Screen house leaf cage experiments were conducted under no-choice conditions to ascertain the antibiosis mechanism operating in introgression cotton lines against the whitefly, Bemisia tabaci (Gennadius) during July and September 2022. Seventeen cotton introgression lines and two parents, namely Synthetic polyploid (A2D1) and upland cotton line PIL 43, were assessed for development and survival of various biological parameters like fecundity, nymphal and pupal growth index. An antibiosis mechanism of resistance was documented in the parent, Synthetic polyploid and introgression lines, D5-BW-WF-28, C1-P-1, C1-P-31, and C1-P-36, and were categorized as resistant lines. In resistant introgression lines, survival and the nymphal/pupal growth index were lower, but the overall development period was longer. Among biophysical parameters, trichome density, leaf area and vascular bundle length showed significantly positive whereas leaf lamina thickness exhibited negative association with fecundity. Sugars were found to be higher in susceptible genotypes whereas phenols and proteins were comparatively higher in resistant lines. However, total soluble and reducing sugars showed a positive correlation, while total soluble proteins and total phenols manifested a negative correlation with fecundity. It may thus be concluded that antibiosis mechanism of resistance is operating in cotton introgression lines; and biophysical and biochemical parameters play a predominant role in imparting resistance against B. tabaci. To the best of our knowledge, this is the first report illustrating the development of whitefly resistant introgression lines using Synthetic cotton polyploid (A2D1).

Stub loaded pocket-shaped fractal antenna (PSFA) with defected ground structure of volumetric dimensions 32 x 36 x 1.6 mm(3) for UWB technology has been presented in this manuscript. Proposed structure exhibits improved impedance bandwidth in juxtaposition to other geometries like antenna with partial ground plane and ground plane with defects. Ground plane of proposed antenna has been modified for attaining the improved results. Finally, the structure of antenna with modified ground plane reveals the wider impedance bandwidth of 11.80 GHz (149.36%) and 5.33 GHz (30.75%) in the frequency range from 2.0 to 13.80 GHz and 14.67 to 20.0 GHz, respectively. The peak gain of antenna is also computed and divulged as 7.02 dB at 9.7 GHz frequency band. The co- and cross-polarisation radiation patterns in E- and H-plane of proposed antenna are measured and presented at frequency points 3.0, 4.9, 7.3, 8.8, 10.2, 13.0, 16.6 and 19.4 GHz. Proposed antenna has been simulated and its performance is also being investigated using HFSS V13 simulator. Further, optimised antenna geometry is fabricated, and fair comparison between simulated and measured results has been drawn and divulged in reasonable agreement with each other. The proposed antenna has reported the wider bandwidth which made it a suitable candidate for distinct wireless applications in the UWB frequency range.

There has been renowned focus on applying ML techniques to neurodegenerative disorders in recent years. Dementia is one of these new world wide health problems, and early diagnosis of it is particularly beneficial. Alzheimer’s disease (AD) is the most frequent kind of dementia. The areas of the brain that are generally affected by dementia are those that affect a person’s ability to think, retain information, and communicate. An investigation of the similarities and differences between several different ML algorithms, including Convolutional Neural Networks (CNN), Random Forest, Support Vector Machine (SVM), and others. It reports a split-half resampling examination of many data-driven feature selection and classification strategies for whole-brain voxel-based classification of Magnetic Resonance Imaging (MRI) scans. A comparative examination of all the other ML approaches reveals that the SVM methodology predicts greater accuracy (97%), higher specificity (100%), and higher sensitivity (45%) for the diagnosis of dementia than any of the other techniques.

Fracture of the long bone is a commonly encountered orthopaedic problem in canine practice (Aithal et al.,1999). Femur fractures are one of the most common orthopaedic affections encountered in dogs comprising 35 % of hind limb fractures and 24 %of all fractures in dogs (Johnson et al., 1998). Proximal and distal epiphyseal fractures happen in young animals, whereas diaphyseal and metaphyseal fractures are more frequent in older animals(Guiot et al., 2012, Abd El Raouf, 2017). They are difficult to repair due to the fact that such dogs are recumbent and need early rehabilitation to establish speedy recovery. The closeness of the abdominal wall to the proximal femur and surrounding heavy muscles limits the use of coaptation and external skeletal fixation for femoral fractures.

Across industries, ROBOTS are frequently utilized. A significant part of the numerous uses of robotics and many countries deciding that whether it’s possible to give identity to the anthropomorphic robots. Different industries hospitals are using the robots. The robots are not limited to these two applications even different sectors are using the different robots according to their needs. Mostly robots are performing the tasks which are difficult for human being. The basic robotic arms, known as three link manipulators, are still in use in micro-to-macro applications, such as chip production. In the field of robotics, robotic instrumentation is essential because without sensors, actuators, and detectors, robots cannot interact with their surroundings. In this paper soft computing also discussed in detail. In this paper the disturbance occur in the closed loop also being discussed. There have been tests, comparisons, and simulations done.GA doesn’t have to be an expert in the system. Even in cases when the population is quite big, the evolutionary process converges too soon. The robotic arm reaches the desired location within the simulated time, demonstrating good performance. Since the evolution function thoroughly tests all potential input spaces, the performance is ideal across the board. Soft computing help in trajectory planning and obstacle avoidance has been discussed in detail. The role of hybrid techniques also discussed. The dynamic nature of the robot also been discussed in detail in this paper. The paper has been sub parted in 9 parts and the modelling of the 2,3, and 5 DOF robots has been discussed din detail.

Mulching is being widely utilized for production of various crops worldwide and it has a great impact on crop growth and yield. In this regard, the present investigation was carried out to determine the effects of various mulch materials on growth and yield of summer squash (Cucurbita pepo L.) during, 2021 in Agricultural fields of Lovely Professional University, Punjab. Different mulch materials viz., compost, dry leaves, paddy straw, saw dust, sugarcane trash, black polyethylene mulch, transparent mulch and without mulch as control were used for the investigation. Among the different mulches, black polyethylene mulch recorded significantly highest plant height, number of leaves per plant, plant spread and days to 50% female flower. Correspondingly, the highest yield attributes viz., average fruit length, average fruit width, average fruit weight and number of fruits per plant with the highest yield per plant (3.82 kg), yield per plot (68.14 kg) and total fruit yield (27.25 t ha-1) were recorded by black polyethylene mulch compare to the control. Based on the study, it is revealed that black polyethylene mulch is the most eco-friendly method for growing and developing of summer squash.

This paper addresses the robotics and artificial intelligence (AI). In many field applications where, technical support is required, man can be in danger while handling work. In such situation, the robotics arm manipulator is commonly used. With the rapid progress in AI research, new perspectives in industrial robot control strategies have emerged, and prospects towards cognitive robots have arisen. AI-based robotic systems are strongly becoming one of the main areas of focus, as flexibility and deep understanding of complex manufacturing processes are becoming the key advantage to raise competitiveness. They are on the great demand to speed up the automation process. Robotic with AI plays a vital role in robotics world, without these robots are not able to interact with the surrounding environment.

Population of world is increasing at alarming rate which has led to large scale urbanization. For this, construction activities over expansive soil has increased in last decade. For stability and reliability of any structure on the poor soil, bearing capacity of soil should be enhanced for structural security. In this research, the influence of two additives Poly Vinyl Acetate (PVAc) and Glass fiber were used on expansive clayey soils for engineering properties examined.The impact of polymers with fiber on the unconfined compression strength and free swell index of the prepared soil was assessed. PVAc added in dosage of 0%, 2%, 4% and 5%, also the Glass fibers are added in proportions of 0.25% and 0.50%. Soil samples with glass fiber are cured for 1 and 14 days. Outcome of UCS tests on stabilized expansive clay samples with different PVAc together with fiber contents after curing for 1 and 14 days stated that such hydrophilic polymers significantly enhance the compressive strength of expansive clay soils. It also increases their strength with curing period. Soil behavior changes from fragile to ductile with the addition of glass fiber and increasing resistance at the identical time are important advantages in developed clay. The reduction in free swell index occurred due to physiochemical connection which moderate the potential expansion of the soil. The effectiveness of the additives however, depends greatly on the soil type, fiber length and testing conditions.

β-defensins are adsorbable on the sperm surface in the male reproductive tract (MRT) and enhance sperm functional characteristics. The beta-defensin 129 (DEFB129) antimicrobial peptide is involved in sperm maturation, motility, and fertilization. However, its role in bovine fertility has not been well investigated. This study examines the relationship between the bovine BBD129 gene and Bos indicus x Bos taurus bull fertility. The complete coding sequence of BBD129 mRNA was identified by RNA Ligase Mediated-Rapid Amplification of cDNA End (RLM-RACE) and Sanger sequencing methodologies. It consisted of 582 nucleotides (nts) including 5' untranslated region (UTR) (46nts) and 3'UTR (23nts). It conserves all beta-defensin-like features. The expression level of BBD129 was checked by RT-qPCR and maximal expression was detected in the corpus-epididymis region compared to other parts of MRT. Polymorphism in BBD129 was also confirmed by Sanger sequencing of 254 clones from 5 high fertile (HF) and 6 low fertile (LF) bulls at two positions, 169 T > G and 329A > G, which change the S57A and N110S in the protein sequence respectively. These two mutations give rise to four types of BBD129 haplotypes. The non-mutated TA-BBD129 (169 T/329A) haplotype was substantially more prevalent among high-fertile bulls (P < 0.005), while the double-site mutated GG-BBD129 (169 T > G/329A > G) haplotype was significantly more prevalent among low-fertile bulls (P < 0.005). The in silico analysis confirmed that the polymorphism in BBD129 results in changes in mRNA secondary structure, protein conformations, protein stability, extracellular-surface availability, post-translational modifications (O-glycosylation and phosphorylation), and affects antibacterial and immunomodulatory capabilities. In conclusion, the mRNA expression of BBD129 in the MRT indicates its region-specific dynamics in sperm maturation. BBD129 polymorphisms were identified as the deciding elements accountable for the changed proteins with impaired functionality, contributing to cross-bred bulls' poor fertility.

In industrial applications and automation, the robotic manipulators exhibit a significant role. Several complex robotic systems performed a number of industrial works named spray painting, welding, assembly, pick and place action, etc. The end-effector’s position and the joint angles play a vital role since any task is activated inside the pre-defined robotic manipulator’s work space. Also, the problem of trajectory planning is a very challenging task in the robotic fields. To solve these problems, this paper proposes a kinematics analysis and trajectory planning of an Industrial robotic manipulators (IRMs) based on the hybrid optimization algorithms. Here, three IRMs such as PUMA 560 (6 DOF), KUKA LBR iiwa 14 R820 (7DOF) and ABB IRB 140 (6DOF) are considered. For each robot, the forward and the inverse kinematics (IK) are analysed and also the trajectory planning of each robot is discussed using the hybrid optimization algorithms. In this work, 18 optimization algorithms such as PSO (particle swarm optimization), SSO (social spider optimization), DFO (dragonfly optimization), BOA (butterfly optimization), CSA (crow search algorithm), BSA (bird swarm algorithm), SHO (selfish herd optimization), KHO (krill herd optimization), ALO (antlion optimization), ACO (ant colony optimization), GWO (Grey wolf optimization), GOA (grasshopper optimization), SBO (satin bowerbird optimizer), WCO (world cup optimization), COA (cuckoo optimization algorithm), CFA (cuttlefish algorithm), SOA (seagull optimization algorithm), and TSA (tunicate swarm algorithm) are utilized for both forward and inverse kinematic analysis and the trajectory planning problem. For the PUMA 560, KUKA LBR iiwa 14 R820, and ABB IRB 140 IRMs, forward kinematics (FK) are solved by the hybrid combination of PSO-SSO, SHO-KHO, and SBO-WCO individually. Also, the IK are solved by the DFO-BOA, ALO-ACO and COA-CFA for each IRMs. The trajectory planning problem is solved by the CSA-BSA, GWO-GOA and SOA-TSA for each robot individually. These optimization techniques give number of solution for kinematics and trajectory problem but it converses the best solution for the minimum multi-objective function value. Each robot obtained the minimum travelling time for without and with an obstacle which is 0.0118 and 0.0313 s for PUMA and 0.0117 and 0.0310 s for KUKA, and 0.0114 and 0.0120 s for ABB IRB 140 robot. The advantages of these hybrid algorithm are shorter computation time, and fewer iterations. The kinematics and trajectory analysis of each IRM is simulated using robotic tool box in MATLAB with GUI interface. For each IRM, optimized position values of the end effector, joint angles and the best optimal path are computed with minimum objective function. Finally, the performance of each robot is compared to the existing robotic works.

In this paper, an optimal collision-free trajectory is developed based on the hybrid optimization algorithms for industrial robotic manipulators (IRMs). Three IRMs such as PUMA 560 (six degrees of freedom-6DOF), KUKA LBR iiwa 14 R820 (7DOF), and ABB IRB 140 (6DOF) are considered. The key objective is to enhance the smoothness and efficiency of manufacturing robots by optimum joint trajectory design using the seventh-order polynomial function. The proposed approach is to solve both kinematics and trajectory planning problems by using the different combinations of the hybrid meta-heuristic algorithms. The kinematic parameters including jerk, acceleration, and velocity mostly impact the travel smoothness of the robot end-effector on the trajectory path. Therefore, these parameters are to be constrained for generating the collision-free path. The endurance of velocity and acceleration can be obtained by reducing the jerk which leads to smooth robotic motion. The proposed work is executed using a robotic toolbox in MATLAB with a graphical user interface. The values of acceleration, velocity, and jerk are computed for the robot joints. Each robot obtained the minimum traveling time for without and with an obstacle which is 0.0118 and 0.0313 s for PUMA and 0.0117 and 0.0310 s for KUKA, and 0.0114 and 0.0120 s for ABB IRB 140 robot. From the experimental outcomes, the proposed scheme of the hybrid optimization algorithms is more effective for the trajectory planning of IRMs than that of other works.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%–80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

Choke or esophageal foreign body obstruction is common condition in cow due to indiscriminate feeding habits. The most common site of obstruction is caudal cervical esophagus. A 7 year old, crossbred cow was presented with a history of sudden onset of ptyalism, bloated abdomen, respiratory distress, restlessness and swollen caudo-ventral cervical part. Physical examination of cervical region revealed partially movable, two round hard masses. Survey radiography showed two spherical (ball) like structures (6.83⁎6.11cm) at the level of C3-C4 and C5-C6 verterbral junction with an outer radiopaque wall and inner radiolucent part. The manual method of pushing foreign body into abdomen using probang and removal through oral cavity was failed due to complete intraluminal obstruction. Left cervical esophagotomy was performed and two trichobezoars (balls) were retrieved. This surgery proved excellent resolution of clinical signs.

In this paper, the inverse kinematics of more advanced degree of freedom robot is computed with the support of MATLAB. This paper deals with the study of control modeling of the KUKA robot. The path planning of robot end effector has been a research area for years. In this paper the new hybrid optimization techniques are used to solve the forward and inverse kinematics solution of KUKA LBR iiwa 14 R820. For Forward Kinematics SHO (selfish herd optimization), KHO (krill herd optimization)hybrid optimization technique is used and for Inverse Kinematics, hybrid ALO (ant lion optimization), ACO (ant colony optimization) technique is used. This proposed work also incorporates the itinerary of the robot in a workspace area with multiple obstacles by using a Hybrid GWO (Grey wolf optimization), GOA (grasshopper optimization). The optimized route discovered by applying the hybrid optimizer is energy efficient. Graphic User Interface is used to strut the optimized path into 3-Dimensional form. Forged consequences are administered to exemplify the effeteness and virtue of the propounding method. While using the different optimizing techniques the optimized path is found, with obstacle and without obstacle with less execution time and in less number of iterations. The Graphic user Interface is used to represent the different paths. In this work, the multi-objective functions such as collision free motion, jerk, travelling time and acceleration are considered for the planning of trajectory of the robot manipulator. The fitness function is reducing the multi-objective function.

Background: The male reproductive specific class-A β-defensins are adsorbed on sperm surface and enrich sperm functioning thus considered vital for maintaining male fertility. The primate DEFB129 play role in sperm maturation, motility, and fertilization but its contribution to bovine fertility is still unexplored. Method : RLM-RACE and RT-qPCR approaches were used to characterize and expression analysis of Indian cattle BBD129 gene. The polymorphism analysis of the BBD129 gene was done by PCR, sequencing, and absolute RT-qPCR on sperm gDNA from distinct fertility cattle bulls. Bioinformatic analysis was performed to understand the structural and functional implications of SNP on BBD129 protein. Results: The complete coding sequence of the BBD129 gene consists of 582 bp mRNA including UTRs and conserves all beta-defensin-like characteristics. Sequencing results revealed two conserved non-synonymous T169G (rs378737321, S57A) and A329G (rs383285978, N110S) SNPs in the functional protein-coding exon. Based on SNP position and linkage, BBD129 gene haplotypes were categorized into four groups: TA haplotype (169T & 329A), GA haplotype (T169G polymorphism), TG haplotype (A329G polymorphism), and GG haplotype (when T169G & A329G polymorphisms present together). The frequencies distributions of BBD129 haplotypes in the high fertile group (n=105 clones) were: TA (71.42%), GA (1.90%), TG (2.8%), and GG (24.76%), while in the low fertile group of bulls, the frequencies distributions of observed BBD129 haplotypes (n=149 clones) were: TA (36.24%), GA (0%), TG (2.68%), and GG (61.07%). The distributions of TA haplotype were majorly distributed in bulls with a high conception rate (P=0.5256) while double mutated GG haplotype was significantly more abundant in bulls with a lower conception rate (P=0.0001). BBD129 exist as a single-copy gene in the bovine genome and found higher expression in the corpus-epididymis region. Bioinformatic analyses found nsSNPs as neutral and non-deleterious but their structural-distorter could result in altered mRNA secondary structure, protein conformations decreased protein stability, and compromised biological functionalities. The polymorphisms resulted in altered O-glycosylations (deletion S57A and insertion N110S) and an increase in phosphorylations (52T-Threonine and 110S-Serine) post-translational-modifications. Conclusion: BBD129 gene polymorphism could be associated with the fertility performance of cattle bulls.

The climate is a long-term phenomenon taken as the average of weather for at least 30 years. It has been changing for billions of years with the regular shift from warm to cold, from glaciated to deglaciated, and from wet to dry. The changes in climate are recorded in several forms, which are potential evidences against climate change. These evidences can be traced through oceanic sediments, oxygen isotope ratios, ice sheets, fossils, pollen grains, tree rings, etc. For example, the deep-sea sediments have recorded the evidence of organisms belonging to geological periods of millions of years. The tree ring shows vital climatic records. Similarly, the study of the buried pollen in an area gives an idea about vegetation types in the past. Likely, several records have stored evidence of past climate change. In this chapter, an effort is made toward the gathering of such geological evidence of climate change.

Vehicular Ad hoc Networks (VANETs) being a vital component of Intelligent Transport System (ITS), is getting due attention from the research community. VANET are self-organized networks, offering a variety of services, comprising not only the safety of drivers and commuters but also provides them travel comfort, while they are on the wheels. But due to some inherent characteristics of VANETs, information dissemination is a big challenge in both dense and sparse environments. Simple broadcasting in the dense traffic environment leads to redundancy of packets, channel access contentions, and packet collisions. This results in a broadcast storm problem. On the contrary, when the traffic density is very low, information dissemination is affected by network partition and network fragmentation. To deal with such issues, we propose a Position Based Speed Adaptive Dissemination (PBSAD) approach, where relay nodes for rebroadcast are selected considering the geographical position of vehicular nodes, irrespective of their direction of movement. The speed of the message sending vehicle is taken into consideration while evaluating the time slots for rebroadcasting nodes. The approach avoids periodic beaconing to gather 1-hop information. Further, this approach ensures information dissemination in a sparse environment as well by using the store, carry, and forwarding concept in which vehicles moving in either direction can act as relay nodes. To validate the proposed approach, a comparative analysis of the PBSAD approach is done with few state of art schemes based on parameters like message delivery ratio, delay, and the number of collisions. The simulation results reveal that PBSAD performs efficiently.