A smart home is a technologically equipped residence that proactively observes its residents and offers various services. It has emerged as a potential solution to support independent living for people with disabilities and older adults, while also relieving the burdens on family caregivers and healthcare providers. A fundamental aspect of smart homes is their capability to monitor daily living activities and ensure residents' safety by detecting changes in their routines. With the advancements in technology, modern smart homes are furnished with numerous low-power sensors, radios, and embedded processors that collaboratively process data to assess the home's state and the behaviors of its occupants. This article delves into the sensor technology employed in smart homes, with a particular focus on direct environment sensing and infrastructure-mediated sensing. It explores the strengths and limitations of different sensor technologies and discusses the challenges and opportunities from technical, and ethical perspectives.

AbstractIntroduction

The endemic species Nepeta cyrenaica Quézel & Zaffran, native to northeastern Libya, is valued as an important honey-bearing plant.

Objectives

This study was aimed to examine the micromorphology, phytochemistry, and bioactivity of in vitro-propagated N. cyrenaica for the first time.

Materials and Methods

The leaf indumentum was examined using light and scanning electron microscopy and further characterised for histochemistry. The chemical composition of essential oil (EO) was performed using GC-MS analysis, while dichloromethane (DCM), methanol (ME), ethanol (ET), and aqueous (AQ) extracts were analysed using qualitative and quantitative LC/MS analyses. The antioxidant activities of EO and extracts were assessed using three parallel assays, while enzyme-inhibiting effects were evaluated against four enzymes.

Results

The leaves bear various types of glandular trichomes, with lipophilic secretion predominating. The main EO component of EO was 1,8-cineole. A considerable number of phenolics and iridoids were tentatively identified in the ME extract. Quantitative LC/MS analysis confirmed that ferulic acid, rosmarinic acid, and epigallocatechin gallate were present in the highest amount in the extracts, in which three iridoids were also quantified. Although the ME extract contained the highest amount of polyphenolics and iridoids, the DCM extract showed the best overall biological potential. Additionally, EO exerted the strongest acetylcholinesterase and tyrosinase inhibition.

Conclusion

This study demonstrated that the endemic N. cyrenaica can be efficiently grown under in vitro conditions, where it develops various glandular trichomes that are thought to secrete and/or accumulate bioactive compounds with valuable medicinal potential.

The study area is the city of Zintan, in northwestern Libya, which has grown over the past

30 years. Its current population is roughly 30,000. Although the city is in part commercial, most

of the population engages in agriculture and primarily grows cereal crops (wheat and barley). The

demand of the growing city for agricultural products has increased, intensifying the use of fertilizers,

pesticides, and insecticides. Consequently, concentrations of potentially toxic elements (PTE) in

the soil have increased. To assess the soil quality (to provide a snapshot of the condition of the

soil), systematic sampling was undertaken across a grid of about 2 km  2 km. The main objective

was to determine the chemical and mineral composition of the area of interest, keeping in mind

the geological footprint of the terrain. The geologic framework itself is not conducive to elevated

concentrations of elements like U, Th, Mo, As, Hg, Pb, and Cr. Therefore, metal concentrations

greater than the amounts in the Earth’s crust are most likely of anthropogenic origin. A total of

143 samples were collected and chemical analyses were performed using a Thermo Fisher Scientific

Niton XL3t GOLDD+ XRF analyzer for the following elements: Mo, Zr, Sr, U, Rb, Th, Pb, Au, Se,

As, Hg, Zn, W, Cu, Ni, Co, Fe, Mn, Cr, V, Ti, Sc, Ca, K, S, Ba, Cs, Te, Sb, Sn, Cd, Pd, and Ag. This

paper provides examples of elevated concentrations, potentially harmful to the environment, such as

those of the following: sulfur of unknown origin (two to three times higher than the Earth’s crust

average); arsenic, given that there are no related natural phenomena (all the samples measured

displayed concentrations higher than those found in the Earth’s crust); mercury (concentrations much

higher than permissible levels); cesium (additional investigations required to determine the origin);

molybdenum; and uranium likely resulting from the use of superphosphates (concentrations nearly

always significantly higher than those in the Earth’s crust).

Purpose

The study aims to propose a predictive model that combines personality and demographic factors to predict student academic performance (SAP). This research study works on understanding, enhancing and applying techniques to enhance the prediction of SAP.

Design/methodology/approach

The authors gathered information from 305 university students from Al-Zintan University Libya. The study uses a survey questionnaire to collect data on essential variables. The purpose of the questionnaire is to discover variables that affect students' academic performance. The survey questionnaire has 44 closed questions with Likert scale designs that were distributed to a variety of college students at the start of the first semester of 2022. It includes questions about demographics, personality, employment and institutional aspects. The authors proposed a predictive model to identify the main fundamental components, consisting of one dependent variable (SAP) and five independent constructs. The suggested model is tested using partial least squares (PLS) and structural equation modeling (SEM), which perform better than covariance-based structural equation modeling (CB-SEM). PLS-SEM performs well with smaller sample sizes, even for complicated models.

Findings

The study results show that the proposed model accurately predicted the student's academic performance. The personality trait variables are a key factor that determines the actual student's academic performance. The student's academic performance is significantly impacted by each variable in the personality trait variables as well.

Originality/value

The process of validating research was done empirically through the accuracy and efficiency of model performance. The study differs from previous studies in that it accumulated a wide range of factors from different dimensions, including student demographics and personality trait factors. The authors developed a structural equation model to predict students' academic performance.

This research aims to develop a computer model of a hybrid renewable energy system that can operate independently for a faculty of engineering of Karabuk university, located in Turkey. The hybrid system consists of several components, such as Photovoltaic (PV) panels, wind turbines, diesel generator, and battery storage system as a backup. The primary purpose of this system is to meet the energy needs of a university building. Different combinations of the hybrid system were examined using HOMER software to determine the most cost-efficient solution based on the net present cost. Following the analysis of multiple combinations, the optimal hybrid system was determined, which consists of a 500kW PV system, wind turbines with a total capacity of 7.5 MW, and a 327Ah, 15.7 kw/h battery storage system, diesel generator of 2000 kw. The overall cost of the system $693,000,000, the project lifespan is 25 years.