This paper presents the development of a novel anti-violence device titled “no pAIn” (an acronym for Never Oppressed Protected by Artificial Intelligence Nonviolence system), which harnesses the power of artificial intelligence (AI). Primarily designed to combat violence against women, the device offers personal safety benefits for individuals across diverse demographics. Operating autonomously, it necessitates no user interaction post-activation. The AI engine conducts real-time speech recognition and effectively discerns genuine instances of aggression from non-violent disputes or conversations. Facilitated by its Internet connectivity, in the event of detected aggression, the device promptly issues assistance requests with real-time precise geolocation tracking to predetermined recipients for immediate assistance. Its compact size enables discreet concealment within commonplace items like candy wrappers, purpose-built casings, or wearable accessories. The device is battery-operated. The prototype was developed using a microcontroller board (Arduino Nano RP2040 Connect), incorporating an omnidirectional microphone and Wi-Fi module, all at a remarkably low cost. Subsequent functionality testing, performed in debug mode using the Arduino IDE serial monitor, yielded successful results. The AI engine exhibited exceptional accuracy in word recognition, complemented by a robust logic implementation, rendering the device highly reliable in discerning genuine instances of aggression from non-violent scenarios. Full article

Shrimp fry counting is an important task for biomass estimation in aquaculture. Accurate counting of the number of shrimp fry in tanks can not only assess the production of mature shrimp but also assess the density of shrimp fry in the tanks, which is very helpful for the subsequent growth status, transportation management, and yield assessment. However, traditional manual counting methods are often inefficient and prone to counting errors; a more efficient and accurate method for shrimp fry counting is urgently needed. In this paper, we first collected and labeled the images of shrimp fry in breeding tanks according to the constructed experimental environment and generated corresponding density maps using the Gaussian kernel function. Then, we proposed a multi-scale attention fusion-based shrimp fry counting network called the SFCNet. Experiments showed that our proposed SFCNet model reached the optimal performance in terms of shrimp fry counting compared to CNN-based baseline counting models, with MAEs and RMSEs of 3.96 and 4.682, respectively. This approach was able to effectively calculate the number of shrimp fry and provided a better solution for accurately calculating the number of shrimp fry. Full article

Accurate feeding management in aquaculture relies on assessing the average weight of aquatic animals during their growth stages. The traditional method involves using a labor-intensive approach and may impact the well-being of fish. The current research focuses on a unique way of estimating red tilapia’s weight in cage culture via a river, which employs unmanned aerial vehicle (UAV) and deep learning techniques. The described approach includes taking pictures by means of a UAV and then applying deep learning and machine learning algorithms to them, such as convolutional neural networks (CNNs), extreme gradient boosting (XGBoost), and a Hybrid CNN-XGBoost model. The results showed that the CNN model achieved its accuracy peak after 60 epochs, showing accuracy, precision, recall, and F1 score values of 0.748 ± 0.019, 0.750 ± 0.019, 0.740 ± 0.014, and 0.740 ± 0.019, respectively. The XGBoost reached its accuracy peak with 45 n_estimators, recording values of approximately 0.560 ± 0.000 for accuracy and 0.550 ± 0.000 for precision, recall, and F1. Regarding the Hybrid CNN-XGBoost model, it demonstrated its prediction accuracy using both 45 epochs and n_estimators. The accuracy value was around 0.760 ± 0.019, precision was 0.762 ± 0.019, recall was 0.754 ± 0.019, and F1 was 0.752 ± 0.019. The Hybrid CNN-XGBoost model demonstrated the highest accuracy compared to using standalone CNN and XGBoost models and could reduce the time required for weight estimation by around 11.81% compared to using the standalone CNN. Although the testing results may be lower than those from previous laboratory studies, this discrepancy is attributed to the real-world testing conditions in aquaculture settings, which involve uncontrollable factors. To enhance accuracy, we recommend increasing the sample size of images and extending the data collection period to cover one year. This approach allows for a comprehensive understanding of the seasonal effects on evaluation outcomes. Full article

Population abundance and density estimates play important roles in biodiversity conservation assessment and can lead to prioritization of conservation efforts, strategies, and management. The Calabar angwantibo (Arctocebus calabarensis) is a poorly studied, Near-Threatened nocturnal, arboreal mammal species occurring only in the lowland moist tropical rainforest blocks of southeastern Nigeria and southwestern Cameroon. Like other arboreal nocturnal mammals, there are gaps in knowledge of the distribution and abundance of this species, which may be facing population declines due to habitat loss and hunting. In this study, we investigated the abundance and density of A. calabarensis in the Oban Hills Region of Nigeria. We conducted systematic distance sampling survey along 32 transects in different habitats in a 1227 km of survey efforts. A total of 41 sightings of A. calabarensis were detected, resulting in an abundance of 7345 individuals (95% CI = 1.51–4.37) with an estimated density of 2.57 animals/km². The estimated population abundance is 6515 individuals in closed-canopy forests and 830 individuals in secondary forests, with encounter rates of 0.52 individual/km² and 0.60 individuals/km² in the closed canopy and secondary forest habitats. The global estimates encounter rate of A. calabarensis across the habitat types is 0.33 individuals/km² and population abundance of 4456 individuals. Our findings indicate that the A. calabarensis populations can adapt to low changes in forest habitat modifications resulting from increasing and widespread forest disturbance by human-dominated activity, which is giving way to forest clearance for agriculture cultivation and infrastructural development. Our findings help to fill a knowledge gap regarding this species and may help establish a baseline for future management, population monitoring, and conservation of the cryptic population of A. calabarensis in Cross-Sanaga Forests. Full article

Entrepreneurship education largely influences the social and economic dimensions of many countries. In the framework of development, frequent changes seek to discover the most effective way of adopting and integrating educational services to meet the requirements of the labour market. This paper aims to analyse entrepreneurial competence in a teaching context from the students’ perspectives. The main objective of the research study aims to measure students’ attitudes towards entrepreneurial intentions, as impacted in an entrepreneurial teaching context. Additionally, it seeks to highlight the significance of the entrepreneurial competence of the lecturing team that goes beyond traditional teaching methods and focuses on fostering an educational environment. As entrepreneurial competence guides opportunity identification by combining skills, knowledge, and attributes and developing them into values, it bridges the gap between teaching and learning, preparing the students to cope with the challenges of the entrepreneurial world. The data were gathered by administering a structured questionnaire that focuses on the perspectives of students in the third cycle of study. The disseminated questionnaire included closed-ended questions related to the entrepreneurial education context, the entrepreneurial competence of the lecturing team, and entrepreneurial intentions. The results of this study demonstrate that the relationship between the entrepreneurial competence of lecturers and entrepreneurial education is crucial for fostering a dynamic and effective learning environment to enhance the entrepreneurial intentions of the students. Full article

Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, leading to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry and agriculture. Since their first isolation in 2013-2014, the Asian-origin H5 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and reassortment of internal gene segments. In just a few years, it supplanted other AIV clades, and now it is widespread in the wild migratory waterfowl, spreading to Asia, Europe, Africa, and the Americas. Wild waterfowl, the natural reservoir of LPAIVs and generally more resistant to the disease, also manifested high morbidity and mortality with HPAIV clade 2.3.4.4b. This clade also caused overt clinical signs and mass mortality in a variety of avian and mammalian species never reported before, such as raptors, seabirds, sealions, foxes, and others. Most notably, the recent outbreaks in dairy cattle were associated with the emergence of a few critical mutations related to mammalian adaptation, raising concerns about the possibility of jumping species and acquisition of sustained human-to-human transmission. The main clinical signs and anatomopathological findings associated with clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized. Full article

Farm crop diversity is often overlooked, predominantly indigenous crops’ role in this diversity. The main concentration has been on the contribution or role of exotic crops to household crop diversification. At the same time, the role played by both types of crops in household food security has only been aggregated, failing to show how indigenous crops play a key role in household food security. This research paper uses Tanzanian Panel data from waves 4 and 5 to study the factors influencing indigenous and exotic crop diversification and the role of this diversity in household food security. Using a random effect model, the author found that various factors are crucial in determining household crop diversification. Gender, household size, marital status, and expected harvest quantity are among the key factors influencing indigenous crop diversification. On the other hand, age, education, access to markets, access to irrigation services, and soil quality are the primary factors that affect the diversification of exotic crops. Moreover, the findings show that indigenous and exotic crop diversity significantly influences household food consumption. Thus, policies to increase the production of indigenous crops in order to improve household food consumption should be considered. Full article

To address the shortage of wireless spectrum resources caused by the rapid development of the Internet of Vehicles, spectrum sensing technology in cognitive radio is employed to tackle this issue. In pursuit of superior outcomes, a double-threshold cooperative spectrum sensing algorithm is introduced. This algorithm enhances traditional energy detection technology to mitigate the high sensitivity to noise interference in the Internet of Vehicles environment. A double-threshold judgment mechanism can be established based on the uncertainty of noise. Varying fusion rules are implemented in the collaborative spectrum sensing scheme according to the density of vehicles and the spectrum resource demand. Simulation results demonstrate that the performance of the double-threshold cooperative spectrum sensing algorithm surpasses that of the traditional single-threshold energy detection scheme, particularly evident under lower Signal-to-Noise Ratio (SNR) conditions. Moreover, the proposed algorithm exhibits superior sensing performance in environments characterized by higher noise uncertainty. Full article

Considering that the excitation method of an electric excitation synchronous motor has the disadvantages of the brush and slip ring, this article proposes a new brushless excitation system, which includes two parts: a wireless charging system and a motor. To meet the requirements of maximum transmission efficiency and constant voltage output of the system, a bilateral cooperation control strategy is proposed. For the strategy, the buck converter in the receiving side of the system can maintain maximum transmission efficiency through impedance matching, while the inverter in the transmitting side can keep the output voltage constant through phase shift modulation. In the control process, considering that the offset of coupling coils will affect the control results, a grey wolf optimization–particle swarm optimization algorithm is proposed to identify mutual inductance. Simulation and experimental results show that this identification algorithm can improve the identification accuracy and maximize the avoidance of falling into local optima. The final experimental result shows that the bilateral cooperation control strategy can maintain the output voltage around 48 V and the transmission efficiency around 84.5%, which meets the expected requirements. Full article

Fly ash has been utilized as a reinforcing material in the production of aluminum matrix composites, and in this investigation, Al-Si (LM6) fly ash composites were fabricated using the compocasting method. Various compositions of fly ash were incorporated into the samples (4, 5 and 6 wt%), and the preparation temperature ranged from 560 to 800°C. This study investigated the thermal (CTE and DTA) and chemical properties (XRD) of fly ash reinforcement and the aluminum melt in the composites. The results revealed that composites with 5 wt% of fly ash exhibited the lowest CTE value compared to those with 4 and 6 wt%. This observation was corroborated by XRD analysis, indicating a reaction between the fly ash particles and the aluminum melt. However, the DTA analysis did not find a significant impact of the addition of fly ash on the melting temperature of the prepared composites. In contrast, this study identified and investigated the existence of reaction effects between the fly ash particles and the aluminum melt. Full article

In this work, we derived a new type model for spatial Hill’s system considering the created perturbation by the parameter effect of the continuation fractional potential. The new model is considered a reduced system from the restricted three-body problem under the same effect for describing Hill’s problem. We identified the associated Lagrangian and Hamiltonian functions of the new system, and used them to verify the existence of the new equations of motion. We also proved that the new model has different six valid solutions under different six symmetries transformations as well as the original solution, where the new model is an invariant under these transformations. The several symmetries of Hill’s model can extremely simplify the calculation and analysis of preparatory studies for the dynamical behavior of the system. Finally, we confirm that these symmetries also authorize us to explore the similarities and differences among many classes of paths that otherwise differ from the obtained trajectories by restricted three-body problem. Full article

Data variability complicates reproducibility and the interpretation of experimental results. Different animal models have been employed to decrease variability to enhance experimental power. However, variation frequently persists among and within strains/lines. In zebrafish (Danio rerio), inbred lines (e.g., NHGRI-1) derived from wild-type lines have been produced to greatly decrease genetic variation, with the goal of providing better understanding of genetic backgrounds that may influence the experimental outcome of studies employing such lines. We hypothesized that variations in morphological phenotypes shaped by environmental stressors early in development are correlated with the intrinsic degree of genetic variability of zebrafish lines. We compared morphological variability (yolk–chorion ratio, body mass, embryo mass, total length, condition factor, and specific growth rate) in wild-type AB and NHGRI-1 zebrafish lines as a function of their responses to altered temperature and oxygen availability during the first 7 days post-fertilization. Overall, both lines showed similar developmental trajectories for yolk–chorion ratio, embryo mass, and total length. Additionally, condition factor and specific growth rate showed similar responses within each line, regardless of temperature and hypoxia. Importantly, the coefficient of variation for each variable was significantly lower in NHGRI-1 than AB larvae for 151 of 187 assessed morphological endpoints. Thus, the low-heterozygosity NHGRI-1 zebrafish line can be useful for decreasing inter-individual variation in morphological responses to environmental stressors, thereby aiding in the interpretation of results and enhancing experimental reproducibility. Full article

Cholera is highly endemic in many sub-Saharan African countries. The bacterium Vibrio cholerae is responsible for this severe dehydrating diarrheal disease that accounts for over 100,000 deaths each year globally. In recent years, the pathogen has been found to invade intestinal layers and translocate into the bloodstream of humans. The non-toxigenic strains of V. cholerae (non-O1/O139), also known as NOVC, which do not cause epidemic or pandemic cases of cholera, are the major culprits of V. cholerae bacteremia. In non-cholera-endemic regions, clinical reports on NOVC infection have been noted over the past few decades, particularly in Europe and America. Although low–middle-income countries are most susceptible to cholera infections because of challenges with access to clean water and inappropriate sanitation issues, just a few cases of V. cholerae bloodstream infections have been reported. The lack of evidence-based research and surveillance of V. cholerae bacteremia in Africa may have significant clinical implications. This commentary summarizes the existing knowledge on the host risk factors, pathogenesis, and diagnostics of NOVC bacteremia. Full article

In this article, we explore a variety of problems within the domain of calculus of variations, specifically in the context of fractional calculus. The fractional derivative we consider incorporates the notion of weighted fractional derivatives along with derivatives with respect to another function. Besides the fractional operators, the Lagrange function depends on extremal points. We examine the fundamental problem, providing the fractional Euler–Lagrange equation and the associated transversality conditions. Both the isoperimetric and Herglotz problems are also explored. Finally, we conclude with an analysis of the variational problem, incorporating fractional derivatives of any positive real order. Full article

Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for testing dogs and cats in a clinical setting, discussing their utility in each biomarker class. We also look at some emerging molecular biomarkers that are promising for clinical use. Finally, we discuss the hurdles that need to be overcome in going ‘bench to bedside’, i.e., the translation from discovery of genomic alterations to adoption by veterinary clinicians. As we understand more of the genomics underlying canine and feline tumours, molecular biomarkers will undoubtedly become a mainstay in delivering precision veterinary care to dogs and cats with cancer. Full article

Considering the diversity of battery data under dynamic test conditions, the stability of battery working data is affected due to the diversity of charge and discharge rates, variability of operating temperature, and randomness of the current state of charge, and the data types are multi-sourced, which increases the difficulty of estimating battery SOH based on data-driven methods. In this paper, a lithium-ion battery state of health estimation method with sample transfer learning under dynamic test conditions is proposed. Through the Tradaboost.R2 method, the weight of the source domain sample data is adjusted to complete the update of the sample data distribution. At the same time, considering the division methods of the six auxiliary and the source domain data set, aging features from different state of charge ranges are selected. It is verified that while the aging feature dimension and the demand for target domain label data are reduced, the estimation accuracy of the lithium-ion battery state of health is not affected by the initial value of the state of charge. By considering the mean absolute error, mean square error and root mean square error, the estimated error results do not exceed 1.2% on the experiment battery data, which highlights the advantages of the proposed methods. Full article

In living cells, some reactions can be conducted by more than one enzyme and sometimes it is difficult to establish which enzyme is responsible. Such is the case with proteins from the TET family, capable of converting 5-methyl-2’-deoxycytidine (5-$mdC$) in DNA to 5-(hydroxymethyl)-2’-deoxycytidine (5-$hmdC$) and further to 5-formyl-2’-deoxycytidine (5-$fdC$) and 5-carboxy-2’-deoxycytidine (5-$cadC$). The estimation of the efficiency of particular TETs in particular oxidative reactions and different cell types is important but experimentally difficult. Here, we propose an approach with mathematical modeling in which methylation and known deoxycytidine modification pathways are presented by 343 possible model versions with assumed different combinations of TET1, 2, and 3 activities in different pathways. Model parameters were calculated on the basis of 5-$mdC$, 5-$hmdC$, 5-$fdC$, 5-$cadC$, and 5-$hmdU$ levels experimentally assessed in five human cultured cell lines and previously published. Selection of the model versions that give in simulations the best average fit to experimental data suggested that not all TET proteins participate in all modification reactions and that TET3 activity may be especially important in the reaction of 5-$fdC$ removal. Full article

Background: This study aimed to investigate the association between abdominal aortic calcification (AAC) and coronary heart disease (CHD) in essential hypertension (EH). Methods: This study included patients diagnosed with EH during the 2013–2014 NHANES survey cycle. The study cohort was categorized into the following four groups based on their AAC-24 score: no AAC (0); mild AAC (1–4); moderate AAC (5–15); and severe AAC (16–24). Logistic regression models were used to assess the association between AAC and CHD. Restricted cubic spline curves (RCS) were used to explore possible nonlinear relationships between AAC and CHD. Results: The prevalence of CHD was found to be higher in the moderate AAC and severe AAC groups than in the group without AAC (40.1% versus 30.9%, 47.7% versus 30.9%). On a continuous scale, the fully adjusted model showed a 7% increase in the risk of CHD prevalence per score increase in AAC [OR (95% CI) = 1.07 (1.03–1.11)]. On a categorical scale, the fully adjusted model showed the risk of CHD prevalence in EH patients with moderate AAC and severe AAC was 2.06 (95%CI, 1.23–3.45) and 2.18 (1.09–5.25) times higher than that in patients without AAC, respectively. The RCS curve suggested a dose-response linear relationship between AAC and CHD. Conclusion: These findings highlight that in patients with EH, a higher severity of AAC is associated with a higher risk of CHD prevalence. Full article

Novel biomarkers are needed in diagnosing reliably acute kidney injury (AKI) in dogs and in predicting morbidity and mortality after AKI. Our hypothesis was that two novel tubular biomarkers, urinary clusterin (uClust) and cystatin B (uCysB), are elevated in dogs with AKI of different etiologies. In a prospective, longitudinal observational study, we collected serum and urine samples from 18 dogs with AKI of different severity and of various etiology and from 10 healthy control dogs. Urinary clusterin and uCysB were compared at inclusion between dogs with AKI and healthy controls and remeasured one and three months later. Dogs with AKI had higher initial levels of uClust (median 3593 ng/mL; interquartile range [IQR]; 1489–10,483) and uCysB (554 ng/mL; 29–821) compared to healthy dogs (70 ng/mL; 70–70 and 15 ng/mL; 15–15; p < 0.001, respectively). Initial uCysB were higher in dogs that died during the one-month follow-up period (n = 10) (731 ng/mL; 517–940), compared to survivors (n = 8) (25 ng/mL; 15–417 (p = 0.009). Based on these results, uClust and especially uCysB are promising biomarkers of AKI. Further, they might reflect the severity of tubular injury, which is known to be central to the pathology of AKI. Full article

High vertical jumping motion, which enables a humanoid robot to leap over obstacles, is a direct reflection of its extreme motion capabilities. This article proposes a single sequential kino-dynamic trajectory optimization method to solve the whole-body motion trajectory for high vertical jumping motion. The trajectory optimization process is decomposed into two sequential optimization parts: optimization computation of centroidal dynamics and coherent whole-body kinematics. Both optimization problems converge on the common variables (the center of mass, momentum, and foot position) using cost functions while allowing for some tolerance in the consistency of the foot position. Additionally, complementarity conditions and a pre-defined contact sequence are implemented to constrain the contact force and foot position during the launching and flight phases. The whole-body trajectory, including the launching and flight phases, can be efficiently solved by a single sequential optimization, which is an efficient solution for the vertical jumping motion. Finally, the whole-body trajectory generated by the proposed optimized method is demonstrated on a real humanoid robot platform, and a vertical jumping motion of 0.5 m in height (foot lifting distance) is achieved. Full article

Ralstonia eutropha strain H16 is a chemoautotrophic bacterium that oxidizes hydrogen and accumulates poly[(R)-3-hydroxybutyrate] [P(3HB)], a prominent polyhydroxyalkanoate (PHA), within its cell. R. eutropha utilizes fructose or CO₂ as its sole carbon source for this process. A PHA-negative mutant of strain H16, known as R. eutropha strain PHB⁻4, cannot produce PHA. Strain 1F2, derived from strain PHB⁻4, is a leucine analog-resistant mutant. Remarkably, the recombinant 1F2 strain exhibits the capacity to synthesize 3HB-based PHA copolymers containing 3-hydroxyvalerate (3HV) and 3-hydroxy-4-methyvalerate (3H4MV) comonomer units from fructose or CO_2. This ability is conferred by the expression of a broad substrate-specific PHA synthase and tolerance to feedback inhibition of branched amino acids. However, the total amount of comonomer units incorporated into PHA was up to around 5 mol%. In this study, strain 1F2 underwent genetic engineering to augment the comonomer supply incorporated into PHA. This enhancement involved several modifications, including the additional expression of the broad substrate-specific 3-ketothiolase gene (bktB), the heterologous expression of the 2-ketoacid decarboxylase gene (kivd), and the phenylacetaldehyde dehydrogenase gene (padA). Furthermore, the genome of strain 1F2 was altered through the deletion of the 3-hydroxyacyl-CoA dehydrogenase gene (hbdH). The introduction of bktB-kivd-padA resulted in increased 3HV incorporation, reaching 13.9 mol% from fructose and 6.4 mol% from CO₂. Additionally, the hbdH deletion resulted in the production of PHA copolymers containing (S)-3-hydroxy-2-methylpropionate (3H2MP). Interestingly, hbdH deletion increased the weight-average molecular weight of the PHA to over 3.0 × 10⁶ on fructose. Thus, it demonstrates the positive effects of hbdH deletion on the copolymer composition and molecular weight of PHA. Full article

Cardiac resynchronization therapy (CRT) significantly improves clinical outcomes in patients with ventricular systolic dysfunction and dyssynchrony. Biventricular pacing (BVP) has a class IA recommendation for patients with symptomatic heart failure with reduced ejection fraction (HFrEF) and left bundle branch block (LBBB). However, approximately 30% of patients have a poor therapeutic response and do not achieve real clinical benefit. Pre-implant imaging, together with tailored programming and dedicated device algorithms, have been proposed as possible tools to improve success rate but have shown inconsistent results. Over the last few years, conduction system pacing (CSP) is becoming a real and attractive alternative to standard BVP as it can restore narrow QRS in patients with bundle branch block (BBB) by stimulating and recruiting the cardiac conduction system, thus ensuring true resynchronization. It includes His bundle pacing (HBP) and left bundle branch area pacing (LBBAP). Preliminary data coming from small single-center experiences are very promising and have laid the basis for currently ongoing randomized controlled trials comparing CSP with BVP. The purpose of this review is to delve into the emerging role of CSP as an alternative method of achieving CRT. After framing CSP in a historical perspective, the pathophysiological rationale and available clinical evidence will be examined, and crucial technical aspects will be discussed. Finally, evidence gaps and future perspectives on CSP as a technique of choice to deliver CRT will be summarized. Full article