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The desire to increase resource management efficacy in the construction sector is expanding because of measures to reduce costs, boost productivity, and minimize environmental impact. The Internet of Things (IoT) has the potential to alter resource management in the construction sector by delivering real-time data and insights that may assist decision-makers in optimizing resource allocation and usage. Incorporating Internet of Things (IoT) technology into the construction sector will be investigated in this study to discover how resource management is affected. The aim of the study is to identify the essential aspects that promote optimal IoT integration and to investigate how IoT may influence resource management. The relations between variables and their fundamental elements are investigated using structural equation modelling (SEM). In the context of building projects, the study analyses how IoT integration influences resource allocation and utilization, real-time monitoring, and proactive maintenance. The building sector in Malaysia provides concepts on IoT in resource management. Based on this research's outcomes, there is a distinct association between the utilization of IoT technology and effective resource management in the construction sector. IoT adoption is affected by a multiplicity of issues, including data analytics, data security and privacy, integration and interoperability, scalability, and flexibility. This study contributes to addressing considerable gaps in the corpus of information on IoT technology integration in the construction sector. It analyses how IoT may effect resource management, emphasizing how IoT technology may enhance the efficacy of human, mechanical, and material resources.

This study presents a comparative analysis of individual and ensemble learning algorithms (ELAs) to predict the compressive strength (CS) and flexural strength (FS) of plastic concrete. Multilayer perceptron neuron network (MLPNN), Support vector machine (SVM), random forest (RF), and decision tree (DT) were used as base learners, which were then combined with bagging and Adaboost methods to improve the predictive performance. In addition, gene expression programming (GEP) was used to develop computational equations that can be used to predict the CS and FS of plastic concrete. An extensive database containing 357 and 125 data points was obtained from the literature, and the eight most impactful ingredients were used in the model’s development. The accuracy of all models was assessed using several statistical measures, including an error matrix, Akaike information criterion (AIC), K-fold cross-validation, and other external validation equations. Furthermore, sensitivity and SHAP analysis were performed to evaluate input variables' relative significance and impact on the anticipated CS and FS. Based on statistical measures and other validation criteria, GEP outpaces all other individual models, whereas, in ELAs, the SVR ensemble with Adaboost and RF modified with the Bagging technique demonstrated superior performance. SHapley Additive exPlanations (SHAP) and sensitivity analysis reveal that plastic, cement, water, and the age of the specimens have the highest influence, while superplasticizer has the lowest impact, which is consistent with experimental studies. Moreover, GUI and GEP-based simple mathematical correlation can enhance the practical scope of this study and be an effective tool for the pre-mix design of plastic concrete.

Technological advancement encourages the usage of electronic appliances in daily life and makes it possible for users to switch to more advanced devices very easily and at a reasonable cost. As new devices are produced and manufactured at an alarming rate around the world, outdated old devices become e-waste. This research work aims at using a popular machine learning (ML) method known as Multi-expression programming (MEP) to examine the compressive strength (CS) and tensile strength (TS) of E-waste aggregate-based concrete (EWAC). 279 and 105 scientific entries for CS and TS, respectively, were culled from reputable literature. The ten convincing input parameters selected based on multicollinearity analysis (correlation matrix and variance inflation factor) were E-waste coarse aggregate (ECA%), E-waste fine aggregate (EFA%), water-cement ratio (w/c), age of concrete (A in days), fine aggregate water-absorption (WAF%), coarse aggregate water-absorption (WAC%), E-waste aggregate water-absorption (WAE%), E-waste aggregate specific-gravity (SGE), coarse aggregate specific-gravity (SGC), and fine aggregate specific-gravity (SGF). To estimate the functioning of the projected models, root-squared-error (RSE), mean-absolute error (MAE), mean-absolute-percent error (MAPE), Nash-Sutcliffe-efficiency (NSE), root-mean-squared error (RMSE), objective-function (OF), coefficient-of-correlation (R), root-mean-squared-logarithmic error (RMSLE), and performance-index (PI) were used. The R-value for both MEP models exceeds 0.9, showing “excellent” with MAPE values in the testing stage equals to 6.68% and 6.78% for the CS-MEP and TS-MEP models, respectively. While for non-linear regression (NLR) models, the MAPE exceeds 20% and 30%, respectively, making them unsuitable for future prediction. Moreover, the sensitivity analysis carried out to evaluate the MEP equations' consistency with the observed physical phenomena, indicates that for both CS and TS, the w/c, ECA%, and EFA% remain the most sensitive parameters with a sensitivity index greater than 0.60. Due to the accuracy and viability of developed models, they can be used to reduce the time needed for laborious laboratory tests.

Aluminum oxide nanoparticles (Al2O3NPs) and zinc oxide nanoparticles (ZnONPs) have been involved in many industries and they are extensively abundant in many aspects of human life. Consequently, concerns have been raised about their potentially harmful effects. However the toxicities of Al2O3NPs and ZnONPs are well documented, the effect of co-exposure to both nanoparticles remains strictly obscure. Therefore, the present study was undertaken to address this issue. Four groups of male Wistar rats (10 rats each) were used; control, Al2O3NPs treated, ZnONPs treated and Co-treated groups. Rats were orally administered their respective treatment daily for 75 days. The effects of each nanoparticle alone or in combination were assessed at different levels including; hepatic and renal function, structure, and redox status, nuclear DNA fragmentation, hepatic expression of mitochondrial transcription factor A (mtTFA) gene and peroxisome proliferator-activated receptor gamma-coactivator 1α (PGC-1α), systemic inflammation, and hematologic parameters. The results confirmed the hepatorenal toxicities of each nanoparticle used at the level of all parameters with suppression of the hepatic expression of mtTFA and PGC-1α. The co-exposure to both nanoparticles results in synergistic effects. From these results, we can conclude that co-exposure to aluminum oxide nanoparticles and zinc oxide nanoparticles results in more pronounced hepatorenal toxicities and systemic inflammation. Keywords: Aluminum oxide nanoparticles, Zinc oxide nanoparticles, Gene expression, DNA fragmentation, Cytokines and p53, Oxidative stress

The present study describes the growth of the very well-known probiotic bacterium Lactobacillus acidophilus NCFM on different carbohydrates. Furthermore, recombinant production of putative moonlighting proteins elongation factor G and pyruvate kinase from this bacterium is described. For further and detailed interpretation of the data presented here, please see the research article “Mucin- and carbohydrate-stimulated adhesion and subproteome changes of the probiotic bacterium Lactobacillus acidophilus NCFM” (Celebioglu et al., 2017) [1].

Osteoid osteoma (OO) is the most commonly seen benign bone-forming lesion. It can occur anywhere, including the metaphyseal regions of small and large bones. We present 2 cases that underwent an arthroscopic technique for removal of OO of the femoral neck. The diagnosis was confirmed by computed tomography in addition to magnetic resonance imaging. The lesions were accessed arthroscopically and excised by unroofing and curettage. The clinical and radiographic findings are presented, along with the surgical management. The patients improved dramatically postoperatively. OO of the femoral neck should be included in the differential diagnosis of hip pain in young patients. Arthroscopic excision and curettage provide a good choice for management, with low morbidity and rapid recovery.

The challenge of caring for patients with fragility fractures is particularly acute for nursing teams who are in short supply and work with patients following fracture on a 24 h basis, coordinating as well as providing complex care. This paper considers the role of nurses within the orthogeriatric team and highlights the value of effective nursing care in patient outcomes. It explores the nature of nursing for patients with fragility fracture with a focus on the provision of safe and effective care and the coordination of care across the interdisciplinary team. It also highlights the need for specific skills in orthopaedic and geriatric nursing as well as specialist education., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Neurological system assessment is an important skill for the orthopaedic nurse because the nervous system has such an overlap with the musculoskeletal system. Nurses whose scope of practice includes such advanced evaluation, e.g. nurse practitioners, may conduct the examination described here but the information will also be useful for nurses caring for patients who have abnormal neurological assessment findings. Within the context of orthopaedic physical assessment, possible neurological findings are evaluated as they complement the patient's history and the examiner's findings. Specific neurological assessment is integral to diagnosis of some orthopaedic conditions such as carpal tunnel syndrome. In other situations such as crushing injury to the extremities, there is high risk of associated neurological or neurovascular injury. These patients need anticipatory examination and monitoring to prevent complications. This article describes a basic neurological assessment; emphasis is on sensory and motor findings that may overlap with an orthopaedic presentation. The orthopaedic nurse may incorporate all the testing covered here or choose those parts that further elucidate specific diagnostic questions suggested by the patient's history, general evaluation and focused musculoskeletal examination. Abnormal findings help to suggest further testing, consultation with colleagues or referral to a specialist., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The present study was carried out to investigate the relationship between creatinine and calcium concentration in buffalo serum in cases of uterine torsion before rolling, and 1 h and 24 h after calving. The degree, duration and site of uterine torsion, as well as fetus viability, time needed for cervical dilation, and the occurrence of uterine rupture were recorded. A total of 150 pregnant buffaloes suffering from colic and anorexia were brought to our clinic and clinically examined. Of these, 35 buffaloes were diagnosed with uterine torsion (different durations, directions and degrees) and the viability of the foeti and any evidence of uterine rupture were determined using ultrasonography and the serum levels of creatinine and calcium were estimated using calorimetric method. The animals were also examined for incidence of uterine rupture after rolling and calving. The calcium level significantly (P < 0.05) decreased with increasing duration and severity of uterine torsion, however, it was higher in cases where a live fetus was delivered compared with a dead one. Conversely, the creatinine level significantly (P < 0.05) increased with increasing duration and severity of uterine torsion but was lower in cases that delivered a live fetus compared with a dead one. The calcium and creatinine levels returned to approximately normal concentration within 24 h after calving. In conclusion, calcium and creatinine serum concentration have a correlation with duration and severity of uterine torsion. Animals with low levels of calcium (below 8.44 mg/dL) and high levels of creatinine (above 2.25 mg/dL) did not usually respond to rolling or suffer from uterine rupture during calving. The calcium and creatinine levels can be used as indicators for the prognosis of mechanical treatment of uterine torsion in buffaloes., (Copyright © 2012 Elsevier Inc. All rights reserved.)