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\"The citrus industry is one of the world's most important fruit production industries, but global climate change, pests, diseases, and improper handling are affecting plant yields. CitrusProduction: Technological Advancements and Adaptation to Changing Climate presents information on advancements in the citrus industry examining various aspects of citrus from its production to harvest. It looks at the challenges and approaches in stress tolerance improvements, increasing citrus crop productivity, and reducing postharvest losses. The book details taxonomy, genetic diversity, and metabolic and molecular responses in citrus crops, as well as abiotic and biotic stresses affecting citrus production. Featuring numerous full-color illustrations throughout, this book poses new harvesting techniques along with postharvest physiology of citrus fruits, devising strategies to prevent crop losses. Citrus Production: Technological Advancements and Adaptation to Changing Climate is an essential resource for researchers, academicians, and scientists looking to expand their knowledge of citrus, particularly horticulturists, food scientists, and botanists\"-- Provided by publisher.

Internet of Things (IoT) technology is increasingly pervasive in all aspects of our life and its usage is anticipated to significantly increase in future Smart Cities to support their myriad of revolutionary applications. This paper introduces a new architecture that can support several IoT-enabled smart home use cases, with a specified level of security and privacy preservation. The security threats that may target such an architecture are highlighted along with the cryptographic algorithms that can prevent them. An experimental study is performed to provide more insights about the suitability of several lightweight cryptographic algorithms for use in securing the constrained IoT devices used in the proposed architecture. The obtained results showed that many modern lightweight symmetric cryptography algorithms, as CLEFIA and TRIVIUM, are optimized for hardware implementations and can consume up to 10 times more energy than the legacy techniques when they are implemented in software. Moreover, the experiments results highlight that CLEFIA significantly outperforms TRIVIUM under all of the investigated test cases, and the latter performs 100 times worse than the legacy cryptographic algorithms tested.

In this paper, we present four categories of covering-based intuitionistic hesitant fuzzy rough set (CIHFRS) models using intuitionistic hesitant fuzzy β-neighborhoods (IHF β-neighborhoods) and intuitionistic hesitant fuzzy complementary β-neighborhoods (IHFC β-neighborhoods. Through theoretical analysis of covering-based IHFRS models, we propose the intuitionistic hesitant fuzzy TOPSIS (IHF-TOPSIS) technique for order of preference by similarity to an ideal solution, addressing multicriteria decision-making (MCDM) challenges concerning the assessment of IHF data. A compelling example aptly showcases the suggested approach. Furthermore, we address MCDM problems regarding the assessment of IHF information based on CIHFRS models. Through comparison and analysis, it is evident that addressing MCDM problems by assessing IHF data using CIHFRS models proves more effective than utilizing intuitionistic fuzzy data with CIFRS models or hesitant fuzzy information with CHFRS models. IHFS emerges as a unique and superior tool for addressing real-world challenges. Additionally, covering-based rough sets (CRSs) have been successfully applied to decision problems due to their robust capability in handling unclear data. In this study, by combining CRSs with IHFS, four classes of CIFRS versions are established using IHF β-neighborhoods and IHFC β-neighborhoods. A corresponding approximation axiomatic system is developed for each. The roughness and precision degrees of CBIHFRS models are specifically talked about. The relationship among these four types of IHFRS versions and existing related versions is presented based on theoretical investigations. A method for MCDM problems through IHF information, namely, IHF-TOPSIS, is introduced to further demonstrate its effectiveness and applicability. By conducting a comparative study, the effectiveness of the suggested approach is evaluated.

The article aims to evaluate the post-high temperature exposure residual response of self-compacting concrete (SCC) in the presence of continuous internal voids. The influence of high temperatures on the mechanical behavior, especially compressive strength, have been reported in literature, while its interaction with the influence of void content, geometry, and distribution has not been rigorously characterized. This study presents an experimental program that investigates the absolute compressive strength response of SCC containing voids of varying dimensions across multiple mix grades (M30, M40, and M50) subjected to progressive heating levels of 100, 200, 300, 400, and 600 °C. In addition to solid reference specimens, three groups of specimens incorporated distinct void geometries VD1, VD2, and VD3 with dimensions of 50 × 50 × 150 mm, 75 × 75 × 150 mm, and 100 × 100 × 150 mm were selected to represent three levels of void ratios and to evaluate their impact on the absolute response of the specimens. The test results showed that for solid SCC specimens, compressive strength exhibited a temperature-dependent evolution, increasing with thermal exposure up to 300 °C, where the M50 grade attained 78.72 MPa, approximately 17.23% higher than its ambient value. Beyond this threshold, strength declined markedly, with reductions of 20–40% observed at 600 °C across all mix grades (M30-M50), reflecting thermally induced microstructural degradation. The presence of voids exerted a pronounced effect on absolute performance at elevated temperatures: at 600 °C, M50 specimens exhibited absolute strengths of 38.07 MPa (VD1), 18.41 MPa (VD2), and 10.84 MPa (VD3), representing an overall loss exceeding 80% relative to the room-temperature solid specimen.

Objective: The present study aimed to assess the thyroid outcomes six-months after radioactive Iodine-131 therapy (RIT) among hyperthyroid patients and identify the factors associated with them. Methods: This retrospective observational study was conducted at the department of Nuclear Medicine and Molecular Imaging, Northwest General Hospital & Research Centre during 2013 to 2019. For the study purpose, the thyroid outcomes of 153 hyperthyroid patients were studied retrospectively for six months after RIT. The data was obtained from the medical records. Patient baseline characteristics, clinical features, laboratory investigations, results of thyroid imaging, and therapeutic investigations were acquired and recorded in a structured questionnaire. Results: Out of the 153 screened records of hyperthyroid patients, 19.6% became euthyroid, 9.2% remained hyperthyroid, and 25.5% developed hypothyroidism after six months of RIT. The observed remission rate by the end of six months was 80.95%. Three months post-RIT, gender and RAI doses had a significant effect on thyroid function. The frequency of hypothyroidism was higher among those treated with an RAI dose of ≤ 20 mCi (83.0%) than those treated with a higher dose > 20 mCi (17%). Moreover, most patients receiving > 20 mCi radioiodine became euthyroid (64.5%). Similar outcomes were observed after six months of the therapy, except gender was replaced by etiologies of hyperthyroidism (p=0.009). Conclusion: Radioactive iodine (131-I) therapy is effective for the treatment of hyperthyroidism. However, the appropriate dose is still debatable, as there was a high incidence of hypothyroidism post-therapy. doi: https://doi.org/10.12669/pjms.39.6.7567 How to cite this: Khan MSA, Hussain A, Ahmad S, Shah MH. Outcomes of Radioactive Iodine (131I) Therapy among Hyperthyroid patients. Pak J Med Sci. 2023;39(6):1685-1689. doi: https://doi.org/10.12669/pjms.39.6.7567 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Ultra-high performance (UHP) concrete is a special type of fibrous cementitious composite that is characterized by high strength and superior ductility, toughness, and durability. This research aimed to investigate the resistance of ultra-high performance fiber-reinforced concrete (UHPFRC) against repeated impacts. An adjusted repeated drop mass impact test was adopted to evaluate the impact performance of 72 UHPFRC disc specimens. The specimens were divided into six mixtures each of 12 discs. The only difference between the mixtures was the types of fibers used, while all other mixture components were the same. Three types of fibers were used: 6 mm micro-steel, 15 mm micro-steel, and polypropylene. All mixtures included 2.5% volumetric content of fibers, however with different combinations of the three fiber types. The test results showed that the mixtures with the 15 mm micro-steel fiber absorbed a higher number of impact blows until cracking compared to other mixtures. The mixture with pure 2.5% of 15 mm micro-steel fiber exhibited the highest impact resistance, with percentage increases over the other mixtures ranging from 25 to 140%. In addition, the Weibull distribution was used to investigate the cracking impact resistance of UHP at different levels of reliability.

Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.

The current work is devoted to bring out a detail analysis including qualitative and semi-analytical study of Hepatitis B model under the Caputo- Fabrizio fractional derivative (CFFD). For the required results, fixed point theory is used to establish the conditions for existence and uniqueness of solution to the considered model. On the other hand, for semi analytical solutions, we use decomposition method of Adomian coupled with integral transform of Laplace. Moreover, the concerned solutions are presented via graphs to analyze the dynamics of different compartments of the model.

Parkinson’s disease is a serious neurological impair-ment which adversely affects the quality of life in individuals. While there currently does not exist any cure for this disease, it is well known that early diagnosis can be used to improve the quality of life of affected individuals through various types of therapy. Speech based screening of Parkinson’s disease is an active area of research intending to offer a non-invasive and passive tool for clinicians to monitor changes in voice that arise due to Parkinson’s disease. Whereas traditional methods for speech based identification rely on domain-knowledge based hand-crafted features, in this paper, we investigate the efficacy of and propose the deep acoustic embeddings for identification of Parkinsonian speech. To this end, we conduct several experiments to benchmark deep acoustic embeddings against handcrafted features for differentiating between speech from individuals with Parkinson’s disease and those who are healthy. We report that deep acoustic embeddings consistently perform better than domain-knowledge features. We also report on the usefulness of decision-level fusion for improving the classification performance of a model trained on these embeddings.

Wireless body area networks are being widely used due to the increase in the use of wireless networks and various electrical devices. A Wearable Patch antenna is used for enhancement of various applications for WBAN. In this paper, a low profile wearable microstrip patch antenna is designed and suggested for constant observation of human vital signs such as blood pressure, pulse rate and body temperature using wireless body area network (WBAN) technology. The operating frequency of the antenna is taken as 2.45 GHz which lies in industrial, scientific and medical (ISM) frequency band. Polyester textile fabric with a relative permittivity of 1.44 and thickness of 2.85 mm is used as a substrate material. The proposed antenna is designed to achieve better return loss, VSWR, gain and low value of specific absorption rate (SAR) as compare to other existing wearable antenna. The achieved antenna return loss at 2.45 GHz is about -10.52 dB and gain of 7.81 dB. The VSWR value achieved at 2.45 GHz is 1.84, which is good in terms of good impedance matching. Other antenna field parameters like 2D and 3D gain, radiation pattern, and SAR value have been calculated. High-Frequency Structure Simulator (HFSS) is used to design and simulate the proposed antenna.