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Yu G, Ali Z, Sajjad Khan A, et al. Int J Nanomedicine. 2021;16:3255-3273. At the authors request, the Editor and Publisher of International Journal of Nanomedicine wish to retract the published article. Concerns were raised regarding the alleged duplication of images in Figures 9A, 9B and 9C with the same images from a previous article (ud Din et al, 2017 https://doi.org/10.1080/10717544.2016.1272651) by the same authors. Specifically, Figure 9A, Untreated Control, Pure Drug, HePC-NLCs, Normal Saline and all corresponding Tumor mass images appear to have been duplicated with the same images for Figure 6A, Control, Solution, DRTN, and Hydrogel images, respectively, from ud Din et al, 2017. Figure 9B, Pure Drug, Caspas-3; HePC-NLCs, Caspas-3 and Normal Saline, Caspas-3 appear to have been duplicated with the same images from Figure 6C, Solution, Ki-67 and Figure 6B, DRTN, Caspase-3 and Control, Caspase-3, respectively, from ud Din et al, 2017. Figure 9C, Untreated Control, PARP; Pure Drug, PARP; HePC-NLCs, PARP and Normal Saline, PARP appear to have been duplicated with the same images from Figure 6C, Hydrogel, CD31; Figure 6B, Solution, PARP; Figure 6C, Control, CD31 and Figure 6B, Control, PARP, respectively, from ud Din et al, 2017. The authors responded to our queries and agreed with the concerns that had been raised and requested for the retraction of the article. The Editor agreed with this decision and approved the authors retraction request. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”.

Health consciousness and increased knowledge about the side effects of synthetic drugs have enhanced interest in traditional medicines. Medicinal plants offer cures for various diseases, leading to improved living standards. This has brought ethnomedicinal studies into the spotlight and increased demand for herb-based medicines. Citrullus colocynthis is an herbaceous plant containing an abundance of nutrients that play a key role in the improvement of wellbeing. C. colocynthis has many biological properties, such as antioxidative, hypoglycemic, antibacterial, anti-cancerous, anti-inflammatory, analgesic, gastrointestinal tract, reproduction, protection, anti-microbial, antidiabetic, hypolipidemic, antineoplastic, profibrinolytic, anti-allergic, pesticidal, and immune-stimulatory. There are numerous bioactive compounds like cucurbitacin, flavonoids, and polyphenols in C. colocynthis that give it medicinal properties. Herein, we have extensively compiled, reviewed, and analyzed significant information on C. colocynthhis from the best published available evidence in PubMed, Scopus (Embase), Web of Science (Web of Knowledge), Cochrane Library, and Google Scholar, etc. Scientific literature evidenced that owing to the bioactive constituents, including cucurbitacin, polyphenols, flavonoids, and other potent molecules, C. colocynthis has many pharmacological and physiological functions. It possesses multi-beneficial applications in treating various disorders of humans and animals. So, the primary purpose of this comprehensive review is to provide an overview of the findings of positive impacts and risks of C. colocynthis consumption on human health, especially in poultry and veterinary fields. In the future, this narrative article will be aware of discoveries about the potential of this promising natural fruit and its bioactive compounds as the best nutraceuticals and therapeutic drugs in veterinary and human medicine.

Noncontiguous orthogonal frequency division multiplexing (NC-OFDM) is considered a suitable candidate for the cognitive radio network (CRN) to accomplish efficient data transmission. The NC-OFDM allows secondary users (SUs) to access the primary user (PU) spectrum while being detected idle. However, interference may occur in the adjacent frequency bands of the PU due to sidelobes of the SU transmission. The use of cancellation carriers (CCs) and generalized sidelobe canceller (GSC) is a widely adopted technique to tackle the sidelobes. To this end, this paper presents a differential evolution- (DE-) based GSC (DE-GSC) scheme to suppress unwanted sidelobes. At first, in the DE-GSC1 scheme, the adaptive weight vector is calculated using the DE algorithm while considering the complete samples of the sidelobes for optimization. The optimized weights are then added with the original weights to reduce the sidelobe issue. Next, in the DE-GSC2 scheme, selected elements for the adaptive weight vector near the main NC-OFDM signal are computed using the DE to reduce the search space. The performance of the proposed methods in terms of power spectral density (PSD) is compared with some of the recent techniques employing five different scenarios. Simulation results in the presence of single and multiple spectral hole scenarios validate that the proposed DE-GSC1 and DE-GSC2 methods result in enhanced suppression performance compared with the: original signal, simple CC, simple GSC, DE-based CC (DE-CC), and genetic algorithm- (GA-) based CC (GA-CC) schemes.

The subject of dolomite formation has always put researchers in the challenge. In this study, the origin of the dolomites of the Chorgali Formation near Chorgali Pass was explored through field observation, petrographic characteristics, mineralogical and geochemical analysis. Analytical analyses used in the present studies include XRD, SEM-EDS, and stable isotopes studies. The dolomites were categorized into three major genetic types based on their textural and structural features showing their distinct origins. These dolomites are named fine crystalline dolomite (Df), medium crystalline dolomite (Dm), and coarse crystalline dolomite (Dc). The analytical approaches linked with field observations and petrographic examinations identified that; the first type of dolomites (i.e., Df) is related to the early stage of diagenesis and contain the presence of mineral dolomite (40%), gypsum (27%), quartz (17%) and albite (16%) and are low stochiometric low ordered in character as recognized by XRD results. The SEM-EDS analysis identified low Mg, Ca, O, Na, Si, and Fe concentrations. Further, the stable isotopes (δ18O) values for Df (i.e., -5.95 to -396‰V-PDB) are less depleted. Moreover, Dm and Dc revealed 100% mineral dolomite and are stochiometric ordered dolomites. High concentrations of Mg, Ca and O are observed in Dm and Dc respectively. Stable isotopes (δ18O) result in exhibiting highly depleted values for Dm (-7.947‰V-PDB) and Dc (-9.227 to -8.302‰V-PDB) showing its formation with the elevated temperature at depth. In addition, δ13C values of Df, Dm, and Dc lie in the range of the original marine signature of Eocene times.

Resveratrol (RV) is a well-known polyphenolic compound in various plants, including grape, peanut, and berry fruits, which is quite famous for its association with several health benefits such as anti-obesity, cardioprotective neuroprotective, antitumor, antidiabetic, antioxidants, anti-age effects, and glucose metabolism. Significantly, promising therapeutic properties have been reported in various cancer, neurodegeneration, and atherosclerosis and are regulated by several synergistic pathways that control oxidative stress, cell death, and inflammation. Similarly, RV possesses a strong anti-adipogenic effect by inhibiting fat accumulation processes and activating oxidative and lipolytic pathways, exhibiting their cardioprotective effects by inhibiting platelet aggregation. The RV also shows significant antibacterial effects against various food-borne pathogens (Listeria, Campylobacter, Staphylococcus aureus, and E. coli) by inhibiting an electron transport chain (ETC) and F0F1-ATPase, which decreases the production of cellular energy that leads to the spread of pathogens. After collecting and analyzing scientific literature, it may be concluded that RV is well tolerated and favorably affects cardiovascular, neurological, and diabetic disorders. As such, it is possible that RV can be considered the best nutritional additive and a complementary drug, especially a therapeutic candidate. Therefore, this review would increase knowledge about the blend of RV as well as inspire researchers around the world to consider RV as a pharmaceutical drug to combat future health crises against various inhumane diseases. In the future, this article will be aware of discoveries about the potential of this promising natural compound as the best nutraceuticals and therapeutic drugs in medicine.

A geophysical survey was carried out at Tattapani thermal spring Azad Kashmir to delineate structure, thickness, depth, lithology and migration of hot plumes contaminating fresh water. The study area was investigated by Vertical Electrical Sounding (VES) using schlumberger array at 21 locations arranged in ten profiles to a maximum depth of 500 m and 200 magnetic observations. The extension and tectonic setup of thermal spring was mapped by geoelectrical litho sections, subsurface geological sections (20m, 20-100m and 100-500m) pseudo section, apparent resistivity map, geoelectrical parameters, statistical distribution of apparent resistivity, total magnetic intensity and anomaly map. The data show that Tattapani hot spring is concentrated along the fault line delineated by geoelectrical litho sections and magnetic section with value of -120 nT to -300 nT, total field intensity of 50000-50450 nT and confirm by macro anisotropy (1.0 to 2.7). The geoelectrical lithological section portrays that study area comprises lithological fabric of dolomite (≥400 ohm.m), sandstone (150-200 ohm.m), clay (80-150 ohm.m), Shaley clay (50-80) and shale (≤ 50). The Thermal Plumes (10-70 ohm.m) were pictured by resistivity section and pseudo section at average depth of 30-60 m and showing migration of hot plumes in the North-Eastern direction contaminating fresh water (100-200 ohm.m). The longitudinal conductance (0.95-15 mhos), transverse resistance (20-300 ohm.m2) are seen having maximum value in the North-Eastern and North-Western side of the study area. The study also shows that fresh ground water is mostly concentrated in sandstone (150-200 ohm.m), dolomite (≥400 ohm.m) and lies above the thermal plumes and thus highly prone to contamination due to upwelling of thermal water

The secondary users (SUs) in cognitive radio networks (CRNs) can obtain reliable spectrum sensing information of the primary user (PU) channel using cooperative spectrum sensing (CSS). Multiple SUs share their sensing observations in the CSS system to tackle fading and shadowing conditions. The presence of malicious users (MUs) may pose threats to the performance of CSS due to the reporting of falsified sensing data to the fusion center (FC). Different categories of MUs, such as always yes, always no, always opposite, and random opposite, are widely investigated by researchers. To this end, this paper proposes a hybrid boosted tree algorithm (HBTA)-based solution that combines the differential evolution (DE) and boosted tree algorithm (BTA) to mitigate the effects of MUs in the CSS systems, leading to reliable sensing results. An optimized threshold and coefficient vector, determined against the SUs employing DE, is utilized to train the BTA. The BTA is a robust ensembling machine learning (ML) technique gaining attention in spectrum sensing operations. To show the effectiveness of the proposed scheme, extensive simulations are performed at different levels of signal-to-noise-ratios (SNRs) and with different sensing samples, iteration levels, and population sizes. The simulation results show that more reliable spectrum decisions can be achieved compared to the individual utilization of DE and BTA schemes. Furthermore, the obtained results show the minimum sensing error to be exhibited by the proposed HBTA employing a DE-based solution to train the BTA. Additionally, the proposed scheme is compared with several other CSS schemes such as simple DE, simple BTA, maximum gain combination (MGC), particle swarm optimization (PSO), genetic algorithm (GA), and K-nearest neighbor (KNN) algorithm-based soft decision fusion (SDF) schemes to validate its effectiveness.

Background Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication. Results We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the “cost of domestication” hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes. Conclusion This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.

Ruminants inhabit the consortia of gut microbes that play a critical functional role in their maintenance and nourishment by enabling them to use cellulosic and non-cellulosic feed material. These gut microbes perform major physiological activities, including digestion and metabolism of dietary components, to derive energy to meet major protein (65-85%) and energy (ca 80%) requirements of the host. Owing to their contribution to digestive physiology, rumen microbes are considered one of the crucial factors affecting feed conversion efficiency in ruminants. Any change in the rumen microbiome has an imperative effect on animal physiology. Ruminal microbes are fundamentally anaerobic and produce various compounds during rumen fermentation, which are directly used by the host or other microbes. Methane (CH4) is produced by methanogens through utilizing metabolic hydrogen during rumen fermentation. Maximizing the flow of metabolic hydrogen in the rumen away from CH4 and toward volatile fatty acids (VFA) would increase the efficiency of ruminant production and decrease its environmental impact. Understanding of microbial diversity and rumen dynamics is not only crucial for the optimization of host efficiency but also required to mediate emission of greenhouse gases (GHGs) from ruminants. There are various strategies to modulate the rumen microbiome, mainly including dietary interventions and the use of different feed additives. Phytogenic feed additives, mainly plant secondary compounds, have been shown to modulate rumen microflora and change rumen fermentation dynamics leading to enhanced animal performance. Many in vitro and in vivo studies aimed to evaluate the use of plant secondary metabolites in ruminants have been conducted using different plants or their extract or essential oils. This review specifically aims to provide insights into dietary interactions of rumen microbes and their subsequent consequences on rumen fermentation. Moreover, a comprehensive overview of the modulation of rumen microbiome by using phytogenic compounds (essential oils, saponins, and tannins) for manipulating rumen dynamics to mediate CH4 emanation from livestock is presented. We have also discussed the pros and cons of each strategy along with future prospective of dietary modulation of rumen microbiome to improve the performance of ruminants while decreasing GHG emissions.

The movement to digitally transform Saudi Arabia in all sectors has already begun under the &ldquo, Vision 2030&rdquo, program. Consequently, renovating and standardizing production and manufacturing industries to compete with global challenges is essential. The fourth industrial revolution (Industry 4.0) triggered by the development of information and communications technologies (ICT) provides a baseline for smart automation, using decentralized control and smart connectivity (e.g., Internet of Things). Industrial engineering graduates need to have acquaintance with this industrial digital revolution. Several industries where the spirit of Industry 4.0 has been embraced and have already implemented these ideas yielded gains. In this paper, a roadmap containing an academic term course based on the concept of Industry 4.0, which our engineering graduates passed through, is presented. At first, an orientation program to students elaborating on the Industry 4.0 concept, its main pillars, the importance of event-driven execution, and smart product manufacturing techniques. Then, various tasks in developing a learning factory were split and assigned among student groups. Finally, the evaluation of student potential in incorporating the Industry 4.0 concept was analyzed. This methodology led to their professional skill development and promoted students&rsquo, innovative ideas for the manufacturing sector.

In recent decades, production in high-volume/low-variety batches is replaced with low-volume/high-variety production type. This type of production demands excessive flows of both material and information. Recent advances in information and communication technologies (ICT), together with the concept of cyber-psychical system (CPS) enable the concept of Industry 4.0 (I4.0). In this paper, the performance of I4.0 related equipment implementation is presented in iterative assembly line balancing (ALB) process of a gearbox assembly line. Largest candidate rule method through spreadsheet simulation was used for tasks reallocations, with the objective to minimize the cycle time when the number of stations is fixed. Utilization of human analysts using snap back method for manual data gathering process still shown advantage over I4.0 equipment utilization in manual ALB. The assembly process is performed in the learning factory environment, and it is considered as very close to real industry process. The major conclusion is that I4.0 is excellent in process data monitoring and product tracking, but activities to be performed to effectively exploit I4.0 is demanding for task reallocations during the balancing procedure. Nevertheless, future enhancements of I4.0 system are listed to bridge this gap and to increase I4.0 system usefulness in the manual assembly line balancing process

Despite the substantial role that chickens have played in human societies across the world, both the geographic and temporal origins of their domestication remain controversial. To address this issue, we analyzed 863 genomes from a worldwide sampling of chickens and representatives of all four species of wild jungle fowl and each of the five subspecies of red jungle fowl (RJF). Our study suggests that domestic chickens were initially derived from the RJF subspecies Gallus gallus spadiceus whose present-day distribution is predominantly in southwestern China, northern Thailand and Myanmar. Following their domestication, chickens were translocated across Southeast and South Asia where they interbred locally with both RJF subspecies and other jungle fowl species. In addition, our results show that the White Leghorn chicken breed possesses a mosaic of divergent ancestries inherited from other subspecies of RJF. Despite the strong episodic gene flow from geographically divergent lineages of jungle fowls, our analyses show that domestic chickens undergo genetic adaptations that underlie their unique behavioral, morphological and reproductive traits. Our study provides novel insights into the evolutionary history of domestic chickens and a valuable resource to facilitate ongoing genetic and functional investigations of the world’s most numerous domestic animal.

Kenaf (Hibiscus cannabinus L.) is a fibrous crop, grown in tropical climate having huge biomass and can be a good candidate for the phytoremediation of different heavy metals. Consequently, the present study was conducted to explore morpho-physiological traits, photosynthetic pigments, gaseous exchange attributes, antioxidative response and phytoextraction of copper (Cu) in H. cannabinus grown under different levels of Cu i.e. 0 (control), 60, 120 and 180 µmol L−1 in Hoagland nutrient solution (pH 6.2). The results from the present study revealed that Cu toxicity reduced plant height, plant diameter, plant fresh weight, plant dry weight, photosynthetic pigments and gaseous exchange attributes compared to control. Moreover, excess Cu in the nutrient solution ameliorates contents of malondialdehyde (MDA), hydrogen peroxide (H2O2) and electrolyte leakage (EL) which showed that Cu induced oxidative damage in the roots and leaves of H. cannabinus. The oxidative stress which was induced by a high concentration of Cu in the nutrient solution is overcome by enzymatic activities of antioxidants which increased with the increase in Cu concentration, i.e. 60 and 120 µmol L−1, while the addition of Cu (180 µmol L−1) caused a reduction in the activities of superoxidase dismutase (SOD), peroxidase (POD), catalase (CAT) and ascorbate peroxidase (APX) in the roots and leaves of H. cannabinus. The results also demonstrated that an increase in Cu concentration in the nutrient solution causes an increase in Cu accumulation through roots, leaves and stems of H. cannabinus, although the highest Cu concentration was accumulated in roots while only a little transported to the above ground parts (leaves and stems) of the plants. All the values of bioaccumulation factor (BAF) and translocation factor (TF) were less than 1, which also indicated that a small quantity of Cu concentration is transported to the aboveground part of the plants. These findings suggested that phytotoxicity of Cu affected plant growth and biomass and increased ROS production while accumulation of Cu in different parts of plant proved that H. cannabinus is an ideal specie for phytoremediation of Cu when grown under Cu contaminated sites.

In a cognitive radio (CR), opportunistic secondary users (SUs) periodically sense the primary user’s (PU’s) existence in the network. Spectrum sensing of a single SU is not precise due to wireless channels and hidden terminal issues. One promising solution is cooperative spectrum sensing (CSS) that allows multiple SUs’ cooperation to sense the PU’s activity. In CSS, the misdetection of the PU signal by the SU causes system inefficiency that increases the interference to the system. This paper introduces a new category of a malicious user (MU), i.e., a lazy malicious user (LMU) with two operating modes such as an awakened mode and sleeping mode. In the awakened mode, the LMU reports accurately the PU activity like other normal cooperative users, while in the sleeping mode, it randomly reports abnormal sensing data similar to an always yes malicious user (AYMU) or always no malicious user (ANMU). In this paper, statistical analysis is carried out to detect the behavior of different abnormal users and mitigate their harmful effects. Results are collected for the different hard combination schemes in the presence of the LMU and opposite categories of malicious users (OMUs). Simulation results collected for the error probability, detection probability, and false alarm at different levels of the signal-to-noise ratios (SNRs) and various contributions of the LMUs and OMUs confirmed that out of the many outlier detection tests, the median test performs better in MU detection by producing minimum error probability results in the CSS. The results are further compared by keeping minimum SNR values with the mean test, quartile test, Grubbs test, and generalized extreme studentized deviate (GESD) test. Similarly, performance gain of the median test is examined further separately in the AND, OR, and voting schemes that show minimum error probability results of the proposed test as compared with all other outlier detection tests in discarding abnormal sensing reports.

This article presents raw data from a survey conducted to identify the selection criteria of breeders raising either of four strains of Beetal goats, namely Beetal Faisalabadi, Beetal Makhi-Cheeni, Beetal Nuqri, and Beetal Rahim Yar Khan. After a pre-survey, a questionnaire was developed and a survey was conducted at four sites of the Punjab province of Pakistan: Faisalabad/Sahiwal, Bahawalpur/Bahawalnagar, Rajanpur, and Rahim Yar Khan. Each of these sites was the home tract of one strain. During the survey breeders (n = 162) were asked to rank the traits of their selection criteria based on the relative importance of those traits. Furthermore, the prevailing production system was also characterized by the breeders. For the interpretation of the results of this survey the readers are referred to Ref. [1]. The raw data set provided in this article can be extended in the future to include more strains of Beetal goats as well as other goat breeds. The selection criteria of breeders can change over time. This data set can also be used in future studies to investigate the temporal changes in the relative importance of different traits for the breeders. The factors potentially influencing those changes can also be investigated. This data set can further be utilized to design community based breeding plans tailored to the needs of the goat farming community. Open-Access-Publikationsfonds 2020 peerReviewed

Internet of Things-based environments pose various challenges due to their anytime/anywhere computing, and the efficient cryptographic based key management is one of the major challenges in Internet of Things. The key management life cycle consists of initialization, key generation, key registration, key backup, key update, key recovery, and key revocation. Our contribution in this paper is to summarize the state-of-the-art key management schemes and techniques in different scenarios, such as mobile ad hoc networks, wireless sensor networks, and the Internet of Things environments. Further different issues related specifically to the Internet of Things environment are discussed and the causes and effects pertaining to the security breach for Internet of Things are identified. Furthermore, in this research work, we develop a novel permutation of threshold and identity-based key management schemes for the Internet of Things environment and have proposed future directions to counteract the attacks on confidentiality, integrity, authentication, and availability of security services in the Internet of Things environment and identified the two key management schemes, that is, identity and threshold schemes for Internet of Things, to resolve Internet of Things key management issues and maximum possible security services effective implementation. We evaluate our scheme with the help of mathematical and statistical techniques.

Cognitive radio (CR) is being considered as a vital technology to provide solution to spectrum scarcity in next generation network, by efficiently utilizing the vacant spectrum of the licensed users. Cooperative spectrum sensing in cognitive radio network has a promising performance compared to the individual sensing. However, the existence of the malicious users’ attack highly degrades the performance of the cognitive radio networks by sending falsified data also known as spectrum sensing data falsification (SSDF) to the fusion center. In this paper, we propose a double adaptive thresholding technique in order to differentiate legitimate users from doubtful and malicious users. Prior to the double adaptive approach, the maximal ratio combining (MRC) scheme is utilized to assign weight to each user such that the legitimate users experience higher weights than the malicious users. Double adaptive threshold is applied to give a fair chance to the doubtful users to ensure their credibility. A doubtful user that fails the double adaptive threshold test is declared as a malicious user. The results of the legitimate users are combined at the fusion center by utilizing Dempster-Shafer (DS) evidence theory. Effectiveness of the proposed scheme is proved through simulations by comparing with the existing schemes.

The present study was conducted with the objectives to describe flock composition and pattern of entry and exit of village chicken through in-depth monitoring in six randomly selected villages belong to two sites in Punjab, Pakistan. Initial survey and six monitoring visits of the selected household in each village were made after fixed intervals for a year. The data collected on population size, sex and flock composition of various age groups of six chicken types/breeds. The number of birds in the flock fluctuated across visits and a large number of laying hens compared to other bird categories were observed in the flock. The causes of flock dynamics indicated diseases as the major reason for all bird groups. Sale of birds provided the source of income to the farmers. Improvement in management and veterinary care are suggested to enhance flock productivity and thereby increase family income. Tropical Agricultural Research Vol. 26 (3): 448 – 455 (2015)

The visiting and less-privileged status of the secondary users (SUs) in a cognitive radio network obligates them to release the occupied channel instantly when it is reclaimed by the primary user. The SU has a choice to make: either wait for the channel to become free, thus conserving energy at the expense of delayed transmission and delivery, or find and switch to a vacant channel, thereby avoiding delay in transmission at the expense of increased energy consumption. An energy-efficient decision that considers the tradeoff between energy consumption and continuous transmission needs to be taken as to whether to switch the channels. In this work, we consider a sensor network-assisted cognitive radio network and propose a backup channel, which is sensed by the SU in parallel with the operating channel that is being sensed by the sensor nodes. Imperfect channel sensing and residual energy of the SU are considered in order to develop an energy-efficient handoff strategy using the partially observable Markov decision process (POMDP), which considers beliefs about the operating and backup channels and the remaining energy of the SU in order to take an optimal channel handoff decision on the question “Should we switch the channel?” The objective is to dynamically decide in each time slot whether the SU should switch the channel or not in order to maximize throughput by utilizing energy efficiently. Extensive simulations were performed to show the effectiveness of the proposed channel handoff strategy, which was demonstrated in the form of throughput with respect to various parameters, i.e., detection probability, the channel idle probabilities of the operating and backup channels, and the maximum energy of the SU.

This study was accomplished with the objective to determine parameters of lactation curves in Beetal goats using Wood’s model. Therefore, milk yield data on 127 Beetal goats maintained at five different government farms were recorded from post-kidding to drying off of does. Wood model parameters were estimated using non-linear regression and individual curves were fitted. The characteristics/parameters of lactation curve were computed. The mean initial yield »a«, rate of increase »b« and rate of decline »c« parameters in Wood’s model for Beetal were 1,214.97, 0.3690 and 0.1196, respectively with R2 value of 98.2 %. The value of percent squared bias (PSB) and the persistency were 0.13 and 60.2%, respectively with mean square error value of 38.45. Flock effect was a significant (P

Growth data from birth to one year of age on 120 Beetal goats, 30 animals on each farm, including Livestock Experiment Station (LES) Rakh Kheirewala, LES Rakh Ghulaman, LES Alladad and LPRI Bahadurnagar, Okara, Pakistan, were recorded and analysed for estimating growth curve parameters: predicted live weight, »a«, turning point of growth, »b« and rate of growth »k« by using Brody and Gompertz mathematical functions employing non-linear regression models. Estimates of the growth curve parameters »a«, »b« and »k« were 29.1, 0.916 and 0.108 for Brody and 23.4, 1.984 and 0.258 for Gompertz functions, respectively. The corresponding values of determination coefficient and mean absolute deviation for these models were 99.8 and 99.8 percent and 0.0061 and 0.0050, respectively. Flock significantly affected parameter »b« of Brody and Gompertz models. Sex did not affect any of the parameters in both models. Type of birth was a significant source of variation for parameter »b« in the Brody model. The determination coefficient showed that both the models efficiently explained the growth of Beetal kids.

To study the environmental and genetic factors affecting productive and reproductive traits, data on 5,897 cows from five main recorded herds (for 1964–2004) of Sahiwal cattle in Pakistan were used. A general linear model was applied on the data. The 305-day milk yield, total milk yield, lactation length, age at first calving, dry period, calving interval and service period averaged 1,393 ± 12 kg, 1,429 ± 11 kg, 235 ± 2, 1,390 ± 4, 244 ± 3, 464 ± 3 and 1,78 ± 3 days, respectively. The age at first calving was effected by herd, year and season of birth. The 305-day and total milk yields were affected by herd, year, season of calving, age at first calving, service period and lactation length while all other first lactation traits were affected by herd, year, season of calving and 305-day milk yield. Animal model heritability estimates for these traits were 0.11 ± 0.029, 0.11 ± 0.028, 0.09 ± 0.027, 0.02 ± 0.019, 0.05 ± 0.019, 0.12 ± 0.027 and 0.04 ± 0.020, respectively. Rate of decline in first lactation milk yield was 7 l per year over the last 35 years with genetic trend close to zero. Lactation length and service period decreased and age at first calving increased by 2, 1 and 6 days per year, respectively. Herd differences for most of the traits were significant. Improved feeding and management may improve performance traits of Sahiwal cattle. Accurate recording of pedigrees and performance traits would help improve genetic param

Level of inbreeding and its effects on growth and reproductive traits were measured in Beetal goats using 4554 kidding records (1968–2004) from an experiment station in Pakistan. Level of inbreeding varied over the years; was zero in 1974 then increased 0.42% per year till 1987 when all the bucks and some of the does were replaced with unrelated animals. From 1988 till 2000, inbreeding again increased 0.21% per year and declined thereafter due to introduction of unrelated bucks. The average level of inbreeding over the years varied from zero to 7.3%. 42.7 % of all investigated animals were inbred, half of which had inbreeding greater than 6.25%. About 3.4% of animals were 25% or more inbred. Regression analysis indicated that birth weight (p