Evaluation of different plant derived oils as wood preservatives against subterranean termite Odontotermes obesus

The study assessed the effect of jatropha, linseed, eucalyptus, neem and jojoba oils on protection of three wood species (Acacia nilotica, Dalbergia sissoo and Pinus wallichiana) against termite attack by Odontotermes obesus. Conditioned and pre-weighed blocks of each wood species were vacuum-pressure impregnated with a 15% concentration of the oil-ethanol solutions.. Resistance of treated and untreated wood against termites was tested under laboratory as well as field conditions using choice and no-choice tests. Oil treated wood showed significant reductions in weight loss compared to control treatments. Complete termite mortality was recorded for all oil treatments except eucalyptus oil. Linseed oil showed good results in each treatment in terms of feeding resistance as well as mortality of termites followed by neem, jatropha, jojoba  and eucalyptus oil. The lower weight losses were found in both choice and no-choice field tests for linseed oil treated Dalbergia sissoo while untreated Pinus wallichiana sapwood had the greater weight loss. It was observed that the oil retention was significantly more in sapwood than in heartwoods. The retention of oils justified that wood with high oil retention showed more resistance against the termite except eucalyptus oil treatment of Pinus wallichiana

Non-destructive Detection of an Invasive Drywood Termite, Cryptotermes brevis (Blattodea: Kalotermitidae), in Timber

Reliable drywood termite detection in structures is challenging but is critical for effective management. A microwave-based non-destructive method was evaluated for detecting termite activity. This study evaluated factors affecting the ability of this device to reliably detect Cryptotermes brevis in timber. The device displayed a high probability of successfully detecting C. brevis in naturally infested boards. The system detected termites 97% of the time when used at the highest sensitivity level, while producing few false positives. The number of termites did not affect detection ability, and detectable signals were produced even when a single termite was present. Detection success decreased with both increasing wood density and testing perpendicular to the grain in abrupt transition timber species. The device detected termites to a maximum depth of 45 mm in southern pine (Pinus spp.), but sensitivity declined with increased wood density with the detection limit declining to only 20 mm in denser Tasmanian oak (Eucalyptus spp). The device could only detect termites in samples with densities between 392 to 511 kg/m3 in 38 mm thick radiata pine samples. The results support the ability of microwaves to reliably detect C. brevis in timber.

Challenges of Islamic Education in the Changing World

Islamic education, deeply rooted in the teachings of Islam, has evolved over centuries to cater to the spiritual, moral, intellectual, and societal needs of Muslims. This article explores the historical foundations of Islamic education, its core objectives, and the challenges it faces in the modern era. The challenges include striking a balance between tradition and modernization, addressing gender equity, promoting critical thinking, countering extremism, and integrating technology. The recommendations presented emphasize curricular reform, teacher training, quality assurance, and the incorporation of critical thinking and digital integration. The conclusion underscores the dynamic nature of Islamic education, emphasizing its role in shaping well-rounded individuals who are rooted in their faith while navigating contemporary realities. The continued collaboration among educators, scholars, and community leaders is essential to ensure that Islamic education remains a transformative force for future generations of Muslims. Keywords: Islamic education, Muslim communities, Challenge

Co-optimization of energy and reserve capacity considering renewable energy unit with uncertainty

This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability

Exploring Challenges of Deploying BERT-based NLP Models in Resource-Constrained Embedded Devices

BERT-based neural architectures have established themselves as popular state-of-the-art baselines for many downstream NLP tasks. However, these architectures are data-hungry and consume a lot of memory and energy, often hindering their deployment in many real-time, resource-constrained applications. Existing lighter versions of BERT (eg. DistilBERT and TinyBERT) often cannot perform well on complex NLP tasks. More importantly, from a designer's perspective, it is unclear what is the "right" BERT-based architecture to use for a given NLP task that can strike the optimal trade-off between the resources available and the minimum accuracy desired by the end user. System engineers have to spend a lot of time conducting trial-and-error experiments to find a suitable answer to this question. This paper presents an exploratory study of BERT-based models under different resource constraints and accuracy budgets to derive empirical observations about this resource/accuracy trade-offs. Our findings can help designers to make informed choices among alternative BERT-based architectures for embedded systems, thus saving significant development time and effort

Head and Neck Cancer: Epidemiology and Role of MicroRNAs

Head and neck cancer (HNC) is referred to the cancers of aerodigestive tract covering number of structures viz, oral and nasal cavity, paranasal sinuses, lips, salivary glands, oropharynx, hypopharynx, pharynx, larynx, and local lymph nodes. It is the sixth most common cancer in the world. MicroRNAs (miRNAs) are small single‐stranded noncoding RNAs (ncRNAs) of about 19–25 nucleotides. These miRNAs have been reported to influence number of biological activities, i.e., gene regulation, differentiation, organ formation, cell death, cell proliferation, and stress responses. The first ever study involving miRNAs in HNC was published in 2005. Since then, association between dysregulation of miRNAs and head and neck tumorigenesis has been documented by a number of researchers. This chapter has covered a comprehensive state of the art literature review of the recent studies about the role of miRNAs in HNC including oral squamous cell carcinoma (OSCC) and human nasopharyngeal carcinoma. Despite significant improvement in multimodal treatment, the prognosis of advanced HNC is quite poor. Recent studies are promising regarding the potential role of miRNAs as prognostic indicators. Recently, some miRNAs have been discovered as important diagnostic biomarkers. In fact, miRNAs are found circulated stably in different body fluids, i.e., urine, blood, saliva, as well as in breath. Hence, these miRNAs can be assessed easily with noninvasive methods. miRNAs are the key therapeutic targets in addition to their prognostic and diagnostic value. Use of synthetically designed “miRNAs sponges,” miR mimics (agomiRs), miR antagonists (“antagomiRs”), and miR inhibitors (antimiRNAs oligonucleotides) is an innovative strategy to modulate oncogenic and tumor‐suppressive pathways. Our understanding of miRNAs involvement in HNC is in its infancy. The discovery of miRNAs heralds a complete new paradigm in the understanding of exact molecular pathways involved in HNC development. More detailed studies are required for better understanding and therapeutic targets to treat HNC

Diagnostic Measures in Childhood Tuberculosis: A Short Review

The trends of incidence, morbidity and mortality of tuberculosis in children have always remained unclear because of lack of a definitive diagnostic tool in mostly cases. The diagnosis of tuberculosis in children remains a major challenge as it is seldom confirmed and is mostly based on clinical signs, symptoms and special investigations e. g. TST, chest X-ray and sputum smear microscopy. Sputum smear microscopy is positive in less than 10-15% of children with TB and culture yields are nearly about 30-40%. In low burden countries, the triad of (a) known contact with an infectious source case, (b) a positive tuberculin skin test and (c) a suggestive CXR is usually used to establish a diagnosis of childhood TB. The research on childhood tuberculosis is often neglected due to technical difficulties like slow growth in culture, the difficulty of obtaining specimens and the diverse and relatively nonspecific clinical presentation of tuberculosis in this age group. The complexity in making an exact diagnosis of tuberculosis in children have led to the development of several diagnostic approaches like point scoring systems, diagnostic classifications and diagnostic algorithms. The aim of this study was to review and analyse the different diagnostic approaches to childhood tuberculosis. In this paper, the mostly used techniques like culture methods as well as the non-culture methods including serology, biochemistry and polymerase chain reaction and DNA fingerprinting for the diagnosis of tuberculosis will be discussed. Keywords: Diagnostic measures, Childhood, Tuberculosi

Maternal Demographic Determinants of Low Birth Weight Babies in District Jhang (Pakistan)

The study was conducted to investigate the maternal demographic determinants of low birth weight babies in district Jhang, Pakistan. In the study demographic characteristics of mothers of low birth weight babies were observed. These characteristics were residential area, education level, socio-economic status, age of mothers at the time of birth and pregnancy interval. These all mentioned characteristics were taken as independent variables against the dependent variable, low birth weight of infants. A sample size of 220 mothers who gave birth to a low weight baby was surveyed through purposive sampling technique in government hospitals of District Jhang and its Tehsils. Data was entered and analyzed by using SPSS. One way analysis of variance with mean plots was used to find out the mean differences between maternal demographic characteristics and low birth weight of babies. Rural women, comparatively aged women, early married women and low educated women were found to have extremely low birth weight babies. DOI: 10.5901/mjss.2015.v6n4s1p49