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Abstract Exploration in complex networks has surged. Centrality measures play a pivotal role in pinpointing essential components within these networks. Previous work focus on nodes with the highest Betweenness centrality through extensive simulations. This paper analyzes the attack and/or defense strategy using one more centrality metric, bridging centrality and Bridging-Betweenness Fusion Attack (combination of both betweenness and bridging centrality). Our two-fold contribution is (1) Using high centrality removal as an attacking strategy and inspired by the dynamic node removal process, recalculated node method after each node removal is proposed. (2) In our defense techniques, new nodes are added to existing lower centrality nodes. They are added after attacks to restore the graph’s connectivity according to proposed defense strategies. Note that some attacks and defense techniques were already introduced while others are presented first time, e.g., the combination of two centrality measures for attack and a bridging-based defense strategy. This innovative approach presents a promising advancement in enhancing the resilience and fortification of complex networks against potential attacks, signifying a notable advantage of this work.

Studying the physiological mechanisms underlying the traits associated with salt tolerance in genotypes could lead to the discovery of new genetic resources for salt tolerance. In this study, the mechanisms of salt tolerance were evaluated, based on ionic, physiological, and agronomic traits in four varieties that differ in their salt tolerance and in 18 F8 recombinant inbred lines (RILs) grown in real field conditions. The salt tolerance of plant materials was assessed under both normal (3.5 mM NaCl) and high salinity stress (150 mM NaCl) conditions for two consecutive years. Different growth and physiological traits were assessed 75 days after sowing, while ion contents in the shoots, grain yield, and its components were determined at the maturity stage. Multivariate analysis was used to conduct a comprehensive evaluation of salt tolerance across various genotypes and traits. The ANOVA results showed significant differences (p ≤ 0.05 and 0.001) among salinity, genotypes, and their interactions for all ionic and agro-physiological traits, with a few exceptions. Salinity stress resulted in a considerable increase in Na+ content and canopy temperature (CT), with a simultaneous decrease of 11.3% to 94.5% in other ionic and agro-physiological traits compared to the control treatment. However, the salt-tolerant genotypes showed minimal increases in Na+ content and CT, as well as decreases in other ionic and agro-physiological traits when compared to salt-sensitive genotypes under salinity stress. All ionic and agro-physiological traits exhibited strong correlations with each other under salinity stress, but these correlations were weak or insignificant under control conditions. The principal component analysis identified Na+ and CT as negative indicators and other ionic and agro-physiological traits as positive indicators for salt tolerance under salinity stress. The negative indicators were strongly linked to salt-sensitive genotypes, while the positive indicators were closely associated with salt-tolerant genotypes. Heatmap clustering, using multiple traits, successfully differentiated the salt-tolerant genotypes from the salt-sensitive ones. The salt-tolerant group showed a significant reduction in Na+ content by 36.9%, in CT by 10.0%, and in HI by 16.7%, along with an increase of 6.3–51.4% in other ionic and agro-physiological traits compared to the salt-sensitive group. In conclusion, the mechanisms associated with Na+ exclusion and high K+/Na+ and Ca2+/Na+ ratios, as well as chlorophyll and relative water content, along with low CT, resulted in significant improvements in growth and yield under salinity stress conditions. Given that the effectiveness of various ionic and agro-physiological traits in evaluating salt tolerance in wheat has been proven in real field conditions, these traits will play a key role in the development of salt-tolerant wheat genotypes.

Developing new bread wheat varieties that can be successfully grown in saline conditions has become a pressing task for plant breeders. High-throughput phenotyping tools are crucial for this task. Proximal remote sensing is gaining popularity in breeding programs as a quick, cost-effective, and non-invasive tool to assess canopy structure and physiological traits in large genetic pools. Limited research has been conducted on the effectiveness of combining RGB and thermal imaging to assess the salt tolerance of different wheat genotypes. This study aimed to evaluate the effectiveness of combining several indices derived from thermal infrared and RGB images with artificial neural networks (ANNs) for assessing relative water content (RWC), chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (Chlt), and plant dry weight (PDW) of 18 recombinant inbred lines (RILs) and their 3 parents irrigated with saline water (150 mM NaCl). The results showed significant differences in various traits and indices among the tested genotypes. The normalized relative canopy temperature (NRCT) index exhibited strong correlations with RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.50 to 0.73, 0.53 to 0.76, 0.68 to 0.84, 0.68 to 0.84, and 0.52 to 0.76, respectively. Additionally, there was a strong relationship between several RGB indices and measured traits, with the highest R2 values reaching up to 0.70. The visible atmospherically resistant index (VARI), a popular index derived from RGB imaging, showed significant correlations with NRCT, RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.49 to 0.62 across two seasons. The different ANNs models demonstrated high predictive accuracy for NRCT and other measured traits, with R2 values ranging from 0.62 to 0.90 in the training dataset and from 0.46 to 0.68 in the cross-validation dataset. Thus, our study shows that integrating high-throughput digital image tools with ANN models can efficiently and non-invasively assess the salt tolerance of a large number of wheat genotypes in breeding programs.

ABSTRAK Pencemaran yang terkandung dalam limbah cair yang mengandung Cr(VI)merupakan ancaman yang cukup serius bagi kelestarian lingkungan karena selain merupakan pencemar yang bersifat racun bagi organisme perairan, pencemar tersebut juga mempengaruhi sifat fisik, kimia, dan biologi lingkungan perairan serta memiliki zat yang dapat menyebabkan penyakit kanker. Tanaman Kangkung Air (Ipomoea Aquatica Forsk) memiliki potensi menurunkan kandungan Cr6+ Sehingga penelitian ini bertujuan untuk mengetahui kemampuan kangkung air dalam menurunkan kadar Cr(VI) dan kemampuan mikroorganisme pada air sungai dalam mendegradasi kadar Cr(VI). Penelitian ini dilakukan secara berkala selama 4 kali dari hari ke-0, 3, 5, dan 7. Pada tahap pertama menganalisis kemampuan mikroorganisme yang terdapat pada air sungai dalam mendegradasi logam berat dengan mengukur konsentrasi Cr(VI) menggunakan colorimeter. Analisis selanjutnya mengukur konsentrasi Cr(VI) pada tanaman kangkung air. Berdasarkan hasil pengamatan maka dapat diketahui bahwa mikroorganisme pada air sungai dapat menurunkan kandungan Cr(VI) lebih dari 75% dari hari ke-0 kandungan Cr(VI) sebesar 0,42 mg/L menjadi 0,10 mg/L pada hari ke-7. Namun, jika dilihat dari hasil penelitian maka kemampuandari kangkung air tidak signifikan, karena hanya dapat menyerap sebagian kecil dari Cr(VI). Sehingga dapat disimpulkan bahwa mikroorganisme dapat menurunkan kadar Cr(VI) lebih cepat dibandingkan kangkung air. Sedangkan pada hasil penelitian pH tetap dalam kondisi netral tidak mengalami perubahan yang signifikan. Kata kunci: colorimeter, limbah cair, logam berat, pH ABSTRACT Pollution in liquid waste containing Cr(VI) is a severe threat to environmental sustainability because apart from being a toxic pollutant to aquatic organisms, the pollutant also affects the aquatic environment's physical, chemical, and biological characteristics and has substances that can cause cancer. Water spinach plants (Ipomoea Aquatica Forsk) can potentially reduce Cr6+ content. So this study aims to determine the ability of water spinach to reduce Cr(VI) levels and the ability of microorganisms in river water to degrade Cr(VI) levels. This research was conducted periodically four times from days 0, 3, 5, and 7. In the first stage, the ability of microorganisms in river water to degrade heavy metals was analyzed by measuring the concentration of Cr(VI) using a colorimeter. The subsequent analysis measured the Cr(VI) concentration in water spinach plants. Based on the observations, it can be seen that microorganisms in river water can reduce the Cr(VI) content by more than 75% from the 0th day, the Cr(VI) content of 0.42 mg/L to 0.10 mg/L on the third day 7. However, from the research results, water spinach's ability is insignificant because it can only absorb a small portion of Cr(VI). So it can be concluded that microorganisms can reduce Cr(VI) levels faster than water spinach. Meanwhile, in the research results, the pH remained in a neutral condition and did not experience a significant change. Keywords: colorimeter, liquid waste, heavy metals, pH

This study was designed to determine the prevalence of Cryptosporidium infections in sheep herds around tributaries in Pakistan and to evaluate the influence of potential risk factors. In total, 448 samples from 26 sheep herds were screened microscopically and then confirmed through polymerase chain reaction (PCR) amplification of the 18S SSU rRNA gene. Our result revealed that, out of 448 samples, 107 were found positive by microscopy and 77 positive by PCR, with prevalence rates of 23.88% and 17.18% in different breeds of sheep. A high statistical difference exists between the p-value (p,0.05) when comparing diarrheic and non-diarrheic sheep, breeds, ages, genders, and seasons. The highest infection rate was found in the Australian breed (8.25%); season-wise, the highest prevalence was recorded in summer. Furthermore, sheep-secreting diarrheal faces were 41% young sheep and lambs. This reveals that young animals are more susceptible to infection than adults, and cryptosporidial infection decreases with increasing age of the animal. This report is the first on the prevalence of Cryptosporidium in sheep sampled near the tributaries in Pakistan. The implications of this study’s findings are clear; immediate action is necessary to prevent further spread and potentially devasting harm. [ABSTRACT FROM AUTHOR]

Objective: To compare the marginal integrity of Class-I amalgam and bonded amalgam restorations in maxillary and mandibular molars at seven days, three, six and twelve-months intervals. Study Design: Comparative prospective study. Place and Duration of Study: Department of Operative Dentistry, Armed Forces Institute of Dentistry, Rawalpindi Pakistan,from Jul 2017 to Jul 2018. Methodology: A total number of 114 patients of either gender with an age range of 14-45 years having Class-I cavities in first and second maxillary and mandibular molars on both sides were equally distributed in two groups. Group-A received conventional Amalgam, and Group-B received bonded amalgam restorations. All the fillings were placed and carved using routine instruments used for amalgam restorations, and the restorations were polished after 24 hours. The patients were initially evaluated for marginal ditching around restorations with the help of a dental mirror and explorer at seven days,followed by inspection at 3, 6 and 12 months. Results: Of the 114 participants, all showed excellent marginal integrity at seven-days intervals regardless of the restorative material used. However, marginal integrity deteriorated swiftly with time among those 57(50%) participants who acquired conventional Amalgam. Marginal integrity at 3, 6 and 12-months period was 51(89.5%), 35(61.4%) and 17(29.8%), respectively.Bonded amalgam restorations performed superiorly with 100%, 56(98.2%) and 43(75.4%) successful marginal integrity at 3, 6 and 12-months, respectively. Conclusion: Bonded amalgams can be a better substitute than non-bonded amalgam restorations with superior longevity in marginal integrity. Keywords: Amalgam, Bonded amalgam, Marginal integrity, Micro-leakage, Marginal deterioration, Restoration longevity.

Objective: To evaluate the diagnostic significance of reticulocyte maturity indices in iron deficiency anaemia. Study Design: Comparative cross-sectional study. Place and Duration of Study: Department of Hematology, Armed Forces Institute of Pathology, Rawalpindi, from Sep 2019 to Jun 2020. Methodology: A total of 340 children, ages between 1 and 5 years of either gender, were divided into two groups based on haemoglobin and ferritin level. Group A comprised of 203 children with haemoglobin >11 g/dL andferritin level >7 ng/ mL. Group B comprised of 137 children with haemoglobin 0.05) and significant differences were noted in terms of low, medium & high fluorescence ratios in both groups (p

Abstract Background Staphylococcus aureus (S. aureus) mastitis is one of the most difficult diseases to treat in lactating dairy cows worldwide. S. aureus with different lineages leads to different host immune responses. Long non-coding RNAs (lncRNAs) are reported to be widely involved in the progress of inflammation. However, no research has identified stable lncRNAs among different S. aureus strain infections. In addition, folic acid (FA) can effectively reduce inflammation, and whether the inflammatory response caused by S. aureus can be reduced by FA remains to be explored. Methods lncRNA transcripts were identified from Holstein mammary gland tissues infected with different concentrations of S. aureus (in vivo) and mammary alveolar cells (Mac-T cells, in vitro) challenged with different S. aureus strains. Differentially expressed (DE) lncRNAs were evaluated, and stable DE lncRNAs were identified in vivo and in vitro. On the basis of the gene sequence conservation and function conservation across species, key lncRNAs with the function of potentially immune regulation were retained for further analysis. The function of FA on inflammation induced by S. aureus challenge was also investigated. Then, the association analysis between these keys lncRNA transcripts and hematological parameters (HPs) was carried out. Lastly, the knockdown and overexpression of the important lncRNA were performed to validate the gene function on the regulation of cell immune response. Results Linear regression analysis showed a significant correlation between the expression levels of lncRNA shared by mammary tissue and Mac-T cells (P

Objective: To evaluate the performance of Nucleated RBC (NRBC) Count using a fully automated haematology analyzer versus manual counting. Study Design: Cross-Sectional Study. Place and Duration of Study: Department of Hematology, Armed Forces Institute of Pathology, from Sep 2019-Jun 2020. Methodology: Routine fresh whole blood samples were run on Sysmex XN-3000 automated haematology analyzer and 384 samples with results of ≥0.1% Nucleated red blood cells were included in this study. Manual NRBC counting was carried out twice on Leishman-stained peripheral blood smears from all 384 samples. Comparison between manual and automated nucleated red blood cell counting methods was statistically analyzed through linear regression analysis & coefficient correlation. The degree of agreement between two methods was analyzed through Bland-Altman plot. Finally, concordance between the two methods was also analyzed at 5 different ranges of nucleated red blood cells. Results: Linear regression analysis revealed a (r2) value of 0.97. Regression equation was calculated as XN = 0.76MC ± 1.28, with 95% limits of agreement between ± 40.42% and -24.47%. A mean bias of 7.97% was demonstrated through Bland-Altman plot. Concordance analysis revealed a concordance rate of 93.74% (360/384). Nucleated red blood cell counting between two methods were more concordant when nucleated red blood cell counts were

We detected Crimean-Congo hemorrhagic fever virus infections in 4 provinces of Pakistan during 2017–2018. Overall, seroprevalence was 2.7% in humans and 36.2% in domestic livestock. Antibody prevalence in humans was highest in rural areas, where increased contact with animals is likely.

A 1 × 4 planar fractal array antenna is designed and presented for millimeter-wave 5G applications. The array’s top side is made up of a rhombus-inscribed circular ring fractal patch radiator, while the backside is made up of a square notch-loaded partial ground plane. To achieve high gain, a 1 × 4 corporate feeding network is used to excite the array elements. The designed array has an overall size of 28 × 17.75 mm2. From simulations as well as experimental results, it is observed that the designed array offers a wide impedance bandwidth in the frequency range of 22.8–29.2 GHz. Furthermore, a peak gain of 10.7 dBi with a radiation efficiency of >95% is observed in the operating bandwidth.

Successfully evaluating and improving the salt tolerance of genotypes requires an appropriate analysis tool to allow simultaneous analysis of multiple traits and to facilitate the ranking of genotypes across different growth stages and salinity levels. In this study, we evaluate the salt tolerance of 56 recombinant inbred lines (RILs) in the presence of salt-tolerant and salt-sensitive control genotypes using multivariate analysis of plant dry weight, measured at 75 (PDW-75) and 90 (PDW-90) days from sowing, biological yield (BY), grain yield (GY), and their salt tolerance indices (STIs). All RILs and genotypes were evaluated under the control and 15 dS m−1 for two consecutive years (2019/2020 and 2020/2021). Results showed significant main effects of salinity and genotype as well as their interactions on four plant traits. Significant genotypic differences were also found for all calculated STIs. STIs exhibited moderate to strong relationships with the four plant traits when measured under either the control or salinity conditions and between each other. The principal component analysis (PCA) showed that the most variation among all analyzed variables was explained by the first two PCs, with the PC1 and PC2 explained at 61.8–71.8% and at 28.0–38.2% of the total variation, respectively. The PC1 had positive and strong correlations with the four plant traits measured under salinity conditions and STI, YI, REI, SWPI, MRPI, MPI, GMPI, and HMPI. The PC2 had strong correlations with BY and GY measured under the control conditions and SSI, TOL, RSE, and YSI. The PC1 was able to identify the salt-tolerant genotypes, while the PC2 was able to isolate the salt-sensitive ones. Cluster analysis based on multiple traits organized 64 genotypes into four groups varied from salt-tolerant to salt-sensitive genotypes, with the salt-tolerant group attaining higher value for plant traits under salinity conditions and the STIs related to the PC1. In conclusion, the use of multivariate analysis together with the STIs that evaluated the performance of genotypes under contrasting environmental conditions will help breeders to distinguish salt-tolerant genotypes from salt-sensitive ones, even at the early growth stages of plant development.

Assessment of the salt tolerance of a large genotype collection at the early growth stages may assist in the fast-tracking improvement of salt-tolerant barley genotypes in breeding programs. This study aimed to investigate the ability of traits related to seed germination ability and seedling growth performance with helping of nine sequence-related amplified polymorphism (SRAP) markers to detect the salt tolerance of 70 barley genotypes during the early growth stages. The different genotypes were exposed to three salt concentrations (0, 100, and 200 mM NaCl) and evaluated for salt tolerance by looking at germination percentage, germination index, and mean germination time during eight days as well as the lengths and weights of seedling shoot and root after 21 days from sowing. The results showed that genotypic variations in germination ability and seedling growth performance obviously appeared under 200 and 100 mM NaCl, respectively. The germination traits exhibited a strong correlation among themselves, whereas they had a poor correlation with seedling traits. A strong and positive correlation was only observed for shoot fresh weight with shoot length and root fresh weight under salinity conditions. Principal component analysis revealed that the first two components, which explained 53% of the total variability, succeeded to identify the genotypes with high salt tolerance during only one stage (germination or seedling stage) and both stages. Cluster analysis based on the stress tolerance index of germination and seedling traits grouped 70 genotypes into four key clusters, with genotypes grouped in cluster 1 and cluster 2 being salt tolerant during the germination stage and moderately tolerant during the seedling stage; the opposite was found with the genotypes grouped in cluster 4. According to Ward’s method, the salt tolerance of genotypes that ranked as most salt-tolerant (T) or salt-sensitive (S) remained almost unchanged during germination and seedling stages. In contrast, a change in salt tolerance with both stages was found for the genotypes that ranked as moderately salt-tolerant (MT) and salt-sensitive (MS) genotypes. The nine SRAP markers divided the tested genotypes into two distinct clusters, with clusters B had the most T and MT genotypes. Finally, using appropriate statistical methods presented in this study with SRAP markers will be useful for assessing the salt tolerance of a large number of barley genotypes and selecting the genotypes tolerant of and sensitive to salinity at the early growth stage.

Bovine mastitis is a widespread and costly disease that affects dairy farming globally, characterized by mammary gland inflammation. Bovine intramammary gland infection has been associated with more than 135 different pathogens of which Staphylococcus aureus is the main etiology of sub-clinical mastitis (SCM). The current study was designed to investigate the prevalence, antibiotic resistance pattern, and the presence of antibiotic resistance genes (mecA, tetK, aacA-aphD and blaZ) in S. aureus isolated from the raw milk of cows with subclinical mastitis. A total of 543 milk samples were collected from lactating cows such as Holstein Friesian (n = 79), Sahiwal (n = 175), Cholistani (n = 107), and Red Sindhi (n = 182) from different dairy farms in Pakistan. From the milk samples microscopic slides were prepared and the somatic cell count was assessed to find SCM. To isolate and identify S. aureus, milk was streaked on mannitol salt agar (MSA) plates. Further confirmation was done based on biochemical assays, including gram staining (+ coccus), catalase test (+), and coagulase test (+). All the biochemically confirmed S. aureus isolates were molecularly identified using the thermonuclease (nuc) gene. The antibiotic resistance pattern of all the S. aureus isolates was evaluated through the disc diffusion method. Out of 543 milk samples, 310 (57.09%) were positive for SCM. Among the SCM-positive samples, S. aureus was detected in 30.32% (94/310) samples. Out of 94 isolates, 47 (50%) were determined to be multidrug resistant (MDR). Among these MDR isolates, 11 exhibited resistance to Cefoxitin, and hence were classified as methicillin-resistant Staphylococcus aureus (MRSA). The S. aureus isolates showed the highest resistance to Lincomycin (84.04%) followed by Ampicillin (45.74%), while the least resistance was shown to Sulfamethoxazole/Trimethoprim (3.19%) and Gentamycin (6.38%). Polymerase chain reaction (PCR) analysis revealed that 55.31% of the isolates carried blaZ gene, 46.80% carried tetK gene, 17.02% harbored the mecA gene, whereas, aacA-aphD gene was found in 13.82% samples. Our findings revealed a significant level of contamination of milk with S. aureus and half (50%) of the isolates were MDR. The isolated S. aureus harbored various antibiotic resistance genes responsible for the absorbed phenotypic resistance. The alarmingly high prevalence of MDR S. aureus isolates and MRSA strains in these cases possess a serious risk to public health, emphasizes the urgent need to address this issue to protect both human and animal health in Pakistan. [ABSTRACT FROM AUTHOR]

Brucellosis is reportedly endemic in ruminants in Pakistan. Both Brucella abortus and B. melitensis infections have been decumented in domestic animals and humans in the country. This study aimed to identify the burden of anti-Brucella antibodies in small ruminants as well as associated potential risk factors with its occurrence at nine institutional livestock farms in Punjab, Pakistan. The sera collected from equal number of sheep and goats (500 from each species) were screened by indirect-ELISA for anti-smooth-Brucella antibodies followed by a serial detection by real-time PCR. Overall, 5.1% (51/1000) seropositivity was registered corresponding to 5% (25/500) prevalence in goats and 5.2% (26/500) in sheep. Brucella-DNA could not be detected in any of the tested sera by real-time PCR. Multiple logistic regression model indicated that farm location (OR 34.05), >4 years of age (OR 2.88), with history of reproductive disorders (OR 2.69), and with BCS of ≤ 3 (OR 12.37) were more likely to test positive for brucellosis at these farms. A routine screening, stringent biosecurity, and quarantine measures are warranted for monitoring and eradication of the infection. Similarly, isolation and molecular investigation of the etiologic agent(s) are needed to understand the relationship of epidemiology and out-breaks of brucellosis in the country.

Although plant chlorophyll (Chl) is one of the important elements in monitoring plant stress and reflects the photosynthetic capacity of plants, their measurement in the lab is generally time- and cost-inefficient and based on a small part of the leaf. This study examines the ability of canopy spectral reflectance data for the accurate estimation of the Chl content of two wheat genotypes grown under three salinity levels. The Chl content was quantified as content per area (Chl area, μg cm−2), concentration per plant (Chl plant, mg plant−1), and SPAD value (Chl SPAD). The performance of spectral reflectance indices (SRIs) with different algorithm forms, partial least square regression (PLSR), and stepwise multiple linear regression (SMLR) in estimating the three units of Chl content was compared. Results show that most indices within each SRI form performed better with Chl area and Chl plant and performed poorly with Chl SPAD. The PLSR models, based on the four forms of SRIs individually or combined, still performed poorly in estimating Chl SPAD, while they exhibited a strong relationship with Chl plant followed by Chl area in both the calibration (Cal.) and validation (Val.) datasets. The SMLR models extracted three to four indices from each SRI form as the most effective indices and explained 73–79%, 80–84%, and 39–43% of the total variability in Chl area, Chl plant, and Chl SPAD, respectively. The performance of the various predictive models of SMLR for predicting Chl content depended on salinity level, genotype, season, and the units of Chl content. In summary, this study indicates that the Chl content measured in the lab and expressed on content (μg cm−2) or concentration (mg plant−1) can be accurately estimated at canopy level using spectral reflectance data.

An area of growing interest in wheat-breeding programs for abiotic stresses is the accurate and expeditious phenotyping of large genotype collections using nondestructive hyperspectral sensing tools. The main goal of this study was to use data from canopy spectral signatures (CSS) in the full-spectrum range (400–2500 nm) to estimate and predict the plant biomass dry weight at booting (BDW-BT) and anthesis (BDW-AN) growth stages, and biological yield (BY) of 64 spring wheat germplasms exposed to 150 mM NaCl using 13 spectral reflectance indices (SRIs, consisting of seven vegetation-related SRIs and six water-related SRIs) and partial least squares regression (PLSR). SRI and PLSR performance in estimating plant traits was evaluated during two years at BT, AN, and early milk grain (EMG) growth stages. Results showed significant genotypic differences between the three traits and SRIs, with highly significant two-way and three-way interactions between genotypes, years, and growth stages for all SRIs. Genotypic differences in CSS and the relationships between the three traits and a single wavelength over the full-spectrum range depended on the growth stage. Water-related SRIs were more strongly correlated with the three traits compared with vegetation-related SRIs at the BT stage; the opposite was found at the EMG stage. Both types of SRIs exhibited comparable associations with the three traits at the AN stage. Principal component analysis indicated that it is possible to assess plant biomass variations at an early stage (BT) through published and modified SRIs. SRIs coupled with PLSR models at the BT stage exhibited good prediction capacity of BDW-BT (57%), BDW-AN (82%), and BY (55%). Overall, results demonstrated that the integration of SRIs and multivariate models may present a feasible tool for plant breeders to increase the efficiency of the evaluation process and to improve the genetics for salt tolerance in wheat-breeding programs.

The incorporation of stress tolerance indices (STIs) with the early estimation of grain yield (GY) in an expeditious and nondestructive manner can enable breeders for ensuring the success of genotype development for a wide range of environmental conditions. In this study, the relative performance of GY for sixty-four spring wheat germplasm under the control and 15.0 dS m−1 NaCl were compared through different STIs, and the ability of a hyperspectral reflectance tool for the early estimation of GY and STIs was assessed using twenty spectral reflectance indices (SRIs; 10 vegetation SRIs and 10 water SRIs). The results showed that salinity treatments, genotypes, and their interactions had significant effects on the GY and nearly all SRIs. Significant genotypic variations were also observed for all STIs. Based on the GY under the control (GYc) and salinity (GYs) conditions and all STIs, the tested genotypes were classified into three salinity tolerance groups (salt-tolerant, salt-sensitive, and moderately salt-tolerant groups). Most vegetation and water SRIs showed strong relationships with the GYc, stress tolerance index (STI), and geometric mean productivity (GMP); moderate relationships with GYs and sometimes with the tolerance index (TOL); and weak relationships with the yield stability index (YSI) and stress susceptibility index (SSI). Obvious differences in the spectral reflectance curves were found among the three salinity tolerance groups under the control and salinity conditions. Stepwise multiple linear regressions identified three SRIs from each vegetation and water SRI as the most influential indices that contributed the most variation in the GY. These SRIs were much more effective in estimating the GYc (R2 = 0.64 − 0.79) than GYs (R2 = 0.38 − 0.47). They also provided a much accurate estimation of the GYc and GYs for the moderately salt-tolerant genotype group; YSI, SSI, and TOL for the salt-sensitive genotypes group; and STI and GMP for all the three salinity tolerance groups. Overall, the results of this study highlight the potential of using a hyperspectral reflectance tool in breeding programs for phenotyping a sufficient number of genotypes under a wide range of environmental conditions in a cost-effective, noninvasive, and expeditious manner. This will aid in accelerating the development of genotypes for salinity conditions in breeding programs.

Now a days a country cannot become economically strong until and unless it has enough electrical power to fulfil industrial and domestic needs. Electrical power being the pillar of any country’s economy, needs to be used in an efficient way. The same step is taken here by proposing a new system for energy distribution from substation to consumer houses, also it monitors the consumer consumption and record data. Unlike traditional manual Electrical systems, pervasive electricity distribution system (PEDS) introduces a fresh perspective to monitor the feeder line status at distribution and consumer level. In this system an effort is taken to address the issues of electricity theft, manual billing, online monitoring of electrical distribution system and automatic control of electrical distribution points. The project is designed using microcontroller and different sensors, its GUI is designed in Labview software.

In the petroleum industry, the researchers have developed a new technique called enhanced oil recovery to recover the remaining oil in reservoirs. Some reservoirs are very complex and require advanced enhanced oil recovery (EOR) techniques containing new materials and additives in order to produce maximum oil in economic and environmental friendly manners. In this work, the effects of nanosuspensions (KY-200) and polymer gel HPAM (854) on oil recovery and water cut were studied in the view of EOR techniques and their results were compared. The mechanism of nanosuspensions transportation through the sand pack was also discussed. The adopted methodology involved the preparation of gel, viscosity test, and core flooding experiments. The optimum concentration of nanosuspensions after viscosity tests was used for displacement experiments and 3 wt % concentration of nanosuspensions amplified the oil recovery. In addition, high concentration leads to more agglomeration; thus, high core plugging takes place and diverts the fluid flow towards unswept zones to push more oil to produce and decrease the water cut. Experimental results indicate that nanosuspensions have the ability to plug the thief zones of water channeling and can divert the fluid flow towards unswept zones to recover the remaining oil from the reservoir excessively rather than the normal polymer gel flooding. The injection pressure was observed higher during nanosuspension injection than polymer gel injection. The oil recovery was achieved by about 41.04% from nanosuspensions, that is, 14.09% higher than polymer gel. Further investigations are required in the field of nanoparticles applications in enhanced oil recovery to meet the world's energy demands.

Simultaneous and timely assessment of growth and water status-related plant traits is critical for precision irrigation management in arid regions. Here, we used proximal hyperspectral sensing tools to estimate biomass fresh weight (BFW), biomass dry weight (BDW), canopy water content (CWC), and total tuber yield (TTY) of two potato varieties irrigated with 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). Plant traits were assessed remotely using published and newly constructed vegetation and water spectral reflectance indices (SRIs). We integrated genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS) models to predict the measured traits based on all SRIs. The different plant traits and SRIs varied significantly (p < 0.05) between the three irrigation regimes for the two varieties. The values of plant traits and majority SRIs showed a continuous decrease from the 100% ETc to the 50% ETc. Water-SRIs performed better than vegetation-SRIs for estimating the four plant traits. Almost all indices of the two SRI types had a weak relationship with the four plant traits (R2 = 0.00–0.37) under each irrigation regime. However, the majority of vegetation-SRIs and all water-SRIs showed strong relationships with BFW, CWC, and TTY (R2 ≥ 0.65) and moderate relationships with BDW (R2 ≥ 0.40) when the data of all irrigation regimes and varieties were analyzed together for each growing season or the data of all irrigation regimes, varieties, and seasons were combined together. The ANFIS-GA model predicted plant traits with satisfactory accuracy in both calibration (R2 = 1.0) and testing (R2 = 0.72–0.97) modes. The results indicate that SRI-based ANFIS models can improve plant trait estimation. This analysis also confirmed the benefits of applying GA to ANFIS to estimate plant responses to different growth conditions.

The application of proximal hyperspectral sensing, using simple vegetation indices, offers an easy, fast, and non-destructive approach for assessing various plant variables related to salinity tolerance. Because most existing indices are site- and species-specific, published indices must be further validated when they are applied to other conditions and abiotic stress. This study compared the performance of various published and newly constructed indices, which differ in algorithm forms and wavelength combinations, for remotely assessing the shoot dry weight (SDW) as well as chlorophyll a (Chla), chlorophyll b (Chlb), and chlorophyll a+b (Chlt) content of two wheat genotypes exposed to three salinity levels. Stepwise multiple linear regression (SMLR) was used to extract the most influential indices within each spectral reflectance index (SRI) type. Linear regression based on influential indices was applied to predict plant variables in distinct conditions (genotypes, salinity levels, and seasons). The results show that salinity levels, genotypes, and their interaction had significant effects (p ≤ 0.05 and 0.01) on all plant variables and nearly all indices. Almost all indices within each SRI type performed favorably in estimating the plant variables under both salinity levels (6.0 and 12.0 dS m−1) and for the salt-sensitive genotype Sakha 61. The most effective indices extracted from each SRI type by SMLR explained 60%–81% of the total variability in four plant variables. The various predictive models provided a more accurate estimation of Chla and Chlt content than of SDW and Chlb under both salinity levels. They also provided a more accurate estimation of SDW than of Chl content for salt-tolerant genotype Sakha 93, exhibited strong performance for predicting the four variables for Sakha 61, and failed to predict any variables under control and Chlb for Sakha 93. The overall results indicate that the simple form of indices can be used in practice to remotely assess the growth and chlorophyll content of distinct wheat genotypes under saline field conditions.

Proximal hyperspectral sensing tools could complement and perhaps replace destructive traditional methods for accurate estimation and monitoring of various morpho-physiological plant indicators. In this study, we assessed the potential of thermal imaging (TI) criteria and spectral reflectance indices (SRIs) to monitor different vegetative growth traits (biomass fresh weight, biomass dry weight, and canopy water mass) and seed yield (SY) of soybean exposed to 100%, 75%, and 50% of estimated crop evapotranspiration (ETc). These different plant traits were evaluated and related to TI criteria and SRIs at the beginning bloom (R1) and full seed (R6) growth stages. Results showed that all plant traits, TI criteria, and SRIs presented significant variations (p < 0.05) among irrigation regimes at both growth stages. The performance of TI criteria and SRIs for assessment of vegetative growth traits and SY fluctuated when relationships were analyzed for each irrigation regime or growth stage separately or when the data of both conditions were combined together. TI criteria and SRIs exhibited a moderate to strong relationship with vegetative growth traits when data from different irrigation regimes were pooled together at each growth stage or vice versa. The R6 and R1 growth stages are suitable for assessing SY under full (100% ETc) and severe (50% ETc) irrigation regimes, respectively, using SRIs. The overall results indicate that the usefulness of the TI and SRIs for assessment of growth, yield, and water status of soybean under arid conditions is limited to the growth stage, the irrigation level, and the combination between them.

Field-based trials and genotype evaluation until yielding stage are two important steps in improving the salt tolerance of crop genotypes and identifying what parameters can be strong candidates for the better understanding of salt tolerance mechanisms in different genotypes. In this study, the salt tolerance of 18 bread wheat genotypes was evaluated under natural saline field conditions and at three saline irrigation levels (5.25, 8.35, and 11.12 dS m−1) extracted from wells. Multidimensional evaluation for salt tolerance of these genotypes was done using a set of agronomic and physio-biochemical attributes. Based on yield index under three salinity levels, the genotypes were classified into four groups ranging from salt-tolerant to salt-sensitive genotypes. The salt-tolerant genotypes exhibited values of total chlorophyll, gas exchange (net photosynthetic rate, transpiration rate, and stomatal conductance), water relation (relative water content and membrane stability index), nonenzymatic osmolytes (soluble sugar, free proline, and ascorbic acid), antioxidant enzyme activities (superoxide dismutase, catalase, and peroxidase), K+ content, and K+/Na+ ratio that were greater than those of salt-sensitive genotypes. Additionally, the salt-tolerant genotypes consistently exhibited good control of Na+ and Cl− levels and maintained lower contents of malondialdehyde and electrolyte leakage under high salinity level, compared with the salt-sensitive genotypes. Several physio-biochemical parameters showed highly positive associations with grain yield and its components, whereas negative association was observed in other parameters. Accordingly, these physio-biochemical parameters can be used as individual or complementary screening criteria for evaluating salt tolerance and improvement of bread wheat genotypes under natural saline field conditions.