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In this study, a novel microwave-water cooling-assisted mechanical rock breakage method was proposed to address the issues of severe tool wear at elevated temperatures, poor rock microwave absorption, and excessive microwave energy consumption. The investigation object was sandstone, which was irradiated at 4 kW microwave power for 60 s, 180 s, 300 s, and 420 s, followed by air and water cooling. Subsequently, uniaxial compression, Brazilian tension, and fracture tests were conducted. The evolution of damage in sandstone was measured using active and passive nondestructive acoustic detection methods. The roughness of the fracture surfaces of the specimens was quantified using the box-counting method. The damage mechanisms of microwave heating and water cooling on sandstone were discussed from both macroscopic and microscopic perspectives. The experimental results demonstrated that as the duration of the microwave irradiation increased, the P-wave velocity, uniaxial compressive strength (UCS), elastic modulus (E), tensile strength, and fracture toughness of sandstone exhibited various degrees of weakness and were further weakened by water cooling. Furthermore, an increase in the microwave irradiation duration enhanced the damaging effect of water cooling. The P-wave velocity of the sandstone was proportional to the mechanical parameters. Microwave heating and water cooling weakened the brittleness of the sandstone to a certain extent. The fractal dimension of the fracture surface was correlated with the duration of microwave heating, and the water-cooling treatment resulted in a rougher fracture surface. An analysis of the instantaneous cutting rate revealed that water cooling can substantially enhance the efficiency of microwave-assisted rock breakage.

Abstract Central to the development of universal learning systems is the ability to solve multiple tasks without retraining from scratch when new data arrives. This is crucial because each task requires significant training time. Addressing the problem of continual learning necessitates various methods due to the complexity of the problem space. This problem space includes: (1) addressing catastrophic forgetting to retain previously learned tasks, (2) demonstrating positive forward transfer for faster learning, (3) ensuring scalability across numerous tasks, and (4) facilitating learning without requiring task labels, even in the absence of clear task boundaries. In this paper, the Task-Agnostic Policy Distillation (TAPD) framework is introduced. This framework alleviates problems (1)–(4) by incorporating a task-agnostic phase, where an agent explores its environment without any external goal and maximizes only its intrinsic motivation. The knowledge gained during this phase is later distilled for further exploration. Therefore, the agent acts in a self-supervised manner by systematically seeking novel states. By utilizing task-agnostic distilled knowledge, the agent can solve downstream tasks more efficiently, leading to improved sample efficiency. Our code is available at the repository: https://github.com/wabbajack1/TAPD .

Study Design Retrospective cohort study. Purpose To determine the incidence and success of three-column osteotomies (3COs) performed in primary and revision adult spine deformity (ASD) corrective surgeries. Overview of Literature 3COs are often required to correct severe, rigid ASD presentations. However, controversy remains on the utility of 3COs, particularly in primary surgery. Methods Patients ASD having 2-year data were included and divided into 3CO and non-3CO (remaining ASD cohort) groups. For the subanalysis, patients were stratified based on whether they were undergoing primary (P3CO) or revision (R3CO) surgery. Multivariate analysis controlling for age, Charlson comorbidity index, body mass index, baseline pelvic incidence–lumbar lordosis, and fused levels evaluated the complication rates and radiographic and patient-reported outcomes between the 3CO and non-3CO groups. Results Of the 436 patients included, 20% had 3COs. 3COs were performed in 16% of P3COs and 51% of R3COs. Both 3CO groups had greater severity in deformity and disability at baseline; however, only R3COs improved more than non-3COs. Despite greater segmental correction, 3COs had much lower rates of aligning in the lumbar distribution index (LDI), higher mechanical complications, and more reoperations when performed below L3. When comparing P3COs and R3COs, baseline lumbopelvic and global alignments, as well as disability, were different. The R3CO group had greater clinical improvements and global correction (both p

Sustainability and environmental protection are reshaping industries, including construction, where sustainability plays a crucial role in its influence on global resource consumption and waste management. The current study has developed a reusable cement material by photo-chemical surface modification of marble powder, achieved by reacting glycidyl methacrylate with carbonate functionality. This innovative modified marble powder boosts the reusability of construction materials, unlocking new possibilities for sustainable building practices. By transforming waste into valuable resources, we minimize raw material consumption, foster recycling, and advance circular economy principles in the construction industry. The difference in unmodified (22.9 nm) and modified (23–27 nm) marble powder particle sizes was used to assess the effectiveness of surface modification technique. Compared to non-reusable counterpart (20.34 MPa), the reusability has come at the cost of a decrease in compression stress (11.30 MPa, 10.89 MPa, and 10.57 MPa). Overall, photochemically modified marble powder for its reusability is a groundbreaking approach that offers substantial environmental, economical, and technical advantages, making it an appealing choice for the construction industry.

The memories of the past, called nostalgia in terms of literature, can be the primary motivation for human life. A lot has been written about it in the literature; nostalgia also has profound effects on Urdu literature. Those who directly experienced the division of the subcontinent have made it the subject of their writings. There are many effects of nostalgia in the novel “Aagy Samandar Hai” How the partition destroyed the houses and then how the people tried to rebuild them, what mental agonies they went through, how many psychological and physical difficulties they faced in leaving the land of their ancestors, and What is the tragedy of memory. All of this has been tried to be considered in this article.

Exercise is essential for a healthy lifestyle, thus it is important to consider how to keep proper posture when performing arm exercises at home. This work uses wrist-worn bands with the MPU6050 sensor to address these issues, which collects motion data using acceleration measurements. The individuals in the dataset are completing a variety of activities at varying ranges of motion. Machine learning-based classification methods are then applied after the pre-processing and feature extraction of the gathered data. An App prototype integrated with a WiFi module and Cloud infrastructure is created to enable real-time data collecting and storage. The Arduino IDE is used to send the collected data to the ThingSpeak platform, where it is subsequently sent to MATLAB for additional analysis. The studied data is then returned to ThingSpeak, where the program displays the findings. This approach reduces the risk of injuries caused by bad posture by enabling people to continue regular workouts at home without requiring a personal trainer or a particular environment. The findings of this work shed important light on the performance of Boosted Trees, Quadratic SVM, Subspace KNN, and Fine KNN algorithms for arm exercises employing a wrist-worn band with an MPU6050 sensor. The Fine KNN has the highest accuracy of 91.3% among all implemented algorithms.

The stability analysis of a deep buried tunnel subjected to dynamic disturbance is an important issue. In this study, the transient response has been obtained by establishing a water-rich tunnel model considering excavation damage zone (EDZ). Based on Biot’s two-phase dynamic theory and wave function expansion method, the analytical solution of dynamic response around the water-rich tunnel containing EDZ subjected to P wave is derived. Moreover, Fourier transform and Duhamel’s integral technique is introduced to calculate the transient response, and the equivalent blasting curve is adopted to input excitation function. The dimensionless parameters thickness N and shear modulus ratio μ∼ are defined to characterize the degree of damage in the surrounding rock, investigating the influencing factors, such as the parameters and the incident source frequencies. The results indicate that the dynamic stress concentration factor (DSCF) gradually decreases as the dimensionless parameters increase. Additionally, it is observed that the DSCF is more sensitive to changes in the thickness parameter N. Finally, the influence of the waveform parameters has been taken into account in the analysis of transient response, and the stress state and transfer process in each time stage of the EDZ are analyzed. This study establishes a theoretical foundation for comprehending the mechanical behavior and support design considerations associated with a deep-buried water-rich tunnel containing EDZ.

Study Design Retrospective review of Kids’ Inpatient Database (KID). Purpose: Identify the risks and complications associated with surgery in adolescents diagnosed with Chiari and scoliosis. Overview of Literature Scoliosis is frequently associated with Chiari malformation (CM). More specifically, reports have been made about this association with CM type I in the absence of syrinx status. Methods: The KID was used to identify all pediatric inpatients with CM and scoliosis. The patients were stratified into three groups: those with concomitant CM and scoliosis (CMS group), those with only CM (CM group), and those with only scoliosis (Sc group). Multivariate logistic regressions were used to assess association between surgical characteristics and diagnosis with complication rate. Results: A total of 90,707 spine patients were identified (61.8% Sc, 37% CM, 1.2% CMS). Sc patients were older, had a higher invasiveness score, and higher Charlson comorbidity index (all p

This paper presents a novel robust output feedback control that simultaneously performs both stabilization and trajectory tracking for a class of underactuated nonholonomic systems despite model uncertainties, external disturbance, and the absence of velocity measurement. To solve this challenging problem, a generalized normal form has been successfully created by employing an input–output feedback linearization approach and a change in coordinates (diffeomorphism). This research mainly focuses on the stabilization problem of nonholonomic systems that can be transformed to a normal form and pose several challenges, including (i) a nontriangular normal form, (ii) the internal dynamics of the system are non-affine in control, and (iii) the zero dynamics of the system are not in minimum phase. The proposed scheme utilizes combined backstepping and sliding mode control (SMC) techniques. Furthermore, the full-order high gain observer (HGO) has been developed to estimate the derivative of output functions and internal dynamics. Then, full-order HGO and the backstepping SMC have been integrated to synthesize a robust output feedback controller. A differential-drive type (2,0) the wheeled mobile robot has been considered as an example to support the theoretical results. The simulation results demonstrate that the backstepping SMC exhibits robustness against bounded uncertainties.

Owing to the increasing threat to environment due to the emission of greenhouse gases from cement industry globally, various promising solutions has been introduced in the past decades. The development of geoplymer concrete (GPC) is one of the contribution by the researches towards ecofriendly and sustainable construction. In this research, geopolymer concrete (GPC) is optimized by adding fixed amount of fly Ash (FA) and alkali activator to fine aggregate ratio as 0.5 with varying Molarity from 12 M to 16 M and Na2SiO3/NaOH ratio from 1.5 to 2.5. Physical and mechanical properties along with effect of heat and ambient curing conditions were investigated at various ages. The optimized mixture of fly ash based geopolymer concrete was then up scaled by blending with locally available Metakaolin (MK) with different dosages (i.e., 10%, 20%, 30%, 40%). The aim of the study is to identify the binary effect of FA and MK on overall performance of geopolymer concrete. Results showed that 30% FA-MK based GPC depicted 21%, 19% and 26% more compressive strength, split tensile strength and flexural strength respectively than Fly Ash based GPC alone at heat cured condition. This can be explained mainly due to two facts namely binary action of metakaolin that enhances compaction of GPC and pozzolanic activity of MK that expedite geopolymeric strength causing phases. The results were further verified by Modified Chapelle test and FTIR. Morphology of the developed GPC is also examined from SEM images. The work is an effort to utilize the fly ash produced by coal power plants to effectively address UN sustainable development goal related to sustainable cities and communities.

Human infant learning happens during exploration of the environment, by interaction with objects, and by listening to and repeating utterances casually, which is analogous to unsupervised learning. Only occasionally, a learning infant would receive a matching verbal description of an action it is committing, which is similar to supervised learning. Such a learning mechanism can be mimicked with deep learning. We model this weakly supervised learning paradigm using our Paired Gated Autoencoders (PGAE) model, which combines an action and a language autoencoder. After observing a performance drop when reducing the proportion of supervised training, we introduce the Paired Transformed Autoencoders (PTAE) model, using Transformer-based crossmodal attention. PTAE achieves significantly higher accuracy in language-to-action and action-to-language translations, particularly in realistic but difficult cases when only few supervised training samples are available. We also test whether the trained model behaves realistically with conflicting multimodal input. In accordance with the concept of incongruence in psychology, conflict deteriorates the model output. Conflicting action input has a more severe impact than conflicting language input, and more conflicting features lead to larger interference. PTAE can be trained on mostly unlabeled data where labeled data is scarce, and it behaves plausibly when tested with incongruent input.

Abstract Dehumidification is one of the key challenges facing the air conditioning (AC) industry in the treatment of moist air. Over many decades, the dual role of heat exchangers of AC chillers for the sensible and latent cooling of space has hindered the thermal-lift reduction in the refrigeration cycle due to the requirements of water vapor removal at dew-point and heat rejection to the ambient air. These practical constraints of AC chillers have resulted in the leveling of energy efficiency of mechanical vapor compressors (MVC) for many decades. One promising approach to energy efficiency improvement is the decoupling of dehumidification from sensible processes so that innovative but separate processes can be applied. In this paper, an advanced microwave dehumidification method is investigated in the laboratory, where the microwave (2.45 GHz) energy can be irradiated onto the dipole structure of water vapor molecules, desorbing rapidly from the pores of adsorbent. Results show a significant improvement in performance for microwave dehumidification, up to fourfold, as compared to data available in the literature.

Wireless Multimedia Sensor Network (WMSN) is a wirelessly connected sensor network featuring multimedia devices such as cameras and microphones that can retrieve video and audio streams, photographs, and scalar sensor data. Because of the low cost of cameras and microphones, in addition to significant advances in distributed signal processing and multimedia data coding approaches, WMSNs can offer multimedia content. Moreover, the most critical difficulty in the implementation of WMSN is to improve the efficiency and lifetime of the network. The Named-Data Network (NDN) technique is used in WMSNs to increase communication and transmission mechanisms efficiency. NDN is thought to be one of the most demanding Internet architectures in the future. Unlike host-centric techniques that focus on the location of the content, NDN focuses on providing the content. In this paper, we propose a novel accumulative Interest-based content-store architecture for NDN-based WMSNs to improve the efficiency of individual nodes as well as the overall network. Furthermore, the proposed solution also controls packet flooding. The proposed scheme is named “Efficient Data Retrieval and Forwarding (E-DRAFT)”. Moreover, the ndnSIM simulator is used to run comprehensive simulations. Compared to existing methodologies, the simulation results reveal that the proposed approach stops additional packet flooding and effectively stores and retrieves Data packets with enhanced processing efficiency.

The Internet of Things (IoT) can enable seamless communication between millions of billions of objects. As IoT applications continue to grow, they face several challenges, including high latency, limited processing and storage capacity, and network failures. To address these stated challenges, the fog computing paradigm has been introduced, purpose is to integrate the cloud computing paradigm with IoT to bring the cloud resources closer to the IoT devices. Thus, it extends the computing, storage, and networking facilities toward the edge of the network. However, data processing and storage occur at the IoT devices themselves in the fog-based IoT network, eliminating the need to transmit the data to the cloud. Further, it also provides a faster response as compared to the cloud. Unfortunately, the characteristics of fog-based IoT networks arise traditional real-time security challenges, which may increase severe concern to the end-users. However, this paper aims to focus on fog-based IoT communication, targeting real-time security challenges. In this paper, we examine the layered architecture of fog-based IoT networks along working of IoT applications operating within the context of the fog computing paradigm. Moreover, we highlight real-time security challenges and explore several existing solutions proposed to tackle these challenges. In the end, we investigate the research challenges that need to be addressed and explore potential future research directions that should be followed by the research community.

The COVID-19 pandemic forcing many individuals to exercise at home without the supervision of a professional trainer, and maintaining proper posture during arm and shoulder exercises has become a concern. In this study, the dataset is collected from various individuals performing different exercises with different variations in the range of motion. The wrist-worn band captures the motion data using the MPU6050 sensor, which measures acceleration data. The collected data is pre-processed, and features are extracted from the raw data. Machine learning-based classification algorithms are employed to classify the collected data. An App prototype has been developed, which is integrated with a WIFI module and Cloud for real-time data collection. The collected data is then used to train the selected machine learning models, which can accurately analyze an individual’s workout session and provide feedback on their performance through the App. Overall, this methodology provides a solution for individuals to continue their regular exercises at home without the need for a professional gym trainer or environment while minimizing the risk of injury due to poor posture. The results of this study will provide insight into the effectiveness of different machine learning algorithms for arm and shoulder exercises using a wrist-worn band, which can help in designing personalized exercise programs for individuals. We applied four machine learning algorithms to the dataset which are weighted KNN, Bagged Trees, Decision Trees, and Fine Gaussian SVM. The experimental results show that the Weighted KNN Model gives the best accuracy of 92%.

The prevalence of electromagnetic fields (EMFs) caused by electromagnetic radiation is increasing in our daily lives, potentially bringing both adverse and beneficial effects. EMFs have garnered significant research attention in various disciplines, including agricultural science. However, our understanding of the impact of EMFs on the ecophysiological performance of plants under suboptimal conditions is limited. Despite this, there are indications that EMFs can improve crop productivity by enhancing seed germination, plant nutrition, precision farming, water use efficiency, root hydraulic conductance, plant water uptake, anti-oxidative defense, pest prevention, stress signaling, and hormonal pathways. This review highlights the practical application of EMFs for increasing plant biomass production by elucidating the underlying mechanisms involved in seed germination, plant growth, water relations, ion flux, photosynthesis, and antioxidant defense. We also highlight the prospects for using EMFs in sustainable agriculture and their potential to alleviate the conventional agricultural pressures related to food security issues.

The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is an emerging cooling technology that combines the advantages of IEC and MVC, i.e., effective temperature and humidity control, high energy efficiency, and low water consumption. This paper presents an experimental study of the hybrid IEC-MVC process. A 1-Rton pilot is fabricated by connecting IEC and MVC in series, and its performance is evaluated under different operating conditions (outdoor air temperature and humidity, air flowrate, compressor frequency). Results revealed that the outdoor air temperature and humidity could be lowered to 5–15 °C and 5–10 g/kg, respectively. The IEC handles 35%–50% of the total cooling load, and the energy consumption can be reduced by 15%–35% as compared to standalone MVC. Moreover, the condensate collected from the evaporator can compensate for >70% of water consumption in IEC, making the system applicable in arid regions. Based on the derived results, a simplified empirical model is developed for rapid evaluation of the IEC-MVC process, and the energy-saving potential in major cities of Saudi Arabia is estimated.

Deep reinforcement learning (RL) agents often suffer from catastrophic forgetting, forgetting previously found solutions in parts of the input space when training new data. Replay memories are a common solution to the problem by decorrelating and shuffling old and new training samples. They naively store state transitions as they arrive, without regard for redundancy. We introduce a novel cognitive-inspired replay memory approach based on the Grow-When-Required (GWR) self-organizing network, which resembles a map-based mental model of the world. Our approach organizes stored transitions into a concise environment-model-like network of state nodes and transition edges, merging similar samples to reduce the memory size and increase pair-wise distance among samples, which increases the relevancy of each sample. Overall, our study shows that map-based experience replay allows for significant memory reduction with only small decreases in performance.

Analytical and empirical models analyze complex and non-linear interactions between the input–output parameters of the system. This is very important in the case of photovoltaic systems to understand their real performance potential. On the other hand, manufacturers of photovoltaic panels rate the maximum performance of the system under fixed lab conditions as per standard testing conditions (STCs) or nominal operating cell temperature (NOCT) standards of IEC. These ratings do not provide the actual production potential of the system in a field with fluctuating conditions of irradiance and temperature. For the case of a concentrated photovoltaic (CPV) system, utilizing multi-junction solar cells (MJCs), there is no commercial tool available to analyze the performance and production, despite some recent empirical models that also require post-processing of experimental data to be used in conventional models. In this study, an artificial neural network (ANN)-based performance model is presented for a multi-junction solar cell, which is not only convenient to apply but can also be easily expanded to predict the real-field performance of the CPV system of any designed size. In addition, the ANN-based model showed a high accuracy of 99.9% in predicting the performance output of MJCs as compared to diode-based empirical models available in the literature. The irradiance concentration at the cell area and the cell temperature are taken as inputs for the neural network. If both of these parameters are known, then the cell efficiency as an output can accurately predict the CPV performance for a field operation.

The canned food market is growing at an annually average rate of 3.6% due to easy access and awareness of dietary requirements, leading to a surge in water withdrawal and an estimated supply-demand gap of 40% by 2030. The conventional desalination processes are not sustainable due to high energy requirements and chemicals injection. The adsorption cycle is an emerging technology for desalination due to its temperature operation. It has many advantages over conventional desalination processes including integration synergy to improve overall performance. The conventional AD cycle processes, however, have lower performance due to inefficient packing of adsorbent in the beds and heat transfer losses to their massive heat exchangers. In this article, we propose an innovative pressure driven adsorption (PDAD) cycle to overcome conventional AD cycle limitations. In PDAD, firstly, low pressure steam is used to regenerate the adsorbent which eliminates the huge infrastructure requirement of water circulation and secondly, steam selectively extracts water vapours from pores, reducing energy consumption. We have tested the PDAD pilot and showed successful regeneration of silica gel at motive steam pressure of 2–5 bar. We also demonstrate that discharge steam from the PDAD at 65 °C can be used as a heat source for a multi effect desalination system when operating in hybrid mode to overcome its operational limitations. Our experiments show that the MED + PDAD cycle increases water production by up to 22% as compared to an earlier hybrid MEDAD cycle. The proposed system has excellent thermodynamic synergy with the combined CCGT power and desalination plant, where low-pressure bleed steam can be utilized more efficiently.

In Saudi Arabia, air conditioning is the main consumer of electricity, and increasing its energy efficiency is of great importance for energy conservation and carbon footprint reduction. This study presents the evaluation of a hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) cycle for cooling applications in Saudi Arabia. Most cities in this country are characterized by a high sensible cooling demand, and a few cities near the coasts of the Red sea and the Persian Gulf also need dehumidification. By employing the hybrid system, IEC can undertake about 60% of the cooling load in the summer of arid cities, and energy consumption can be reduced by up to 50%. The contribution of IEC and energy saving are less significant in humid cities because the latent loads have to be handled by MVC. Over the whole year, IEC contributes 50% of the total cooling capacity and reduces energy consumption by 40% in dry cities, while the saving is lower at 15%–25% in humid cities like Mecca and Jeddah. The average water consumption of the IEC is in the range of 4–12 L/hr. The water consumption can be replenished by the condensate collected from the MVC evaporator if the ambient humidity is high. Based on the annual performance, the cost of the IEC-MVC process is calculated, and it is 15%–35% lower than the standalone MVC. The results demonstrate the great potential of the hybrid IEC-MVC cycle in Saudi Arabia.

Abstract In seawater desalination, the energy efficiency of practical processes is expressed in kWh_electricity or low-grade-heat per m3 of water produced, omitting the embedded energy quality underlying their generation processes. To avoid thermodynamic misconceptions, it is important to recognize both quality and quantity of energy consumed. An unmerited quantitative apportionment can result in inferior deployment of desalination methods. This article clarifies misapprehensions regarding seeming parity between electricity and thermal sources that are sequentially cogenerated in power plants. These processes are represented by heat engines to yield the respective maximum (Carnot) work potentials. Equivalent work from these engines are normalized individually to give a corresponding standard primary energy (Q SPE), defined via a common energy platform between the adiabatic flame temperature of fuel and the surroundings. Using the Q SPE platform, the energy efficiency of 60 desalination plants of assorted types, available from literature, are compared retrospectively and with respect to Thermodynamic Limit.

Since the 1970s, commercial-scale thermally-driven seawater desalination plants have been powered by low-grade energy sources, drawn either with low-pressure bled-steam from steam turbines or the solar renewable energy harvested that are supplied at relatively low temperatures. Despite the increasing trend of seawater reverse osmosis plants, the role of thermal desalination methods (such as multi-stage flashing and multi-effect distillation) in GCC countries is still relevant in the Arabian Gulf, arising from higher salinity, the frequent algae blooms of seawater and their ability to utilize low temperature heat sources. Given the urgent need for lowering both the capital and operating costs of all processes within the desalination industry and better thermodynamic adaptation of low-grade heat input from renewable sources, the present paper addresses the abovementioned issues by investigating the direct contact spray evaporation and condensation (DCSEC) method. A DCSEC system comprises only hollow chambers (devoid of membranes or tubes, minimal use of chemical and maintenance) where vapor generation (flashing) utilizes the enthalpy difference between the sprayed feed seawater and the saturated vapor enthalpy of the vessels. Concomitantly, vapor is condensed with spray droplets of cooler water (potable) in adjacent condenser vessels, employing a simple design concept. We present detailed design and real seawater experiments data of a DCSEC system for the first time. The water production cost is calculated as $0.52/m3, which is one of the lowest figures reported compared to commercial processes presented by Global Water Intelligence.

Cooling has a significant share in energy consumption, especially in hot tropical regions. The conventional mechanical vapor compression (MVC) cycle, widely used for air-conditioning needs, has high energy consumption as air is cooled down to a dew point to remove the moisture. Decoupling the latent cooling load through dehumidification from the sensible cooling load can significantly improve the energy requirement for air-conditioning applications. Solid desiccants have shown safe and reliable operation against liquid desiccants, and several configurations of solid desiccants dehumidifiers are studied to improve their performance. However, the characteristics of solid desiccants are critical for the performance and overall operation of the dehumidifier. The properties of every desiccant depend upon its porous adsorbing surface characteristics. Hence, it has an optimum performance for certain humid conditions. Therefore, for a better dehumidification performance in a specific tropical region, the solid desiccant must have the best performance, according to the humidity range of that region. In this article, a theoretical methodology has been discussed to help the industry and chemists to understand the porous structural properties of adsorbent surfaces needed to tune the material performance for a particular humidity value before material synthesis.

Phytosterols are natural compounds found in all higher plants that have a wide variety of roles in plant growth regulation and stress tolerance. The phytosterol composition can also influence the development and reproductive rate of strict herbivorous insects and other important agronomic traits such as temperature and drought tolerance in plants. In this study, we analysed the phytosterol composition in 18 Brassica napus (Rapeseed/canola) cultivars and 20 accessions belonging to 10 related wild Brassicaceae species to explore diverse and novel phytosterol profiles. Plants were grown in a controlled phytotron environment and their phytosterols were analysed using a saponification extraction method followed by GC-MS from the leaf samples. The B. napus cultivars showed slight diversity in eight phytosterols (>0.02%) due to the genotypic effect, whereas the wild accessions showed significant variability in their phytosterol profiles. Of interest, a number of wild accessions were found with high levels of campesterol (HIN20, HIN23, HUN27, HIN30, SARS2, and UPM6563), stigmasterol (UPM6813, UPM6563, ALBA17, and ALBA2), and isofucosterol (SARS12, SAR6, and DMU2). These changes in individual phytosterols, or ratios of phytosterols, can have a significant implication in plant tolerance to abiotic stress and plant insect resistance properties, which can be used in breeding for crop improvement.

The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is deemed a promising cooling system for hot and humid areas. It possesses the merits of high energy efficiency and strong capability of temperature and humidity control. Herein, we provide an overview of the state-of-the-art investigations over different aspects of the hybrid IEC-MVC process. Firstly, we evaluate the potential of IEC as a pre-cooler and heat-recovery device. Then, we compare the energy efficiency of IEC-MVC with standalone MVC and summarize its long-term energy-saving potential under specific weather conditions. Subsequently, we discuss the economic viability and water consumption of the hybrid process. These studies form a solid foundation for the future installation of the IEC-MVC system.

Understanding adsorption phenomena is essential to optimize and customize the energy transformation in numerous industrial and environmental processes. The complex and heterogeneous structure of the adsorbent surface and the distinct interaction of adsorbent-adsorbate pairs are attributed to the diverse response of adsorption phenomena, measured by the state diagrams of adsorption uptake known as adsorption isotherms. To understand various forms of adsorption isotherms, the surface characteristics of the adsorbent surface with the heterogeneity of adsorption energy sites must be analyzed so that they can be modified for the tailored response of the material. Conventionally, such material synthesis is based on chemical recipes or post-treatment. However, if the adsorbent's surface characteristics and heterogeneity are known, then a directed change in the material structure can be planned for the desired results in the adsorption processes. In this paper, a theoretical and mathematical methodology is discussed to analyze the structure of various adsorbents in terms of the distribution of their adsorption energy sites. The change in their surface is then analyzed, which results in the tailored or customized response of the material.

Background: Klippel–Feil syndrome (KFS) includes craniocervical anomalies, low posterior hairline, and brevicollis, with limited cervical range of motion; however, there remains no consensus on inheritance pattern. This study defines incidence, characterizes concurrent diagnoses, and examines trends in the presentation and management of KFS. Methods: This was a retrospective review of the Kid's Inpatient Database (KID) for KFSpatients aged 0–20 years from 2003 to 2012. Incidence was established using KID-supplied year and hospital-trend weights. Demographics and secondary diagnoses associated with KFS were evaluated. Comorbidities, anomalies, and procedure type trends from 2003 to 2012 were assessed for likelihood to increase among the years studied using ANOVA tests. Results: Eight hundred and fifty-eight KFS diagnoses (age: 9.49 years; 51.1% females) and 475 patients with congenital fusion (CF) (age: 8.33 years; 50.3% females) were analyzed. We identified an incidence rate of 1/21,587 discharges. Only 6.36% of KFS patients were diagnosed with Sprengel's deformity; 1.44% with congenital fusion. About 19.1% of KFS patients presented with another spinal abnormality and 34.0% presented with another neuromuscular anomaly. About 36.51% of KFS patients were diagnosed with a nonspinal or nonmusculoskeletal anomaly, with the most prevalent anomalies being of cardiac origin (12.95%). About 7.34% of KFS patients underwent anterior fusions, whereas 6.64% of KFS patients underwent posterior fusions. The average number of levels operated on was 4.99 with 8.28% receiving decompressions. Interbody devices were used in 2.45% of cases. The rate of fusions with

With the increasing world population, demand for industrialization has also increased to fulfill humans’ living standards. Fungi are considered a source of essential constituents to produce the biocatalytic enzymes, including amylases, proteases, lipases, and cellulases that contain broad-spectrum industrial and emerging applications. The present review discussed the origin, nature, mechanism of action, emerging aspects of genetic engineering for designing novel proteases, genome editing of fungal strains through CRISPR technology, present challenges and future recommendations of fungal proteases. The emerging evidence revealed that fungal proteases show a protective role to many environmental exposures and discovered that an imbalance of protease inhibitors and proteases in the epithelial barriers leads to the protection of chronic eosinophilic airway inflammation. Moreover, mitoproteases recently were found to execute intense proteolytic processes that are crucial for mitochondrial integrity and homeostasis function, including mitochondrial biogenesis, protein synthesis, and apoptosis. The emerging evidence revealed that CRISPR/Cas9 technology had been successfully developed in various filamentous fungi and higher fungi for editing of specific genes. In addition to medical importance, fungal proteases are extensively used in different industries such as foods to prepare butter, fruits, juices, and cheese, and to increase their shelf life. It is concluded that hydrolysis of proteins in industries is one of the most significant applications of fungal enzymes that led to massive usage of proteomics.

Image processing and analysis is useful to monitor the activated sludge (AS) wastewater treatment plants based on the morphology of microbial aggregates (flocs) and filamentous bacteria. Phasecontrast microscopy is used to observe filamentous bacteria in the AS samples at lower objective magnification with improved visibility of details. However, segmentation of the phase-contrast images faces inherent difficulties caused by the artifacts associated with the microscopy, such as halos and shade-off. This paper is comprised mainly of three tasks: robust segmentation of phase-contrast images for filamentous bacteria, identification of novel image analysis parameters for morphology of the bacteria, and the use of the proposed parameters to model sludge volume index (SVI). SVI is the most important physical measurement employed to monitor the operation of an AS plant. In this paper, a robust phase-congruency-based method, augmented by top-hat and bottom-hat filtering, is proposed for segmentation of filamentous bacteria. Different metrics, such as accuracy, recall, variation of information, F-measure, and Rand index are used for the segmentation assessment. We propose an exact procedure to determine the total length of branched and unbranched filamentous bacteria. Moreover, a novel rotation invariant feature is proposed to determine the extent of the curvature of a filament. Finally, we investigated regression models for SVI of multiple AS wastewater treatment plants, based on the proposed image analysis parameters of the filaments. The modeling of SVI proves the significance of the proposed image analysis parameters for monitoring AS plants.

Peripartum pancreatitis is a rare clinical condition that occurs usually in the third trimester of pregnancy. Pancreatitis is usually secondary to gallstones, and it can lead to life-threatening and rare complications. We report a case of necrotizing postpartum pancreatitis that developed abdominal compartment syndrome (ACS) in early course, posterior reversible encephalopathy syndrome (PRES), and splanchnic and extrasplanchnic thrombosis later on. Case. 31-year-old female, one week after delivery, presented to the emergency department with abdominal pain, nausea and vomiting, tenderness in the epigastrium, and raised pancreatic enzymes. Ultrasound (USG) showed bulky pancreas with gallstones. She was diagnosed as having acute biliary pancreatitis and started to be hydrated and was supplemented with analgesia. Her condition deteriorated on the 2nd day, and she was shifted to the surgical intensive care unit (SICU) where she developed abdominal compartment syndrome (ACS), respiratory distress, and acute kidney injury, requiring endotracheal intubation and ventilation. Computerized tomography (CT) showed pancreatic necrosis with multiple fluid collections and significant left-sided pleural effusion. Percutaneous drainage of pleural effusion was done, and she was stabilized to be weaned off from mechanical ventilation. On day 15, she underwent USG-guided drainage of the pancreatic collection and ERCP (endoscopic retrograde cholangiopancreatography) on day 19. Post-ERCP, she had tonic colonic convulsions which were treated with benzodiazepines and phenytoin. It was diagnosed by imaging studies as posterior reversible encephalopathy syndrome (PRES). Her abdomen was still distended and tender; CT showed a significant pseudocyst with splanchnic and extrasplanchnic thrombosis. She had laparotomy, gastrocystostomy, and cholecystectomy on day 28th. She made uncomplicated recovery and discharged in good health. Conclusion. Peripartum pancreatitis can be complicated by ACS, PRES, and splanchnic and extrasplanchnic thrombosis.

The dynamic nature of meteorological data and the commercial availability of diverse photovoltaic systems, ranging from single-junction silicon-based PV panels to concentrated photovoltaic (CPV) systems utilizing multi-junction solar cells and a two-axis solar tracker, demand a simple but accurate methodology for energy planners and PV system designers to understand the economic feasibility of photovoltaic or renewable energy systems. In this paper, an electrical rating methodology is proposed that provides a common playing field for planners, consumers and PV manufacturers to evaluate the long-term performance of photovoltaic systems, as long-term electricity rating is deemed to be a quick and accurate method to evaluate economic viability and determine plant sizes and photovoltaic system power production. A long-term performance analysis based on monthly and electrical ratings (in kWh/m2/year) of two developed CPV prototypes, the Cassegrain mini dish and Fresnel lens CPVs with triple-junction solar cells operating under the meteorological conditions of Singapore, is presented in this paper. Performances are compared to other conventional photovoltaic systems.

For future sustainable seawater desalination, the importance of achieving better energy efficiency of the existing 19,500 commercial-scale desalination plants cannot be over emphasized. The major concern of the desalination industry is the inadequate approach to energy efficiency evaluation of diverse seawater desalination processes by omitting the grade of energy supplied. These conventional approaches would suffice if the efficacy comparison were to be conducted for the same energy input processes. The misconception of considering all derived energies as equivalent in the desalination industry has severe economic and environmental consequences. In the realms of the energy and desalination system planners, serious judgmental errors in the process selection of green installations are made unconsciously as the efficacy data are either flawed or inaccurate. Inferior efficacy technologies’ implementation decisions were observed in many water-stressed countries that can burden a country’s economy immediately with higher unit energy cost as well as cause more undesirable environmental effects on the surroundings. In this article, a standard primary energy-based thermodynamic framework is presented that addresses energy efficacy fairly and accurately. It shows clearly that a thermally driven process consumes 2.5–3% of standard primary energy (SPE) when combined with power plants. A standard universal performance ratio-based evaluation method has been proposed that showed all desalination processes performance varies from 10–14% of the thermodynamic limit. To achieve 2030 sustainability goals, innovative processes are required to meet 25–30% of the thermodynamic limit.

The use of the Internet is growing in this day and age, so another area has developed to use the Internet, called Internet of Things (IoT). It facilitates the machines and objects to communicate, compute and coordinate with each other. It is an enabler for the intelligence affixed to several essential features of the modern world, such as homes, hospitals, buildings, transports and cities. The security and privacy are some of the critical issues related to the wide application of IoT. Therefore, these issues prevent the wide adoption of the IoT. In this paper, we are presenting an overview about different layered architectures of IoT and attacks regarding security from the perspective of layers. In addition, a review of mechanisms that provide solutions to these issues is presented with their limitations. Furthermore, we have suggested a new secure layered architecture of IoT to overcome these issues.