuracy of 78%. Thus, the MIMU sensor placed at the upper torso effectively identifies stride duration, and the combination with the ML classifier advances wearable activity monitoring.These findings highlight the practical applicability of the proposed
approach for continuous, non-invasive monitoring of athletes’ training load and movement patterns, offering a portable solution for performance optimization and injury prevention