A study of genetic population of Alosa braschnicowi (Borodin, 1904) in Sari and Mahmodabad coasts in the Caspian Sea, using Microsatellite loci

In this study, five Microsatellite loci were used to evaluate genetic diversity of A. braschnicowi between two populations of the Caspian Sea. Sixty samples were collected from the coasts of Mahmodabad and Sari (30 specimens for each population). Five Microsatellite loci were highly polymorphic among all samples. The number of alleles per locus observed ranged from 17 to 32 and averaged 14.1 alleles across two populations. The average observed heterozygosis in Mahmodabad and Sari were 57.1% to 60.1% and average observed heterozygosis between two populations was 58.9%. Among 10 population-locus (5 loci × 2 populations) only two tests were in the Hardy-Weinberg equilibrium, so highly deviation from the Hardy-Weinberg equilibrium was found. The average values of Fis and Nm were 0.33 and 14.19, respectively. Also AMOVA on base Fst index showed low genetic difference between two populations (2%), while the genetic diversity within population was 98%. Due to allelic diversity and estimates of heterozygosity, these markers can be useful in Alosa genus for population level analysis in the Caspian Sea

Ensemble Learning Models for Prediction of Punching Shear Strength in RC Slab-Column Connections

In reinforced concrete (RC) structures, accurate prediction of the punching shear strength (PSS) of slab-column connections is imperative for ensuring safety. The existing equations in the literature show variability in defining parameters influencing PSS. They neglect potential variable interactions and rely on a limited dataset. This study aims to develop an accurate and reliable model to predict the PSS of slab-column connections. An extensive dataset, including 616 experimental results, was collected from earlier studies. Six robust ensemble machine learning techniques—random forest, gradient boosting, extreme gradient boosting, adaptive boosting, gradient boosting with categorical feature support, and light gradient boosting machines—are employed to predict the PSS. The findings indicate that gradient boosting stands out as the most accurate method compared to other prediction models and existing equations in the literature, achieving a coefficient of determination of 0.986. Moreover, this study utilizes techniques to explain machine learning predictions. A feature importance analysis is conducted, wherein it is observed that the reinforcement ratio and compressive strength of concrete demonstrate the highest influence on the PSS output. SHapley Additive exPlanation is conducted to represent the influence of variables on PSS. A graphical user interface for PSS prediction was developed for users’ convenience. Doi: 10.28991/CEJ-SP2024-010-01 Full Text: PD

Effects of different levels of dried tomato pomace on performance, egg quality and serum metabolites of laying hens

A study was conducted to investigate the effects of dietary inclusion of dried tomato pomace (DTP) on performance, egg quality and serum metabolites in laying hens. A total of one hundred and forty four LOHMANN LSL-LITE hens were randomly allocated into 4 groups consisting of 6 replicates, each replicate has 6 birds. Birds were fed either a basal diet or the basal diet supplemented with 150, 170 or 190 g/kg of DTP. As a result of this study, there were no significant differences in body weight (BW), feed intake (FI), egg production (EP), feed conversion ratio (FCR) egg weight (EW), egg mass (EM), eggshell weight (ESW), eggshell thickness (EST) and Haugh unit (HU) among treatments. Dietary inclusion of DTP significantly increased yolk color score (YCS, P < 0.01). As dietary DTP increased from 0 to 19%, YCS significantly increased from 7.25 to 9.67 and 7.25 to 9.83 in first and second periods, respectively. Total serum protein, cholesterol, LDL, HDL, albumin, glucose and triglyceride levels were not significantly affected by DTP addition. In summary, DTP can be used as an alternative feedstuff in laying hen diets at inclusion levels up to 190 g/kg without any negative impact on performance and egg quality traits.Key words: Dried tomato pomace, egg quality, laying hen, serum metabolites

GT-TSCH: Game-Theoretic Distributed TSCH Scheduler for Low-Power IoT Networks

Time-Slotted Channel Hopping (TSCH) is a synchronous medium access mode of the IEEE 802.15.4e standard designed for providing low-latency and highly-reliable end-to-end communication. TSCH constructs a communication schedule by combining frequency channel hopping with Time Division Multiple Access (TDMA). In recent years, IETF designed several standards to define general mechanisms for the implementation of TSCH. However, the problem of updating the TSCH schedule according to the changes of the wireless link quality and node's traffic load left unresolved. In this paper, we use non-cooperative game theory to propose GT-TSCH, a distributed TSCH scheduler designed for low-power IoT applications. By considering selfish behavior of nodes in packet forwarding, GT-TSCH updates the TSCH schedule in a distributed approach with low control overhead by monitoring the queue length, the place of the node in the Directed Acyclic Graph (DAG) topology, the quality of the wireless link, and the data packet generation rate. We prove the existence and uniqueness of Nash equilibrium in our game model and we find the optimal number of TSCH Tx timeslots to update the TSCH slotframe. To examine the performance of our contribution, we implement GT-TSCH on Zolertia Firefly IoT motes and the Contiki-NG Operating System (OS). The evaluation results reveal that GT-TSCH improves performance in terms of throughput and end-to-end delay compared to the state-of-the-art method.Comment: 43rd IEEE International Conference on Distributed Computing System

BigBand: GHz-Wide Sensing and Decoding on Commodity Radios

The goal of this paper is to make sensing and decoding GHz of spectrum simple, cheap, and low power. Our thesis is simple: if we can build a technology that captures GHz of spectrum using commodity Wi-Fi radios, it will have the right cost and power budget to enable a variety of new applications such as GHz-widedynamic access and concurrent decoding of diverse technologies. This vision will change today s situation where only expensive power-hungry spectrum analyzers can capture GHz-wide spectrum. Towards this goal, the paper harnesses the sparse Fourier transform to compute the frequency representation of a sparse signal without sampling it at full bandwidth. The paper makes the following contributions. First, it presents BigBand, a receiver that can sense and decode a sparse spectrum wider than its own digital bandwidth. Second, it builds a prototype of its design using 3 USRPs that each samples the spectrum at 50 MHz, producing a device that captures 0.9 GHz -- i.e., 6x larger bandwidth than the three USRPs combined. Finally, it extends its algorithm to enable spectrum sensing in scenarios where the spectrum is not sparse

Modeling for Superheating Phenomenon of Embedded Superfine Metallic Nanoparticles

Abstract A theoretical model is proposed to predict the size-dependency of melting point for embedded nanoparticles (NPs) by employing surface and interior average coordination number, cohesive energy and atomic bond strength. The model was applied on the perfect clusters of icosahedral (IC) and body centered tetragonal (BCT) without any vacancies and defects. The predicted results for superfine NPs (lower than 50 nm) of In, Ag, Sn and Pb were consistent with experimental results

Why do farmers over-extract groundwater resources? Assessing (un)sustainable behaviors using an Integrated Agent-Centered framework

This study uses an Integrated Agent-Centered (IAC) framework to investigate the socio-psychological drivers of Iranian farmers’ unsustainable groundwater management practices. Empirical land use change analysis of US Geological Survey Landsat satellite images of the Jaz-Murian wetland region for 1990, 2010, and 2022, is combined with community surveys conducted with randomly selected farmers in five townships within the region (n=356). Visual analysis reveals dramatic increases in agricultural land coverage, diminished water bodies and increased salt lands over the 32-year sampled period. We use survey data to explain the socio-psychological drivers of unsustainable groundwater use that lead to these adverse environmental changes. In the IAC survey analysis, we find that variables for “expectation” and “subjective culture” have a negative influence on pro-environmental “intention”. “Intention” and “habit” have a positive influence, and “contextual factors” have a negative influence on the drivers of “unsustainable water use behavior”. We conclude that situational influences, habitual process, intentional process, and normative processes must be considered together to alleviate pressure on wetland ecosystems. Policy makers must provide effective agricultural extension training, deliberative dialogue amongst farmer networks, well governed local water markets and financial support to shift farmer short-termist economic gain-thinking towards socially-supported pro-environmental habits over the longer term

Izražajnost kalretinina kao biomarkera rizika za metastatski karcinom mliječne žlijezde u pasa

Malignant breast tumors are the most common tumors in humans and are associated with a poor prognosis. An accurate animal model of human mammary gland tumorigenesis is needed to test novel diagnosis and treatment strategies. Dogs represent a promising model since they develop such tumors spontaneously. In the present study, three immunomarkers, including calretinin, c-Kit (CD117) and placental alkaline phosphatase (Plap), were used and compared with each other, in relation to estrogen and progesterone receptors and HER2 (triple markers), with the intention of malignancy grading. Enhanced expression of calretinin and placental alkaline phosphatase, without immunoreaction to c-Kit in neoplastic cells, is related to high-grade malignancy. Out of 50 tumors, 31 were metastasized, 29 of which (93.5%) were moderately to strongly calretinin positive (P<0.05). However, the results for c-Kit - and Plap+ in metastatic tumors were not reproducible. It may be concluded that calretinin could be introduced as a determinant biomarker in the diagnosis of breast cancer metastasis.Maligni tumori dojke najčešći su tumori u ljudi i povezani su s lošom prognozom. Da bi se testirali novi dijagnostički postupci i terapijske procedure u ljudi, potreban je prikladan životinjski model tumorogeneze mliječne žlijezde. Psi su potencijalno dobar model zbog spontanog razvoja ovakvih tumora. U ovom su istraživanju, s ciljem stupnjevanja malignosti, međusobno uspoređena tri imunomarkera, kalretinin, c-Kit (CD117) i placentalna alkalna fosfataza (Plap), a zatim su isti uspoređeni i s estrogenskim, progesteronskim te HER2 (trostrukim) markerima. Povećanje izražajnosti kalretinina i placentalne alkalne fosfataze, bez imunoreakcije na c-Kit u neoplastičnim stanicama povezano je s visokim stupnjem malignosti. Od 50 tumora, 31 je metastazirao, od kojih je 29 (93,5 %) bilo umjereno do izrazito pozitivno na kalretinin (P < 0,05). Doduše, rezultati za c-Ki ti Plap+ nisu bili ponovljivi. Zaključujemo da bi kalretinin mogao poslužiti kao biomarker u dijagnostici metatstatskog raka dojke

Analysis of DNS Dependencies and their Security Implications in Australia:A Comparative Study of General and Indigenous Populations

This paper investigates the impact of internet centralization on DNS provisioning, particularly its effects on vulnerable populations such as the indigenous people of Australia. We analyze the DNS dependencies of Australian government domains that serve indigenous communities compared to those serving the general population. Our study categorizes DNS providers into leading (hyperscaler, US-headquartered companies), non-leading (smaller Australian-headquartered or non-Australian companies), and Australian government-hosted providers. Then, we build dependency graphs to demonstrate the direct dependency between Australian government domains and their DNS providers and the indirect dependency involving further layers of providers. Additionally, we conduct an IP location analysis of DNS providers to map out the geographical distribution of DNS servers, revealing the extent of centralization on DNS services within or outside of Australia. Finally, we introduce an attacker model to categorize potential cyber attackers based on their intentions and resources. By considering attacker models and DNS dependency results, we discuss the security vulnerability of each population group against any group of attackers and analyze whether the current setup of the DNS services of Australian government services contributes to a digital divide