Demand-side load forecasting in smart grids using machine learning techniques.

Electrical load forecasting remains an ongoing challenge due to various factors, such as temperature and weather, which change day by day. In this age of Big Data, efficient handling of data and obtaining valuable information from raw data is crucial. Through the use of IoT devices and smart meters, we can capture data efficiently, whereas traditional methods may struggle with data management. The proposed solution consists of two levels for forecasting. The selected subsets of data are first fed into the "Daily Consumption Electrical Networks" (DCEN) network, which provides valid input to the "Intra Load Forecasting Networks" (ILFN) network. To address overfitting issues, we use classic or conventional neural networks. This research employs a three-tier architecture, which includes the cloud layer, fog layer, and edge servers. The classical state-of-the-art prediction schemes usually employ a two-tier architecture with classical models, which can result in low learning precision and overfitting issues. The proposed approach uses more weather features that were not previously utilized to predict the load. In this study, numerous experiments were conducted and found that support vector regression outperformed other methods. The results obtained were 5.055 for mean absolute percentage error (MAPE), 0.69 for root mean square error (RMSE), 0.37 for normalized mean square error (NRMSE), 0.0072 for mean squared logarithmic error (MSLE), and 0.86 for R2 score values. The experimental findings demonstrate the effectiveness of the proposed method.

mRNA vaccines against infectious diseases and future direction.

Vaccines are used for the control of infectious diseases of animals. Over other types of vaccinations like live attenuated or killed vaccines, mRNA-based vaccines have significant advantages. As only a small portion of the pathogen's genetic material is employed and the dose rate of mRNA-based vaccines is low, there is the least possibility that the pathogen will reverse itself. A carrier or vehicle that shields mRNA-based vaccines from the host's cellular RNases is necessary for their delivery. mRNA vaccines have been shown to be effective and to induce both a cell-mediated immune response and a humoral immune response in clinical trials against various infectious diseases (viral and parasitic) affecting the animals, including rabies, foot and mouth disease, toxoplasmosis, Zikavirus, leishmaniasis, and COVID-19. The current review aims to highlight the use of mRNA-based vaccines both in viral and parasitic diseases of animals.

A model for new media data mining and analysis in online English teaching using long short-term memory (LSTM) network.

To maintain a harmonious teacher-student relationship and enable educators to gain a more insightful understanding of students' learning progress, this study collects data from learners utilizing the software through a network platform. These data are mainly formed by the user's learning characteristics, combined with the screen lighting time, built-in inertial sensor attitude, signal strength, network strength and other multi-dimensional characteristics to form the learning observation value, so as to analyze the corresponding learning state, so that teachers can carry out targeted teaching improvement. The article introduces an intelligent classification approach for learning time series, leveraging long short-term memory (LSTM) as the foundation of a deep network model. This model intelligently recognizes the learning status of students. The test results demonstrate that the proposed model achieves highly precise time series recognition using relatively straightforward features. This precision, exceeding 95%, is of significant importance for future applications in learning state recognition, aiding teachers in gaining an intelligent grasp of students' learning status.

AndroDex: Android Dex Images of Obfuscated Malware.

With the emergence of technology and the usage of a large number of smart devices, cyber threats are increasing. Therefore, research studies have shifted their attention to detecting Android malware in recent years. As a result, a reliable and large-scale malware dataset is essential to build effective malware classifiers. In this paper, we have created AndroDex: an Android malware dataset containing a total of 24,746 samples that belong to more than 180 malware families. These samples are based on .dex images that truly reflect the characteristics of malware. To construct this dataset, we first downloaded the APKs of the malware, applied obfuscation techniques, and then converted them into images. We believe this dataset will significantly enhance a series of research studies, including Android malware detection and classification, and it will also boost deep learning classification efforts, among others. The main objective of creating images based on the Android dataset is to help other malware researchers better understand how malware works. Additionally, an important result of this study is that most malware nowadays employs obfuscation techniques to hide their malicious activities. However, malware images can overcome such issues. The main limitation of this dataset is that it contains images based on .dex files that are based on static analysis. However, dynamic analysis takes time, therefore, to overcome the issue of time and space this dataset can be used for the initial examination of any .apk files.

Inhibition of Trichinella spiralis Membrane-Associated Progesterone Receptor (MAPR) Results in a Reduction in Worm Burden.

Trichinella spiralis (T. spiralis), a nematode parasite, is the major cause of Trichinellosis, a zoonotic disease. A key role of MAPR in the reproductive system is to maintain pregnancy. Previous studies found that antihormone drug design and vaccine therapy of recombinant protein (rTs-MAPRC2) control T. spiralis infection. The current study investigates the inhibitory effects of different ratios of antibodies against Ts-MAPRC2 on the development of muscle larvae (ML) and newborn larvae (NBL). First, we performed indirect immunofluorescence assays and examined the effects of rTs-MAPRC2-Ab on ML and NBL in vitro as well as in vivo. Afterward, siRNA-Ts-MAPRC2 was transfected into T. spiralis muscle larvae. Following that, Ts-MAPRC2 protein was detected by Western Blotting, and mRNA levels were determined by qPCR. We also assessed whether siRNA-treated NBLs were infective by analyzing muscle larvae burden (MLs). Our results showed that rTs-MAPRC2-Ab greatly inhibited the activity of the Ts-MAPRC2 in ML and NBL of T. spiralis and rTs-MAPRC2-Ab reduced larval infectivity and survival in the host in a dose-dependent manner (1:50, 1:200, 1:800 dilutions). Furthermore, siRNA-Ts-MAPRC2 effectively silenced the Ts-MAPRC2 gene in muscle larvae (ML) in vitro, as well as in newborn larvae (NBL) of T. spiralis in vivo. In addition, siRNA-Ts-MAPRC2 (siRNA180, siRNA419, siRNA559) reduced host larval survival and infectivity significantly. This study, therefore, suggests that Ts-MAPRC2 might be a novel molecular target useful in the development of vaccines against T. spiralis infection.

Cobalt Iron Oxide (CoFe2O4) Nanoparticles Induced Toxicity in Rabbits.

The market for nanoparticles has grown significantly over the past few decades due to a number of unique qualities, including antibacterial capabilities. It is still unclear how nanoparticle toxicity works. In order to ascertain the toxicity of synthetic cobalt iron oxide (CoFe2O4) nanoparticles (CIONPs) in rabbits, this study was carried out. Sixteen rabbits in total were purchased from the neighborhood market and divided into two groups (A and B), each of which contained eight rabbits. The CIONPs were synthesized by the co-precipitation method. Crystallinity and phase identification were confirmed by X-ray diffraction (XRD). The average size of the nanoparticles (13.2 nm) was calculated by Scherrer formula (Dhkl = 0.9 λ/ß cos θ) and confirmed by TEM images. The saturation magnetization, 50.1 emug-1, was measured by vibrating sample magnetometer (VSM). CIONPs were investigated as contrast agents (CA) for magnetic resonance images (MRI). The relaxivity (r = 1/T) of the MRI was also investigated at a field strength of 0.35 T (Tesla), and the ratio r2/r1 for the CIONPs contrast agent was 6.63. The CIONPs were administrated intravenously into the rabbits through the ear vein. Blood was collected at days 5 and 10 post-exposure for hematological and serum biochemistry analyses. The intensities of the signal experienced by CA with CIONPs were 1427 for the liver and 1702 for the spleen. The treated group showed significantly lower hematological parameters, but significantly higher total white blood cell counts and neutrophils. The results of the serum biochemistry analyses showed significantly higher and lower quantities of different serum biochemical parameters in the treated rabbits at day 10 of the trial. At the microscopic level, different histological ailments were observed in the visceral organs of treated rabbits, including the liver, kidneys, spleen, heart, and brain. In conclusion, the results revealed that cobalt iron oxide (CoFe2O4) nanoparticles induced toxicity via alterations in multiple tissues of rabbits.

Metagenome of Gut Microbiota Provides a Novel Insight into the Pathogenicity of Balantioides coli in Weaned Piglets.

Balantioides coli plays an important role in the diarrhea of weaned piglets, but its pathogenic potential and interaction with gut microbes remain unclear. To investigate the impact of B. coli colonization on the gut bacterial structure and function of weaned piglets, a metagenomic analysis based on shotgun sequencing was performed on fresh fecal samples collected from ten B. coli-colonized piglets and eight B. coli-free ones in this study. The results showed that decreasing diversity and shifted composition and function of the bacterial community were detected in the weaned piglets infected by B. coli. In contrast to the B. coli-negative group, the relative abundances of some members of the Firmicutes phylum including Clostridium, Ruminococcus species, and Intestinimonas butyriciproducens, which produce short-chain fatty acids, were significantly reduced in the B. coli-positive group. Notably, some species of the Prevotella genus (such as Prevotella sp. CAG:604 and Prevotella stercorea) were significantly increased in abundance in the B. coli-positive piglets. A functional analysis of the gut microbiota demonstrated that the differential gene sets for the metabolism of carbohydrates and amino acids were abundant in both groups, and the more enriched pathways in B. coli-infected piglets were associated with the sugar-specific phosphotransferase system (PTS) and the two-component regulatory system, as well as lipopolysaccharide (LPS) biosynthesis. Furthermore, several species of Prevotella were significantly positively correlated to the synthesis of lipid A, leading to the exporting of endotoxins and, thereby, inducing inflammation in the intestines of weaned piglets. Taken together, these findings revealed that colonization by B. coli was distinctly associated with the dysbiosis of gut bacterial structure and function in weaned piglets. Lower relative abundances of Clostridiaceae and Ruminococcaceae and higher abundances of Prevotella species were biomarkers of B. coli infection in weaned piglets.

TTECCDU: a blockchain-based approach for expressive authorization management.

Authorization uses the access control policies to allow or limit a user the access to a resource. Blockchain-based access control models are used to manage authorization in a decentralized way. Many approaches exist that have provided the distributed access control frameworks which are user driven, transparent and provide fairness with its distributed architecture. Some approaches have used authorization tokens as access control mechanisms and mostly have used smart contracts for the authorization process. The problem is that most of the approaches rely on a single authorization factor like either trust or temporal; however, none has considered other important factors like cost, cardinality, or usage constraints of a resource making the existing approaches less expressive and coarse-grained. Also, the approaches using smart contracts are either complex in design or have high gas cost. To the best of our knowledge, there is no approach that uses all the important authorization factors in a unified framework. In this article, we present an authorization framework: TTECCDU that consists of multi-access control models i.e., trust-based, cost-based, temporal-based, cardinality-based, and usage-based to provide strong and expressive authorization mechanism. TTECCDU also handles the delegation context for authorization decisions. The proposed framework is implemented using smart contracts which are written in a modular form so that they are easily manageable and can be re-deployed when needed. Performance evaluation results show that our smart contracts are written in an optimized manner which consume 60.4% less gas cost when the trust-based access is compared and 59.2% less gas cost when other proposed smart contracts from our approach are compared to the existing approaches.

Biosynthesis and characterization of zinc oxide nanoparticles using Nigella sativa against coccidiosis in commercial poultry.

Coccidiosis causes huge economic losses worldwide. Current study evaluated the effect of biosynthesized Zinc oxide nanoparticles (ZnONPs) using Nigella sativa, on Eimeria tenella infected broilers. Scanning electron microscopy showed spherical ZnONPs with 50-100 nm diameter, Fourier transforms infrared spectroscopy revealed the functional groups involved in the reduction of zinc acetate dihydrate to ZnONPs, UV-vis spectroscopy showed a peak at 354 nm, and Zeta potential exhibited stability at - 30 mV. A total of 150, a day-old broiler chicks were divided into 5 equal groups. Control negative: uninfected and untreated; Control positive: Infected and untreated; 3rd, 4th and 5th group were infected orally with 5 × 104 sporulated oocysts of Eimeria tenella and treated with 60 mg/kg ZnONPs, 1% Nigella sativa seeds and amprolium 125 ppm, respectively. ZnONPs significantly (p < 0.05) improved the growth performance in the infected birds and decreased the oocyst shedding and anti-coccidial index. A significant (p < 0.05) decrease in the level of aspartate transferase and alanine transferase, whereas, a significantly higher amount of antioxidants like catalase and superoxide dismutase in ZnONPs treated group was observed. Pro-inflammatory cytokines like IL-2 and TNF-α were significantly decreased by ZnONPs (p < 0.05). In conclusion, biogenic ZnONPs with Nigella sativa might have enhanced anticoccidial, antioxidant, and anti-inflammatory effects with improved growth performance.

Prenyl Transferases Regulate Secretory Protein Sorting and Parasite Morphology in Toxoplasma gondii.

Protein prenylation is an important protein modification that is responsible for diverse physiological activities in eukaryotic cells. This modification is generally catalyzed by three types of prenyl transferases, which include farnesyl transferase (FT), geranylgeranyl transferase (GGT-1) and Rab geranylgeranyl transferase (GGT-2). Studies in malaria parasites showed that these parasites contain prenylated proteins, which are proposed to play multiple functions in parasites. However, the prenyl transferases have not been functionally characterized in parasites of subphylum Apicomplexa. Here, we functionally dissected functions of three of the prenyl transferases in the Apicomplexa model organism Toxoplasma gondii (T. gondii) using a plant auxin-inducible degron system. The homologous genes of the beta subunit of FT, GGT-1 and GGT-2 were endogenously tagged with AID at the C-terminus in the TIR1 parental line using a CRISPR-Cas9 approach. Upon depletion of these prenyl transferases, GGT-1 and GGT-2 had a strong defect on parasite replication. Fluorescent assay using diverse protein markers showed that the protein markers ROP5 and GRA7 were diffused in the parasites depleted with GGT-1 and GGT-2, while the mitochondrion was strongly affected in parasites depleted with GGT-1. Importantly, depletion of GGT-2 caused the stronger defect to the sorting of rhoptry protein and the parasite morphology. Furthermore, parasite motility was observed to be affected in parasites depleted with GGT-2. Taken together, this study functionally characterized the prenyl transferases, which contributed to an overall understanding of protein prenylation in T. gondii and potentially in other related parasites.

Crimean-Congo hemorrhagic fever: Immunopathogenesis and recent advances in the development of vaccines.

Crimean-Congo hemorrhagic fever is a serious vector-borne zoonotic viral infection which leads to severe illness and fatalities in people living in endemic regions and becoming infected sporadically. Hyalomma ticks are responsible for the transmission of the virus which belongs to the family Nairoviridae. This disease spreads through ticks bite, infected tissues, or blood of viremic animals, and from infected humans to others. Serological studies also indicate the presence of the virus in various domestic and wild animals to be a risk factor for the transmission of the disease. Crimean-Congo hemorrhagic fever virus elicits many immune responses during the infection including inflammatory, innate, and adaptive immune responses. The development of an effective vaccine could be a promising method for the control and prevention of disease in endemic areas. The purpose of this review is to highlight the importance of CCHF, its mode of transmission, the interaction of the virus with the hosts and ticks, immunopathogenesis, and advances in immunization.

Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism.

With the rise in popularity and usage of Android operating systems, malicious applications are targeted by applying innovative ways and techniques. Today, malware becomes intelligent that uses several ways of obfuscation techniques to hide its functionality and evade anti-malware engines. For mainstream smartphone users, Android malware poses a severe security danger. An obfuscation approach, however, can produce malware versions that can evade current detection strategies and dramatically lower the detection accuracy. Attempting to identify Android malware obfuscation variations, this paper proposes an approach to address the challenges and issues related to the classification and detection of malicious obfuscated variants. The employed detection and classification scheme uses both static and dynamic analysis using an ensemble voting mechanism. Moreover, this study demonstrates that a small subset of features performs consistently well when they are derived from the basic malware (non-obfuscated), however, after applying a novel feature-based obfuscation approach, the study shows a drastic change indicating the relative importance of these features in obfuscating benign and malware applications. For this purpose, we present a fast, scalable, and accurate mechanism for obfuscated Android malware detection based on the Deep learning algorithm using real and emulator-based platforms. The experiments show that the proposed model detects malware effectively and accurately along with the identification of features that are usually obfuscated by malware attackers.

Splenic Injury After a Screening Colonoscopy.

Colonoscopy is a safe and routinely performed procedure worldwide. However, complications such as bleeding and perforation can occur. Splenic injury after a colonoscopy is a rare complication. We present the case of a 71-year-old woman who presented to the ED due to abdominal pain after undergoing a screening colonoscopy. An abdominal CT scan showed a grade III splenic injury with a subcapsular hematoma. She was successfully managed conservatively. Splenic injuries after colonoscopy are associated with significant morbidity and mortality. A low threshold of suspicion and timely diagnosis can improve outcomes.

Cost-benefit ratio of anthelmintic treatment and its comparative efficacy in commercial dairy farms.

Intestinal parasitic infection is one of the major challenges in obtaining optimal production and maintaining the health and welfare of all animals including cattle and buffaloes. Anti-parasitic treatments appear to be a reliable countermeasure. However, the effectiveness and selection of suitable anthelmintics require situational assessments in a given locality. In the current study, the efficacy and impact of benzimidazole (albendazole) were assessed in a total of 400 (100 each) on the performance of buffaloes, buffalo-heifer, cattle, and cattle-heifers at two commercial dairy farms in the Province of Punjab, Pakistan. Additionally, the cost-benefit ratio was calculated by assessing the inputs (medication, feed, and labor cost) and outputs (milk and weight gain). The qualitative and quantitative examination of helminth eggs in each type of animal indicated a prevalence of 73.3, 78.3, 76.6, and 85.0% in cattle, cattle-heifers, buffaloes, and buffaloes-heifers, respectively. Specifically, a highest rate (10.0-13.3%) of Haemonchus sp. infection was only observed in cattle and heifers, while Fasciola sp. infections (10.0-11.6%) were the most often found species in buffaloes and heifers. The highest anthelmintic impacts (egg per gram of feces, p < 0.001) were observed on day 14 post-medication. Until 60 days of post-anthelmintic treatment, an average increase of 0.8 and 0.7 L in milk production per day in cattle and buffaloes, respectively while a total of 11.45 and 9.45 kg body weight were noticed in cattle-heifer and buffaloes-heifer, respectively. Cumulative cost-benefit analysis indicated a positive correlation between treated and non-treated animals. These findings reiterate the importance of anthelmintic drugs in reducing the impacts of parasites on the productivity, health, and well-being of an animal under high infection challenges.

New strategies in the treatment of diseases caused by Acanthamoeba based on nanoparticles: a systematic review.

BACKGROUND: Acanthamoeba is one of the opportunistic parasites with a global prevalence. Currently, due to the side effects and the emergence of drug resistance to this parasite, much research has been performed on the use of nano-drugs to treat Acanthamoeba-caused diseases. Therefore, this systematic review study aims to evaluate new strategies for treating diseases caused by Acanthamoeba based on nanoparticles (NPs). METHODS: We designed a systematic review based on the articles published in English between 2000 and 2022. Our search strategy was based on syntax and specific tags for each database, including ScienceDirect, PubMed, Scopus, Ovid, and Cochrane. From the articles, those that had inclusion criteria were selected, and their data were extracted and analyzed. RESULTS: In this study, 26 studies were selected. Metallic nanoparticles were mostly used against the Acanthamoeba species (80.7%). 19.2% of the studies used polymeric nanoparticles, and 3.8% used emulsion nanoparticles. Most studies (96.1%) were performed in vitro, and only one study (3.8%) was carried out in vivo. Silver NPs were the most used metallic nanoparticles in the studies. The best effect of the anti-Acanthamoeba compound was observed for green synthesized nanoparticles based on stabilization by plant gums, loaded with citrus fruits flavonoids hesperidin (HDN) and naringin (NRG) with a 100% growth inhibition at a concentration of 50 µg/mL. CONCLUSION: This study showed that chlorhexidine and other plant metabolites loaded with silver and gold nanoparticles increase the anti-Acanthambae activity of these nanoparticles. However, green synthesized nanoparticles based on stabilization by plant gums, loaded with citrus fruits flavonoids hesperidin (HDN) and naringin (NRG), showed the best anti-Acanthambae effect. Nevertheless, further studies should be performed to determine their safety for human use.

AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems.

Due to the widespread usage of Android smartphones in the present era, Android malware has become a grave security concern. The research community relies on publicly available datasets to keep pace with evolving malware. However, a plethora of apps in those datasets are mere clones of previously identified malware. The reason is that instead of creating novel versions, malware authors generally repack existing malicious applications to create malware clones with minimal effort and expense. This paper investigates three benchmark Android malware datasets to quantify repacked malware using package names-based similarity. We consider 5560 apps from the Drebin dataset, 24,533 apps from the AMD and 695,470 apps from the AndroZoo dataset for analysis. Our analysis reveals that 52.3% apps in Drebin, 29.8% apps in the AMD and 42.3% apps in the AndroZoo dataset are repacked malware. Furthermore, we present AndroMalPack, an Android malware detector trained on clones-free datasets and optimized using Nature-inspired algorithms. Although trained on a reduced version of datasets, AndroMalPack classifies novel and repacked malware with a remarkable detection accuracy of up to 98.2% and meagre false-positive rates. Finally, we publish a dataset of cloned apps in Drebin, AMD, and AndrooZoo to foster research in the repacked malware analysis domain.

Excretory/secretory proteins inhibit host immune responses by downregulating the TLR4/NF-κB/MAPKs signaling pathway: A possible mechanism of immune evasion in parasitic nematode Haemonchus contortus.

Haemonchus contortus is an important parasitic nematode of ruminants. Previous studies showed that H. contortus escape the immunity through complex mechanisms, including releasing excretory/secretory proteins (ESPs) to modulate the host immune response. However, the detailed mechanism through which H. contortus excretory/secretory proteins (HcESPs) promote immune evasion remains unknown. In the present study, we demonstrated that HcESPs inhibit the adaptive immune response of goats including downregulation of immune cell antigen presentation, upregulation of immune checkpoint molecules, activation of the STAT3/PD-L1 pathway, and activation of immunosuppressive regulatory T (Treg) cells. Furthermore, HcESPs reversed the LPS-induced upregulation of pro-inflammatory mediators in PBMCs by inhibiting the TLR4/NF-κB/MAPKs/NLRP3 signaling pathway. Our study provides a better understanding of the evasion mechanisms for H. contortus, which could be helpful in providing an alternative way to prevent the infection of this parasite.

Molecular and Morphological Characterization of Eimeria crandallis Isolated from Deer (Cervidae) in Different Captive Animals.

Coccidiosis is a protozoan disease that is characterized by diffuse diarrhea, dehydration, emaciation accompanied by moderate morbidity and mild mortality in animals and birds. The current study targeted the molecular characterization of Eimeria isolates in captive deer from different localities in Lahore. The host species was the Cervidae family, such as Hog deer (Axis porcinus) and Punjab urial (Ovis aries vignei). The Eimeria crandallis was isolated from zoo animals. The DNA was extracted from oocysts and amplified by using reported oligonucleotide primers that exhibited the 809 bp product. These were analyzed by using the small subunit 18S rRNA gene-based evolutionary relationship with 36 other Eimeria species reported in caprine, cervinae, bovines, avians, and rodents. Light microscopic examination exhibited 3.29% (7/213) Eimeria-positive fecal samples with morphological features, including sub-spherical forms, the presence of micropyle with polar cap, and oocysts diameters (µm) ranging from 24.32 ± 1.61 to 18.94 ± 1.51. The phylogenetic tree constitutes four distinct clusters with relatively higher values. The evolutionary network showed that sequences were clustered in the monophyletic group of Eimeria species reported in caprine and cervinae. The nucleotide and amino acid sequence similarity matrix analysis exhibited 99.5-99.9% identity of the study isolates with Eimeria crandallis (AF336339). This study provides relevant baseline data to develop strategic control measures for coccidiosis in zoo animals. However, further investigations are required to place the hog deer and Punjab urial-derived E. crandallis into the caprine-originated cluster.