Weed competitive ability (WCA) is a desirable key trait for the improvement of grain yield under direct-seeded rice (DSR) and the aerobic rice ecosystem. The present study targeted screening of 167 introgression lines (ILs) of a Green Super Rice (GSR) IR2-6 population derived from a cross between Weed Tolerant Rice 1 (WTR1) as the recipient parent and Y134 as the donor parent developed at IRRI for weed competitiveness in screen house conditions (SHC). The ILs were phenotyped for WCA traits such as early seed germination (ESG) and early seedling vigor (ESV) in Petri dishes and pot experiment conditions. The results of phenotypic variance revealed ESG-related traits, especially first germination count (1st GC) that positively correlated with second germination count (2nd GC), germination percentage (GP), total dry weight (TDW), total fresh weight (TFW), and vigor index (VI-1), whereas, in ESV, all the traits were positively correlated with each other except for three traits: root dry weight (RDW), 1st GC, and GP-2. The ESG and ESV traits are vital for weed competitiveness. A 6K SNP array was used to study the genetic association for the WCA traits. Forty-four QTLs for WCA traits were mapped on all chromosomes (except on chromosomes 4 and 8) through single marker analysis (SMA). Out of 44 QTLs, 29 were associated with ESG traits and 15 with ESV traits, with LOD scores of 2.93 to 8.03 and 2.93 to 5.04 and explained phenotypic variance ranging from 7.85% to 19.9% and from 7.85% to 13.2%, respectively. However, 31 QTLs were contributed by a negative additive allele from Y134, whereas a positive additive allele was contributed by WTR1 in 13 QTLs. Among them, two QTL hotspot regions were mapped on chromosome 11 (24.7-27.9 Mb) and chromosome 12 (14.8-17.4 Mb). The majority of the QTLs related to WCA traits were grouped into two QTL hotspots: QTL hotspot-I (qAFW11.1, qFC11.1, qFC11.2, qSC11.1, qGP-111.1, qGP-111.2, qTFGS11.1, qVI-111.1, and qVI-111.2) and QTL hotspot-II (qFC12.1, qFC12.2, qSC12.1, qFC12.2, qGP-112.1, qGP-112.2, qTFGS12.1, qTFGS12.2, qVI-112.1, qIV12.2, qFC12.1, and qGC12.2), and a few of them were co-localized on chromosomes 11 and 12. Further, we fine-tuned in the genomic regions of QTL hotspots and identified a total of 13 putative candidate genes on chromosomes 11 and 12 collectively. The present study is the first report on the genetic basis of WCA-related traits and the co-localized QTLs, which could be highly valuable in future breeding programs aiming to improve WCA in rice.

Fall armyworm (FAW), Spodoptera frugiperda, has been causing significant crop losses and has now become the most economically important pest of corn globally. With the challenges arising from the extensive use of synthetic chemicals such as reports that FAW gained resistance to various insecticides, researchers are developing environmentally sound control measures to address these issues. An example is the application of the RNA interference in managing FAW populations. RNA interference is a biological process where dsRNA molecules silence specific gene of interest. Here, dsRNA fragments were generated to target Cytochrome P450 monooxygenases CYP321A7 and CYP321A8 in FAW. Mortality and phenotypic effects of RNAi-mediated knockdown of essential genes of target CYP450s through RNAi in FAW were analyzed. Results showed that RNA in vitro transcription yielded ~14 μg/μL of dsCYP321A7 and dsCYP321A8. The mortality rate of dsCYP321A7- and dsCYP321A8-fed larvae following exposure to insecticide with dual active ingredient of Chlorantraniliprole and Thiamethoxam increased by 90% and 80%, respectively as compared to dsGFP-fed larvae with 40% at 2 days post insecticide exposure. This study provided evidence for the potential of RNAi for FAW management strategies particularly for insecticide-resistant populations, including the potential for biopesticide development.

This study aims to test empirical research on the effect of financial resource ability, research and development (R & D) on innovation orientation and competitive position. This study also examines the critical mediating role of innovation orientation and competitive position to achieving new products performance (NPP). This study used a quantitative research approach by comparing data from service industry and manufacture industry in Indonesia included in Indonesian-State-Ownership companies. The analysis unit in this study used middle managers and top managers who responsible for managing divisions within the Indonesian-State-Ownership companies. The number of respondents studied in this study was 287 sample. The purposive sampling technique was used in taking the research sample. This study indicated that financial resources abilities, research and development (R & D) abilities positive effect on innovation orientation and competitive position. This study also testing the importance role of innovation orientation and a competitive position to enhancing new products performance (NPP).

The present study aims to identify tomato (Solanum lycopersicum L.) cultivars with weed-suppressive ability against target weed species in the tomato growing season. A greenhouse study was conducted with 17 tomato cultivars and target weeds Palmer amaranth (Amaranthus palmeri S. Wats), yellow nutsedge (Cyperus esculentus L.), and large crabgrass (Digitaria sanguinalis L.). Tomato plants and weed species were grown in the same pot. The height, chlorophyll, and dry weight biomass of the weeds were measured 28 days after sowing. The largest effect of tomato interference was on Palmer amaranth. Cultivar 15 reduced Palmer amaranth height, chlorophyll, and biomass by 58, 28, and 83%, respectively. Chlorophyll percentage of yellow nutsedge seedlings was suppressed by 15% by cultivar 64, whereas 13% of its height was reduced by cultivar 20. Cultivar 15 reduced biomass of yellow nutsedge by 40%. The percentage of chlorophyll of large crabgrass was reduced by 22% with cultivar 5, whereas the height and biomass were reduced by 35 and 44% with cultivars 38 and 63, respectively. Factoring all parameters evaluated, cultivars 38, 33, and 7 were most suppressive against the problematic weed species in tomato.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

A field experiment was conducted at farmer field of Sundarbazar, Lamjung during rainy season of 2020 with an objective to determine the dynamics of weed with respect different planting methods and varieties. The experiment was laid out in split plot design with three replications where five Varieties (KabreKodo 1, KabreKodo 2, Dalle 1, Okhale 1 and local) were used as the main plot factor and three planting methods (Direct sowing;10*10cm, Conventional transplanting;10*10 cm with 15 days old seedlings and System of Crop Intensification;25*25 cm with 30 days old seedlings) as sub plot factor. Result showed that among 5 genotypes of weeds based on Importance value index, Cyperusrotundus was the most dominant during the initial stage but after the first weeding, Aegeratumhaustinianum dominated the field. Weed biomass and density was recorded highest in directly sown field than that in transplanted field. Among the transplanted crop, weed infestation was seen higher in SCI than in conventionally transplanted finger millet due to wider spacing. But after the first hand weeding, due to profuse root growth and tillering in SCI, weeds were suppressed and thus weed biomass was observed higher in CT. After one hand weeding, SCI showed higher weed control index, crop resistance index and planting method efficiency index in terms of yield. Weed infestation was observed higher in Dalle 1 among varieties.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

Product innovation is a crucial factor in enterprise survival. Even though there are sources from strategic theory that guides the clear comprehension towards appreciating the nexus between these two variables (product innovation and enterprise survival), there are still many lacunas that should be addressed and filled. Consequently, the need for additional empirical corroboration or support is pertinent. This study aimed at verifying the nexus between product innovation and enterprise survival, and how they are affected by the existence of antecedent variables such as competitive intensity and competitive advantage. In the methodology, this study adopts the conduct of explanatory and cross-sectional investigations through the use of structural equation modelling (SEM) to a sample of selected food and beverages enterprises in Lagos, Nigeria. Regarding the food and beverage enterprises in Lagos, Nigeria, this study discovered that competitive intensity has huge positive implication on product innovation at (0.39; t = 5.69, p < 0.05). This gives numerical evidence that, in the face of more market competition, enterprises will be pressured to adopt the model of costs reduction on products which will enhance the reduction of product prices, and will have significant impact on profit. However, the findings reveal that there is no significance between competitive advantage and product innovation at (0.002; t = 0.203, p > 0.05), and there is no significance between product innovation and enterprise survival at (-0.035; t = -1.583, p > .05). As a result, the food and beverage enterprises should concentrate more on product innovation so that they will be able to stand the intensity of competition. The results emanated from the study is germane as it make significant contribution to literature and the body of knowledge and on strategic management by enlightening that competitive intensity is a necessary inducement for product innovation.

To achieve real-time identification of soybean seedlings and weeds in soybean seedling fields on agricultural intelligent terminal devices, this article constructs a real-time evolutionary identification system ESWIM driven by computational complexity under few-shot training. Firstly, based on the identification task, high-quality image samples are collected and annotated. By analyzing the terrain, the weather during the growth period, image acquisition methods, and the status of equipment fieldwork, we obtained a suitable enhancement algorithm. This algorithm not only effectively simulates the diversity of actual images, but also solves the problem of significant imbalance in the number of targets. Then, using the computational complexity driven approach and YOLOv5n as the foundation model, a soybean seedling and weed recognition model SWIM is constructed. The model's computational space and time complexity are reduced by 45.19% and 42.86%, respectively, while mAP (0.5) increased by 0.1%. Finally, by utilizing human-computer interaction to enable real-time and effective evolution of the dataset, an evolutionary strategy is designed to rapidly iterate and update model parameters, resulting in the development of the evolutionary system ESWIM. Laboratory experiments have shown that the ESWIM system can quickly adjust the recognition system during device operation to achieve target identification tasks in different environments.

Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images, the most appropriate model scale and training weights are determined, facilitating the development of a lightweight network. Subsequently, the introduction of the Bidirectional Feature Pyramid Network (BiFPN) during feature fusion effectively prevents the omission of weeds. Lastly, the use of Dynamic Snake Convolution (DSConv) to replace some convolutional kernels enhances flexibility, benefiting the segmentation of weeds with elongated stems and irregular edges. Experimental results indicate that the BFFDC-YOLOv8-seg model achieves a 4.9% increase in precision, an 8.1% increase in recall rate, and a 2.8% increase in mAP50 value to 98.8% on a vegetable weed dataset compared to the original model. It also shows improved mAP50 over other typical segmentation models such as Mask R-CNN, YOLOv5-seg, and YOLOv7-seg by 10.8%, 13.4%, and 1.8%, respectively. Furthermore, the model achieves a detection speed of 24.8 FPS on the Jetson Orin nano standalone device, with a model size of 6.8MB that balances between size and accuracy. The model meets the requirements for real-time precise weed segmentation, suitable for complex vegetable field environments and resource-limited laser weeding devices.

This study aimed at testing the effectiveness of novel combinations of chemical and physical methods to control Prosopis juliflora, an invasive weed in the Moshi and Simanjiro districts of Nothern Tan-zania. Six different treatments including manual uprooting, glyphosate, bark chop with chemical application, two separate chemical mixtures and control were tested in a total of 32 plots, which represented two land use types (grazing land and farmland) found in the two districts. Each plot covered 20m×30m plot area. Two response variables (stem count and tree volume) were recorded to compare weed population density before and after treatment six months later. An analysis of the untreated control plots, showed that the inherent growth potential of P. juliflora was higher in Moshi than in Simanjiro district. The number of stems increased during the experiment for all six treatments showing that the P. juliflora population had not yet reached the local carrying capacity. For the manual control treatment, the increase was reduced compared to the untreated control. For all other treatments, the increase in stem count was on par with that in the untreated control or even higher. Thus, we conclude that only manual uprooting had a controlling effect but not to the extent that it eradicated P. juliflora. Thus, it is for P. juliflora as for weed control in general: weed control must be an ongoing effort.

Healthcare personnel must face two problems of growing importance: violence in the workplace and the loss of work ability due to ageing of the workforce. Studying the relationship between these two phenomena can help to prepare effective prevention measures. In a public health company, we asked nurses to self-assess their work ability using the Work Ability Index (WAI) and we analysed the relationship between this indicator and the violence experienced in the previous and following years. 321 out of 344 nurses (99.3%) participated. In a logistic regression model, the WAI score was a significant protective factor for violence experienced in the previous year (OR=0.94 CI95%=0.90; 0.98 p&lt;0.01) and in the following year (OR=0.88 CI95%=0.84; 0.92 p&lt;0.01). In a hierarchical logistic regression model, social support acted as a protective factor (OR = 0.87 CI95% = 0.79; 0.95 for violence experienced in the previous year), while occupational stress was a significant determinant of the risk of aggression (OR=3.65 CI95%=1.90; 7.03 in the previous year, OR=3.54 CI95%=1.801; 6.947 in the following year). The difficulties that nurses encounter in carrying out their growing work demands in an environment that is not promptly adapted to their changing physical and mental conditions can lead to an increased risk of violence. Prevention of workplace violence should include organizational and ergonomic measures that reduce stress and increase staff support and work ability.

The rationale of this study is to explore underlying sustainability assessment constructs in the context of WCSM implementation as a key focus by manufacturing industries in the journey of achieving world-class status in their manufacturing operations. This study primarily intends to collect primary data from 143 plant managers and supervisors through the structured questionnaires at select manufacturing companies in south India on the basis of area-cum-purposive sampling technique. The survey questionnaire is designed exclusively to reflect the sustainability assessment dimensions in terms of social, economic and environmental issues to examine the impetus of WCSM implementation on the competitive advantage of manufacturing companies. The empirical findings of this study clearly revealed that sustainable manufacturing practices, sustainability programs, creation of sustainable products, safety for employee, community and product, operational efficiency and integration of sustainability goals in day-to-day manufacturing activities were considered to be the key indicators by the manufacturing firms in their never-ending journey towards becoming the world class. Moreover, the WCSM practices & techniques adopted by sample manufacturers have a substantial positive influence on the achievement of competitive advantage in their manufacturing and business operations.

Microcystis-dominated cyanobacterial blooms (MCBs) frequently occur in freshwaters worldwide due to massive Microcystis colonies formation and severely threaten human and ecosystems health. Quorum sensing (QS) is a direct cause of Microcystis colonies formation, possibly regulating MCBs occur and Microcystis population behaviors [1, 2]. Many novel findings in fundamental knowledge of Microcystis QS phenomenon and the signaling molecules have been documented. However, little effort has devoted to comprehensively summarize and discuss research progresses and exploration direction on QS signaling molecules-mediated QS system in Microcystis. This article summarizes action process of N-acyl homoserine lactones (AHLs) as major signaling molecules in Microcystis and discussed the detailed roles of AHLs-mediated QS system in cells aggregation, colonies formation, ecological adaptability and competitive advantage. And the progress was summarized in research on the QS mechanism in Microcystis. Compared to other QS system, the LuxI/LuxR-type QS system is more likely to found in Microcystis. Also, we introduced Quorum quenching (QQ) — QS blocking process in Microcystis, with emphasizing on the potential of QS inhibitors in MCBs control. Finally, in response to the research deficiencies and gaps in Microcystis QS and QQ, we proposed several future research directions in these fields. This review may deepen the understanding of Microcystis QS knowledge and provide theoretical guidance for the development of strategies to monitor, control and harness MCBs.

Maize mosaic virus (MMV) is a plant virus that is transmitted by the corn planthopper, Peregrinus maidis Ashmead (Hemiptera: Delphacidae) in a persistent and propagative manner. MMV is the causal agent for mosaic disease that can cause significant loss in corn yield. Management is focused on controlling insect vector population. The molecular mechanisms of virus transmission by the insect vector are not fully understood. Previously, we identified a receptor for MMV, the P. maidis syntaxin 18 (PmStx18). PmStx18 interacts with the viral glycoprotein and potentially facilitates MMV recognition and entry into the vector, enabling virus proliferation. Stx18 is a key component of the vesicular trafficking machinery and also plays a critical role in neurotransmitter release in insects. In this work, we investigated the expression of PmStx18 in different developmental stages and major parts of the insect vector. Primers were designed to generate templates for synthesis of double-stranded RNA fragments. A 374-bp amplicon was selected and gene-specific sequences were flanked by T7 promoter sequences for in vitro transcription. Results showed a significant difference in the expression of Stx18 in the different developmental stages of P. maidis but not between male and female adults and major body parts. In vitro transcription products indicated optimal reaction conditions and protocol suitability. The findings establish the initial steps for developing RNAi-based approach in controlling MMV transmission by targeting Syntaxin-18 in P. maidis. Further investigations are needed to evaluate the efficacy of this approach.

Lindernia dubia (L.) Pennell is a species with invasive behavior outside of its native range of distribution (North America), linked mainly to aquatic habitats. This annual species has been acknowledged as a weed in rice paddies in Europe and Asia. Due to the impacts of this invasive plant, some authors have even listed this species as a global invader. The present work focused on spontaneous plant species occurring in cattail seedlings grown in central Spain for the establishment of constructed wetlands. Weed inventory revealed the presence of L. dubia as a dominant spontaneous species in this crop environment. A suite of mesocosm experiments were designed to study the distribution of L.dubia versus the distribution of the other dominant plant species, and to determine traits associated with its weedy potential. Results showed that L.dubia presents competitive attributes such as morphological variability, early flowering, long seeding time, short growth cycle, small and light seeds and high seed production and germination rate (25 ⁰C), meaning a high reproductive capacity in a cycle of about three months, in non-limiting conditions for plant growth. Data from this work provide a basis for understanding the weedy potential of L.dubia, and for management decisions of a potentially invasive species, little investigated in Europe

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted, and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x10^4 – 2x10^7 CFU per ml and has a sensitivity of S = 1.655x10^5 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10^-9 grams (g), which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).

Organic soil amendments, such as composts, mitigate the environmental burdens associated with wasting organic resources. Although compost application to soil enhances an agroecosystem's capacity to store carbon and produce food, studies investigating the agronomical efficacy and their ability to ameliorate drought stress when used as a soil amendment are minimal. In this study, we produced and used a nutrient rich co-compost through the composting of sludge, a nitrogen-rich organic material with carbon rich municipal solid wastes (MSW) to evaluate the agronomic efficacy of the MSW derived co-compost and their ability to ameliorate drought stress. Application of co-compost significantly enhanced growth and yield of lettuce and maize, by a magnitude comparable to chemical fertilizers. Furthermore, under drought stress, lettuce plants grown under co-compost soil amendment grew much better with less wilting, more biomass and yield, and improved root growth. Also, co-compost application enhanced relative root mass ratio (RRMR) under drought stress, indicative that co-compost amendment increased the allocation of biomass to the roots, which is an important morphological attribute for drought adaptability. K content in both leaves and roots of plants amended with co-compost was also higher under drought stress, which may have played a role in osmotic adjustment, consequently, the plants exhibited higher leaf relative water content (RWC). Other nutrient elements that were significantly enhanced by co-compost application included Mg, Ca, Fe and Cu. These results provide evidence that MSW co-composting could optimize organic resource recycling for climate change mitigation and agricultural productivity while minimizing nutrient losses from agroecosystems.

The increasing prevalence of species that are detrimental to biodiversity is a major concern, particularly for managers of National Parks. To develop effective programs for controlling weeds, it is essential to have a thorough understanding of the extent and severity of infestations, as well as the contributing factors such as temperature, rainfall, and disturbance. Predicting these factors on a regional scale requires models that can incorporate a wide range of variables in a quantifiable manner, while also assisting with on-ground operations. In this study, we present two Bayesian Network models specifically designed for six significant weed species found along the southern coast of Australia. Our models are based on empirical data collected during a coastal weed survey conducted in 2015 and repeated in 2016. We applied these models to the coastal national parks in the isolated and pristine East Gippsland region. Importantly, the prediction models were developed at two different spatial scales that directly corresponded to the scale of the observations. Our findings indicate that coastal habitats, with their vulnerable environments and prevalence of open dune systems, are particularly susceptible to weed infestations. Moreover, adjacent regions also have the potential for colonization if these infestations are not effectively controlled. Climate-related factors play a role in moderating the potential for colonization, which is a significant concern for weed control efforts in the context of global climate change.

Weeds are among the major constraints to any crop production system, reducing productivity and profitability. Herbicides are among the most effective methods to control weeds, and reliance on herbicides for weed control has increased significantly with the advent of herbicide-resistant crops. Unfortunately, over-reliance on herbicides leads to environmental-health issues and herbicide-resistant weeds, causing human-health and ecological concerns. Crop diversification can help manage weeds sustainably in major crop production systems. It acts as an organizing principle under which technological innovations and ecological insights can be combined to manage weeds sustainably. Diversified cropping can be defined as the conscious inclusion of functional biodiversity at temporal and/or spatial levels to improve the productivity and stability of ecosystem services. Crop diversification helps to reduce weed density by negatively impacting weed seed germination and weed growth. Additionally, diversified farming systems are more resilient to climate change than monoculture systems and provide better crop yield. However, there are a few challenges to adopting a diversified cropping system, which ranges from technology innovations, government policies, farm-level decisions, climate change, and market conditions. In this review, we discuss how crop diversification supports sustainable weed management, the challenges associated with it, and the future of weed management with respect to the diversification concept.

Weed seedbank is an indication of future weed infestation potential of the species and is essential for making strategic planning for its sustainable management. Parthenium weed (Parthenium hysterophorus L.) is an invasive alien species threatening the biodiversity and the environment in Malaysia. A study was, therefore, conducted to estimate the soil seedbank of the weed at four soil depths of four villages of Kuala Muda, Kedah. The aim was to indicate the critical s of parthenium weed seedbank in Malaysia. Soil samples were collected from the sites using a soil core. The seeds were extracted from the soil samples with sieve shaker at the Universiti Malaysia Kelantan laboratory, Jeli Campus. The study indicates that the weed seedbank is in critical level at the area. The highest number of weed seeds (6915/m2) was found in Kg. Kongsi 6, followed by Kg. Sungai Tok Rawang (4481 seeds/m2). The top layer of soil, 0-5 cm, contained the maximum number of weed seeds (4878 seeds/m2) and a significant number of seeds (316 seeds/m2) were noticed at 10-15 cm soil depth. The study suggests the Malaysian government to take immediate action to control parthenium weed seedbank of the sites.

The intelligent elderly care model places new demands on the skills of aging caregivers. The identification and development of forward-thinking, high-potential nursing talent is essential for advancing the intelligent elderly care sector. Multi-benchmarking selection and competitive analysis is used to evaluate and identify nursing personnel in the rehabilitation treatment center of a hospital in Hefei City. Using proxy evaluation and democratic evaluation model, three types of benchmarks such as single item benchmark, individual benchmark and group benchmark were identified and selected, and the professional nursing team was constructed based on the evaluation results. Different from the traditional other-directed evaluation, multi-benchmarking selection and competitive analysis is self-directed evaluation, this method is more conducive to the identification of high-potential and digital nursing talents by intelligent elderly service organizations, and facilitates the formation of professional nursing teams with complementary strengths and cross-fertilization, so as to satisfy the diversified and multi-level needs of the elderly for intelligent elderly services.

Aural rehabilitation with hearing aids can decrease the attentional requirements of cognitive resources by amplifying the deteriorated-frequency sound in hearing loss patients and improve the auditory discrimination ability like speech-in-noise perception. As aural rehabilitation with an intelligible-hearing sound also can be hopeful, the aim of this study was to evaluate the effectiveness of the aural rehabilitation with intelligible-hearing sound for hearing loss patients. Adult native Japanese speakers (17 males and 23 females, 68.43±9.23 years) showed over 30 dB at 125, 250, 500, 1000, 2000, 3000, 4000, 8000, 10000, and 12000Hz on any side, were recruited and underwent Mini-Mental State Examination Japanese. we conducted self-evaluation questionnaire for hearing problems of voice, gap detection test, fast speech test, and speech-in-noise test, pure tone audiogram, speech perception test using Japanese 67-S, cortical auditory evoked fields, and magnetic mismatch negativity before and after the non-intelligible-hearing (N=20) and intelligible-hearing (N=20) sound therapy with listening to music for one hour a day for 35 days. Better hearing ear was defined using a four-frequency pure-tone average at the thresholds of 500, 1000, 2000 and 4000 Hz. After the sound therapy, speech-in-noise test with signal to noise ratio +10 in better hearing ear showed significant improvement (p&lt;0.05), and N1m-P2m amplitudes showed the significant increase in Lt superior temporal gyrus at the stimulus from better hearing ear (p&lt;0.05). The significant enhancement of the magnetic mismatch negativity amplitude at Lt superior temporal gyrus was exhibited after the sound therapy (p&lt;0.01). Intelligible-hearing sound therapy can improve the ability of speech-in-noise perception in better hearing ear and the enhancement of central cortex response, which reflect the ability of working memory, was proved by cortical auditory evoked fields and magnetic mismatch negativity. Intelligible-hearing sound therapy can be a valuable aural rehabilitation method for sensory neural hearing loss as same as hearing aids.

Deep learning is widely used in image segmentation, effectively identifying crops and weeds and contributing to the reduction of herbicide use. Traditional methods of applying pesticides over large areas are inefficient in dealing with weeds as needed, leading to massive waste of pesticides, high-cost production, and serious environmental pollution. This affects crop yield and quality. Although weed recognition using conventional deep learning methods has evolved over time, there are still challenges in weed extraction, detection, and segmentation. Accurate recognition and detection of weeds are essential prerequisites for implementing variable spraying. This paper proposes a semantic segmentation method based on UNet++ for complex environments where accurate identification of plants and weeds is challenging, targeting weeds in sugar beets, peas, and rice. An attention module is integrated into the upsampling process of UNet++, and UNet++ is used as a backbone network to effectively integrate multi-scale information, efficiently suppressing external noise interference. The UNet++ model with an integrated attention mechanism module achieves higher IOU than the general UNet++ model used in medical image analysis. This method effectively detects crops and weeds in complex backgrounds, providing reference material for the accurate application of robotic herbicides.

Verticillium wilt is a soil borne disease caused by distinct vegetative compatibility groups (VCG) of the fungus Verticillium dahliae. Two V. dahliae isolates were recovered from symptomatic cot-ton plants in Australian cotton fields and were assigned to two distinct vegetative compatibility groups (VCGs). One corresponding to the defoliating (VCG 1A) and the other non-defoliating (VCG 2A) pathotypes of Verticillium, have been transformed with Red and Green Fluorescent protein genes, respectively. The transformants maintained their ability to infect cotton and both strains were observed to colonise the xylem vessels of cotton plants. Moreover, we observed that the cotton V. dahliae strains could also infect some sampled non-Gossypium species found in the Australian landscape. The fluorescently labelled strains of V. dahliae will allow us to gain a thorough understanding of the infection processes of this important pathogen.

A crop-weed simulation model is presented to compare and evaluate Integrated Weed Management (IWM) strategies. Specifically, the model was parameterized for soybean crops in competition with Euphorbia davidii Subils. We used both, weed and crop demographic data surveyed in agronomic fields of the central zone of the Buenos Aires province, Argentina, throughout two crop cycles (2011/2012 and 2013/2014). The proposed model underwent a calibration process and subsequent validation with 70/30 % data split respectively (N=37). Two annual-based and one multiannual-based case studies were simulated to demonstrate the performance of the model. Different IWM strategies were compared under both, operational and tactical planning horizons through the evaluation of different model outcomes (i.e. crop yield, interspecific competition, economic return, and environmental impact). Our case studies results suggest that the inclusion of cultural management practices could reduce weed interspecific competition by 46 to 97 % and weed seed production by 40 to 89%. An increment in both expected crop yield, by 6 to 20%, and annual gross margin, by 44 to 199 US$.ha-1, were obtained in silico for similar levels of environmental impact.

We give a series of numerical examples of competitive evolution in the predation system, showing in some cases how the choice is made to increase the efficiency of the predation mechanism (or other significant parameters) to the detriment of populations (both of prey and predators). We then develop the mathematical theory that enables us to understand the causality involved, and identify a trend towards the emergence of the functional predation mechanism as such (and not of populations of the species involved). The realization of this trend only takes place when the conditions for it are offered by the hazards proposed to successive competitive choices. The logical structure of this trend is similar to that of the « tendency of rate of profit to fall » in certain economic models.

The relevance of bacteria to subjective experiences or qualia is under-appreciated. Here, I make four proposals. Firstly, living systems traverse sequences of active states that determine their behaviour; these states result from competitive coherence, which depends on a connectivity-based competition between a Next process and a Now process whereby elements in the active state at time n+1 are chosen between the elements in the active state at time n and those elements in the developing n+1 state. Secondly, bacteria should help us link the mental to the physical world given that bacteria were here first, are highly complex, influence animal behaviour and dominate the Earth. Thirdly, the operation of competitive coherence to generate active states in bacteria, brains and other living systems is inseparable from qualia. Fourthly, these qualia become particularly important to the generation of active states in the highest levels of living systems, namely, the ecosystem and planetary levels.

Bodybuilders utilize peaking strategies in a bid to fine-tune their aesthetics for competition day. The most prevalent peaking strategies utilized by natural bodybuilders are unreported in the current literature. Eighty-one (M - 59, F - 22) natural bodybuilders were recruited from competitions during the 2016 and 2017 British Natural Bodybuilder Federation seasons. Competitors completed a 34-item questionnaire designed to investigate peaking and contest day strategies. The questionnaire listed commonly utilized peaking strategies and provided additional space for qualitative information. Analysis of the data indicated that carbohydrate (CHO), water and sodium manipulation were the most commonly utilized peak week strategies. The consumption of high glycemic index CHO was the most common competition day strategy. Only 6.2 % of competitors reported following their regular diet the week prior to competition. The CHO manipulation strategies were similar to classical CHO loading, whereby bodybuilders attempt to maximize muscle glycogen concentrations. Furthermore, bodybuilders attempted to remove superfluous water by exploiting the diuretic/polyuria effect associated with water loading/restriction. The potentially deleterious effects of peaking on bodybuilders' health is considered and the efficacy of these strategies to enhance appearance is discussed. The findings of the present investigation are likely to be of interest to bodybuilders and their coaches.

This study evaluated the using of machine vision in combination with deep learning to identify weeds in real-time for wheat production system. PMAS-Arid Agriculture university research farm were selected for collection of images (6000 total images) of weeds and wheat crops under different weather condition. During growing season, the database was constructed to identify the weeds. For this study two framework were used TensorFlow and PyTorch under CNNs and Deep learning. Deep learning perfromed better with in PyTourch value as compared to another model in Tensorflow. comparing with other networks such as YOLOv4, we concluded that our network reaches a better result between speed and accuracy. Specifically, the maximum precision of weed and wheat plants were 0.89 and 0.91 respectively with 9.43 ms and 12.38 ms inference time per image (640 × 640) NVIDIA RTX2070 GPU.

Starting with BitTorrent and then Bitcoin, decentralized technologies have been on the rise over the last 15+ years, gaining significant momentum in the last 2+ years with the advent of platform ecosystems such as the Blockchain platform Ethereum. New projects have evolved from decentralized games to marketplaces to open funding models to decentralized autonomous organizations. The hype around cryptocurrency and the valuation of innovative projects drove the market cap of cryptocurrencies to over a trillion dollars at one point in 2017. These high valued technologies are now enabling something new: globally scaled, decentralized business models. Despite their valuation and the hype, these new business ecosystems are frail. This is not only because the underlying technology is rapidly evolving, but also because competitive markets see a profit opportunity in exponential cryptocurrency returns. This extracts value from these ecosystems, which could lead to their collapse, if unchecked. In this paper, we explore novel ways for decentralized economies to protect themselves from, and coexist with competitive markets at a global scale utilizing decentralized technologies such as Blockchain.

The shoulder region has the highest incidence of acute injuries in the sport of surfing. Little is known about the strength profile at the shoulder in a surfing cohort. The primary aim of this study was to establish the reliability of a rotator cuff strength testing procedure for surfers with a secondary aim of providing a profile of internal (IR) and external rotation (ER) strength in a competitive surfing cohort. Shoulder IR and ER isometric strength was measured using a hand-held dynamometer in 13 competitive surfers. Intra-class coefficient values ranged from 0.97 to 0.98 for intra rater reliability and were lower for inter rater reliability ranging from 0.80 to 0.91. Normalised force (N/Kg) for IR strength was significantly greater than ER strength bilaterally (dominant, p= 0.007, non-dominant, p<0.001). No significant differences (p< 0.79) were found in IR strength (N/Kg) between the dominant and non-dominant arms. ER strength (N/Kg) was significantly weaker on the non-dominant arm compared with the dominant arm (p<0.02). The non-dominant arm ER to IR ratio (0.82 ± 0.15) was significantly (p=0.025) lower than the dominant (0.88 ± 0.14) The current procedure is reliable with the same clinician, results indicate musculature asymmetry specific to the external rotators.

Intelligent fault diagnosis techniques have replaced the time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning model can improve the accuracy of intelligent fault diagnosis with the help of its multilayer nonlinear mapping ability. This paper has proposed a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in first convolutional layer for extracting feature and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform state of the art DNN model which is based on frequency features under different working load and noisy environment.

Adlay seed samples were collected from 3 adlay growing regions (Yeoncheon, Jeonnam and Eumseong regions) in Korea during 2012. Among all the samples collected, 400 seeds were tested for fungal occurrence by standard blotter and test tube agar methods and different taxonomic groups of fungal genera were detected. The most predominant fungal genera encountered were Fusarium, Phoma, Alternaria, Cladosporium, Curvularia, Cochliobolus and Leptosphaerulina. The occurrence of Fusarium species were 45.6% and based on the combined sequences of two protein coding genes, EF-1a, Beta-tubulin and phylogenetic analysis, 10 species were characterized as F. incarnatum (11.67%), F. kyushense (10.33%), F. fujikuroi (8.67%), F. concentricum (6.00%), F. asiaticum (5.67%), F. graminearum (1.67%), F. miscanthi (0.67%), F. polyphialidiom (0.33%), F. armeniacum (0.33%) and F. thapsinum (0.33%). The ability of these isolates to produce mycotoxins fumonisin (FUM) and zeralenone (ZEN) were tested by ELISA quantitative analysis method. The result revealed that fumonisin (FUM) was produced only by F. fujikuroi and zeralenone (ZEN) by F. asiaticum & F. graminearum. Mycotoxigenic species were then examined for their morphological characteristics to confirm their identity. Morphological observations of the species correlated well with their molecular identification and confirmed as F. asiaticum, F. fujikuroi and F. graminearum.

Weeds are unwanted and invasive plants that proliferate and compete for resources such as space, water, nutrients, and sunlight, affecting the quality and productivity of the desired crops. Weed detection is crucial for the application of precision agriculture methods and for this purpose machine learning techniques can be used, specifically convolutional neural networks (CNN). This study focuses on the search for CNN architectures and technology used to detect and identify weeds in different crops; 61 articles applying CNN architectures and technology were analyzed in the last five years (2019-2023). The results show the used of different devices to acquire the image for training, such as digital cameras, smartphones, and drone cameras. Additionally, the YOLO family and algorithms are the most widely adopted architectures, followed by VGG, ResNet, Faster R-CNN, AlexNet, and MobileNet, respectively. This study provides an update on CNNs that will serve as a starting point for researchers wishing to implement these weed detection and identification techniques.

Photothermal therapy (PTT) can overcome cancer treatment resistance by enhancing cell membrane permeability, facilitating drug accumulation, and promoting drug release within the tumor tissue. Iron oxide nanoparticles (IONPs) have emerged as effective agents for PTT due to their unique properties and biocompatibility. Approved for the treatment of anemia, as MRI contrast agents, and as magnetic hyperthermia mediators, IONPs also offer excellent light-to-heat conversion and can be manipulated using external magnetic field for targeted accumulation in specific tissues. Optimizing parameters such as laser wavelength, power density, shape, size, iron oxidation state, functionalization, and concentration is crucial for IONPs effectiveness. In addition to PTT, IONPs enhance other cancer treatment modalities. They improve tumor oxygenation enhancing the efficacy of radiotherapy and photodynamic therapy. IONPs can also trigger ferroptosis, a programmed cell death pathway mediated by iron-dependent lipid peroxidation. Their magneto-mechanical effect can exert mechanical force on cancer cells to destroy tumors, minimizing damage to healthy tissues. This review outlines strategies for managing photothermal performance and PTT efficiency with iron oxide nanoparticles, as well as synergies with other cancer therapies.

The popular appreciation of dry white wines is most frequently directed to young wines. However, present consumption trends comprise the valorisation of aged dry white wines. Therefore, the present work was aimed at the sensory analysis of these wines with different ages to define their sensory space and to understand which factors drive their quality evaluation by experienced tasters (critics, oenologists and students). Individuals were asked to evaluate several synthetic and aesthetic attributes and to characterise the analytic sensory profile through a Check-All-That-Apply (CATA) methodology. The quality evaluations were differently correlated with wine synthetic parameters according to the taster group. For both critics and oenologists, overall quality scores were driven by persistence and complexity. Moreover, quality was also highly correlated with power for critics and with balance for oenologists. Quality scores were highly correlated with wine browning (absorbance at 420 nm) for critics. The tasting panel showed a homogeneous analytic description of aroma, taste and mouthfeel consistent with wine age. The different ages could be associated to a continuous sensory space characterised by a decreasing perception of freshness and increase in mature and mellowed descriptors. All wines shared an austere in-mouth perception elicited by their acidity, saltiness, bitterness, smoothness and dryness. The age prediction showed that most tasters failed to guess the age wines with more than roughly 13 years old, indicating that tasters were not familiar with the sensory features of white wines with 17 to 46 years old. In conclusion, experienced tasters consistently described the sensory space and recognised the high quality of aged dry white wines. Education programs may use the defined sensory spaces according to aging and to expand the range of quality perception by consumers.

When water molecules or other particles collide with protein molecules in a solution, the protein molecules absorb some of the momentum and deform, forming a certain molecular potential energy. When a protein molecule in a high-energy state changes to a stable state, if there is a suitable substrate binding and the potential energy of the protein molecule is greater than the energy required to break the substrate chemical bond, catalytic action will occur. The α-helices and β-folds in protein molecules play a major role in converting the kinetic energy of water molecules into their own potential energy due to the large number of amino acids involved and their regular structure. The internal structural deformation of proteins caused by the impact of water molecules on α-helices and β-folds also has a profound impact on the structure of substrates. ‌

Type II diabetes is a major coronavirus disease comorbidity that can be prevented through a diet. Capsicum annuum (chili) consumption is often suggested, and using functional food cultivars is the most effective strategy. However, the general combining ability (GCA), specific combining ability (SCA), and heterotic effect of functional biochemicals (polyphenol content, antioxidant activities, and α-glucosidase inhibitory compounds) remain poorly known in C. annuum. This study aimed to estimate those parameters in C. annuum by using five different genotypes and their hybrid com-binations based on growth characteristics, yield, yield components, and fruit functional biochem-icals. The F1 and F1R progenies were obtained from crosses in a greenhouse and full diallel design. Each parent used in this study had a GCA advantage for each character. The hybrid combination of 074 x 005 and 435 x 367 displayed the best yield results. However, the results indicated the opposite regarding α-glucosidase inhibitory. The heterotic effect of functional biochemicals was observed for traits related to genotypes, polyphenol content, antioxidant activity, α-glucosidase inhibitory compounds, and similar properties related to yield and yield components, indicating their hybrid use in chili production.

The study aimed to evaluate the association between the changes in ventilatory variables (tidal volume (Vt), respiratory rate (RR), and lung ventilation (VE)) and deoxygenation of m.intescostales (∆SmO2-m.intercostales) during a maximal incremental exercise in nineteen male competitive marathon runners. The ventilatory variables and oxygen-consumption (VO2) were recorded breath-by-breath by exhaled gas analysis. A near-infrared spectroscopy device (MOXY) located in the right-hemithorax allowed recording SmO2-m.intercostales. To explore changes in oxygen levels in muscles with high demand during exercise, a second MOXY records SmO2-m.vastus laterallis. The triphasic model of exercise intensity was used for evaluating changes in SmO2 in both muscle groups. We found that ∆SmO2-m.intercostales correlated with VO2-peak (r=0.65; p=0.002) and the increase of VE (r=0.78; p=0.001), RR (r=0.54; p=0.001), but not Vt (p=0.210). The interaction of factors (muscles X exercise-phases) in SmO2 expressed as an arbitrary unit (a.u) was significant (p=0.005). At VT1 were no difference (p=0.177), but SmO2-m.intercostales was higher at VT1 (p&lt;0.001) and VO2-peak (p&lt;0.001). In competitive marathon runners, the m.intercostales deoxygenation during incremental exercise is directly associated with the aerobic capacity and increased lung ventilation and respiratory rate, but not tidal volume. Besides, it shows less deoxygenation than m.vastus laterallis at intensities above the aerobic ventilatory threshold.

This study explores the strategic importance of leveraging supplier relationships for competitive advantage in the e-commerce industry. Strong supplier relationships are crucial for enhancing operational efficiencies, cost management, quality assurance, innovation, sustainability, and overall supply chain resilience. Through collaborative partnerships, e-commerce companies can streamline logistics, reduce costs, ensure consistent product quality, and foster innovation through joint development initiatives. Ethical sourcing and sustainable practices play a pivotal role in supplier relationship management (SRM), aligning with consumer expectations and enhancing brand reputation. Advanced technologies such as AI, blockchain, and IoT further transform SRM practices by improving transparency, efficiency, and decision-making capabilities across the supply chain. The study also discusses challenges in managing global supplier relationships, emphasizing the importance of effective communication, cultural sensitivity, and strategic risk management. By addressing these challenges and nurturing trust-based relationships with suppliers, e-commerce firms can navigate market complexities and achieve sustainable growth. This research provides insights for e-commerce companies seeking to optimize their supplier relationships and maintain competitive advantage in a dynamic market environment.

Weeds can have both positive and negative effects on agricultural environments. However, despite the growing interest in the ecology of weed communities in agricultural areas, few studies have been carried out in the northern region of the Andes of Colombia, where urban and agricultural expansion have gen-erated highly disturbed scenarios. The aim of this study is to analyze the diversity of vegetation and weed seed banks in three agricultural production systems and a forest ecosystem in the northern Andes of Colombia. Hill numbers were used to compare diversity, Beta diversity to assess changes in composition, and range-abundance-dominance curves at different sites. Likewise, indicator species were analyzed to find species associations to each system. The results revealed differences in the composition of weeds between the forest ecosystem and the agricultural production systems, with higher equitability in the forest ecosystem and higher dominance in agricultural systems. A higher differentiation was observed in the dominant species of each agricultural system, highlighting those considered pests due to their life history traits, giving them greater success against various anthropogenic selection pressures. These findings highlight the impact of anthropogenic disturbances on the ecological dynamics of weed com-munities in different ecosystems, which should be considered when planning integrated weed manage-ment techniques.

Broomrape (Orobanche cumana), root parasitic weed, negatively affects sunflower, thereby causing severe yield losses and required controls on O. cumana infestation. Brassinosteroids (BRs) plays key roles in plant growth and provides resilience to weed infection. This designed study evaluated the mechanisms by which BRs ameliorates O. cumana infection in sunflower (Helianthus annuus). The pretreatment of sunflower seeds with various concentrations of BRs (1, 10, and 100 nM) were applied with and without O. cumana infestation. Under O. cumana infection, a significant reduction in plant height (38.61%), fresh/dry biomass, photosynthesis and regulation in plant defense (POX, GST), BRs signaling (BAK1, BSK1 to BSK4) and synthesis (BRI1, BR6OX2) associated genes. Moreover, O. cumana elevated the levels of MDA, OH‒, H2O2 and O2•‒ in leaves/roots by 77%/112%, 62%/104%, 57%/98% and 55%/89.4% and caused ultrastructural damages in leaves/roots, suggesting the severe oxidative or cellular damages in sunflower. In response, plants activate activities of SOD and POD enzymes as well as reduced or oxidized glutathione, but unable to stimulate APX and CAT activities. Addition of BRs, especially at 10 nM notably lowered the production of oxidative stress, activated the enzymatic and non-enzymatic antioxidants. The downregulation in the reported genes by BRs attributed to the increased resilience of sunflower (via susceptible reaction). In nutshell, the pretreatment of BRs enhanced the sunflower resistance to O. cumana infection by improving the planta growth and biomass, photosynthesis, activating the antioxidant defense system, lowering the oxidative stress, cellular damages and modulating the expression of BR synthesis and signaling genes.

Despite the productivity, achieving long-term sustainability and maintaining plant biodiversity become the pivotal goals in orchard floor management, especially along tree rows. Thus, the paradigm of eradicating weeds in the tree row using chemical herbicide or repeated soil tillage needs to be substituted with more sustainable alternatives. This study was conducted in two commercial apple and peach orchards in Marche region (Italy). Two integrated mechanical approaches, integrated mowing (mower + brush or disc) and integrated tillage (blade weeder + integrated mowing), were compared with standard herbicide system in a 2-years trial. Weed species abundance, soil coverage rate, and weed biomass productions, including gas exchange parameters, tree growth, fruit yield and quality were measured. Both integrated practices had significant effects on the number of weed species, total vegetation coverage, and dry weed biomass production. No significant differences were found in terms of tree gas exchange parameters, growth and fruit yield. However, a few fruit quality parameters such as fruit firmness, solid soluble content and dry matter content responded positively to the integrated practices. These results suggest that the integrated mechanical approaches of weed management increased orchard biodiversity, and they had no adverse effects on tree growth, fruit yield, and quality.

Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa despite the availability of resistant varieties since extreme environmental factors weakens plant defenses hence reduce CBSD resistance. This study examined the inheritance of CBSD in cassava populations, assessed genetic variability and identified superior sources of resistance through F1, S1 and half-sib offspring of populations derived from resistant sources. The offsprings underwent field evaluation at two distinct sites from 2019 to 2021, and the symptoms free genotypes were analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most resistant, resistant, most tolerant and tolerant based on symptoms and virus titer. The findings of the study indicate that the resistance to Cassava Brown Streak Disease (CBSD) is highly influenced by genotypes, F1/S1 types, and environmental conditions. The analysis of combining abilities revealed significant general combining abilities (GCA) for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates for resistance to CBSD varied between 43.4% to 63.2% for foliar symptoms and 14.6% to 57.9% for root necrosis across locations. The inheritance pattern involved a combination of additive and recessive genes and selfed (S1) populations displayed stronger and effective resistance to the disease. There was a high prevalence of cassava brown streak virus (CBSV) and a low prevalence of Ugandan cassava brown streak virus (UCBSV). Four genotypes were identified to be highly resistant to Cassava Brown Streak Disease (CBSD) that could be used as key sources of resistance to CBSD.

On average, one in ten patients die because of a diagnostic error and medical errors are the third largest cause of death in the word. While LLMs have been proposed to help doctors with diagnoses, no research results have been published on comparing the diagnostic ability of many popular LLMs on an openly accessible real-patient cohort. In thus study, we compare LLMs from Google, OpenAI, Meta, Mistral, Cohere and Anthropic using our previously published evaluation methodology and explore improving their accuracy with RAG.

The genetic development of commercial broiler led to body misconfiguration and consequent walking disabilities, mainly at the slaughter age. The present study aimed to identify broiler locomotion ability using image analysis automatically. A total of 40 broiler 40 d-old were placed to walk on a specially built runway, and their locomotion was recorded. An image segmentation algorithm was developed, and the coordinates of the bird's center of mass were extracted from the segmented images for each frame analyzed, and the Unrest Index (UI) was applied. We calculated the center of mass's movement of the broiler walking's lateral images, therefore, capturing the bird's displacement speed in the onward direction. Results indicated that broiler speed on the runway tends to decrease with the increase of the gait score. The locomotion did not differ between males or females. The proposed algorithm was efficient if predicting the broiler gait score based on their displacement speed.

We describe a competitive colorimetric assay that enables rapid and sensitive detection of galactose and reduced nicotinamide adenine dinucleotide (NADH) via colorimetric readouts and demon-strates its usefulness for monitoring NAD+-driven enzymatic reactions. We present a sensitive plasmonic sensing approach for assessing galactose concentration and the presence of NADH using galactose dehydrogenase immobilized gold nanostars (AuNS-PVP-GalDH). The AuNS-PVP-GalDH assay remains turquoise blue in the absence of galactose and NADH; however, as galactose and NADH concentrations grow, the reaction well color changes to a characteristic red color in the presence of an alkaline environment and metal ions catalyst (detection solution). As a result, when galactose is sensed in the presence of H2O2, the colored response of the AuNS-PVP-GalDH assay transforms from turquoise blue to light pink, then to wine red in a con-centration-dependent manner discernible to the human eye. This competitive AuNS-PVP-GalDH assay could be a viable analytical tool for rapid and convenient galactose quantification in re-source-limited areas.

Puerarin (PUE) is a compound isolated from the roots of Pueraria lobata. We studied the pharmacokinetics and tissue distribution kinetics of PUE in Sprague-Dawley rats following intraperitoneal administration of three concentrations. Indirect competitive ELISA based on an anti-PUE monoclonal antibody was used to determine the concentration of PUE in the blood, heart, liver, spleen, lung, kidney, hippocampus, cerebral cortex, and striatum. The plasma and tissue distribution kinetic characteristics following a single injection of PUE (20, 40, and 80 mg/kg) were calculated using a non-compartment model. In the high-dose (80 mg/kg) and medium-dose (40 mg/kg) groups, the kinetic profile of PUE in blood and kidney samples showed two absorption peaks, while that of the other tissues showed only one peak. In the low-dose (20 mg/kg) group, there was only one peak, irrespective of the sample type. Pharmacokinetic parameters such as the area under the curve, C_max, and T_max varied according to the administered dose. AUC and C_max values increased dose-dependently. PUE was widely distributed in areas of the brain such as the hippocampus, cerebral cortex, and striatum, providing a foundation for guiding the use of PUE in the treatment of cerebral ischaemic stroke and neurodegenerative diseases.

Soybean (Glycine max L.) is a vital leguminous crop known for its rich nutritional profile, includ-ing high protein and oil content, making it a valuable resource in global agriculture and human nutrition. In Pakistan due to regulatory issues non-GMO soybean is grown therefore, the universal herbicide control method is not applicable. Similarly, for other crops, specific herbicides are avail-able but for soybean no crop specific herbicide is present. A comprehensive study was conducted over two growing seasons, in 2022 and 2023, at Agronomic Research Farm University of Agri-culture Faisalabad. The research involved 16 different treatments, including both six pre-emergence and eight post-emergence herbicides as well as a control group and weedy check. Findings of this study showed that critical importance of weed management in soybean cultiva-tion, as unchecked weed infestation can lead to substantial yield losses. Among the pre-emergence herbicide S-Metolachlor + Pendimethalin performed best and showed higher plant height (54.33 cm & 53.67 cm), 100 grain weight (11.57 g & 12 g), seed yield plant-1 (13.07 g and 12.87 g), lower Susceptibility Index (10%), higher weed control percentage (91.21% & 95.65%) higher weed con-trol efficiency (92.02% & 93.43%), herbicide efficiency index (27.54% & 32.48%) and lower weed index (18.16% & 21.70%) during 2022 and 2023 respectively. However, in post emergence herbi-cide the Fluizefop-p-butyl is most effective herbicide due to less crop injury 10% Susceptibility In-dex, higher plant height (42.67 cm & 44 cm), whole plant weight (93.33 g & 95 g), 100-grain weight (11.40 g & 11.77 g), seed yield plant-1 (12.87 g & 13.13 g), higher weed control percentage (91.12% & 91.03%) higher weed control efficiency (89.73% & 92.36%, herbicide efficiency index (21.18% & 30.41%) and lower weed index (19.42% & 20.08%) in both 2022 and 2023 respectively. Notably, herbicides such as S-Metolachlor + Atrazine + Mesotrione, Topramezone, Mesosulfu-ron-methyl + Iodosulfuron-methyl sodium and Mesotrione + Atrazine led to complete plant mor-tality, resulting lethal to soybean. The findings of this study support the hypothesis that screened the best suitable herbicides with less plant injury, and higher efficiency index. So, it is recom-mended that the application of S-Metolachlor + Pendimethalin as PRE and Fluizefop-p-butyl as POST showed the least injury and best weed control results with higher grain yield.

The Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, it is worthwhile assessing its characteristics. The WAI was distributed online among the workers of a healthcare company; the results were compared with data contained in the workers' personal health records and with absence registers. 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in colleagues due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to overreport illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.

Agriculture is an important sector of European Union in societal , economic and environmental dimensions. Sustainability of the sector require improvements in its key operations. Weeding is one of the crucial operation having impact on farms’ productivity, safety for farmers, food security and environmental state. To achieve EU policy goals of sustainable agriculture there are needed new technical and organizational solutions. One of the advanced techniques are laser based weeding technique. It is important to understand well the impacts of introduction of these tech-niques to the markets and agricultural practice in sustainability context. For that reason Social Life Cycle Assessment was performed. The method was based on participatory approach. The as-sessment was carried in three perspectives: general society, farmers, and business perspective re-lated to agriculture. Expert interviews based on questionnaires and workshops were realized to get the opinions on the impacts of a new laser technique on particular aspects of its implementation. The results show generally positive impact in all perspectives, especially in the perspective of farmers.

The potential of generalized machine learning models developed for crop water estimation was examined in the current study. Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), and Random Forest (RF) are three ensembled machine learning models that were developed using all of the data from a single location from 1976 to 2017 and then immediately applied at eleven different locations without the need for any local calibration. For the test period of January 2018 to June 2020, the model's capacity to estimate the numerical values of crop water requirement (Pen-man-Monteith (PM) ETo values) was assessed. In comparison to the GBM and RF models, the XGBoost model outperformed them both marginally and significantly. The estimate's weighted standard error was smaller than 0.85 mm/day, and the model's effectiveness varied from 96% to 99% across various locations. The model's strong performance was indicated by the decreased noise-to-signal ratio. A real-time water management system at the regional level can be seamlessly linked with this type of model due to its accuracy in estimating crop water requirements and its capacity to generalize.

There has been a growing interest in incorporating psychological and neuroscientific knowledge about the development of cognitive functions in educational policies and academic practices. In this paper, we argue that the current knowledge about the interactions between these functions and their neurodevelopmental characteristics should also be considered in order to develop practices that could be better suited to pupils depending on their age. To facilitate this, we review current neuroscientific knowledge on the competitive interactions between two neural circuitry underlying distinct learning functions, their developmental trajectories and how they are linked to other functions such as cognitive control. The incorporation of this knowledge in education could help improve academic outcomes.

. (1) Background: The aim of this study was to verify the differences in body composition, power and lower limb muscle strength in futsal players from three competitive levels. (2) Methods: The study involved 68 players (24.26 ± 4.63 years), divided into three competitive levels: elite, sub-elite and amateur. To assess physical condition, we used the Inbody270, the ChronoJump and the Isokinetic Dynamometer and used the non-parametric Kruskal-Wallis test to compare the three independent variables. (3) Results: There were no differences in body composition between the players at the three competitive levels. With regard to lower limb muscle power and strength, the elite group showed, on average, better performance and capabilities, especially when compared to the amateur group, and all groups showed an H/Q ratio &gt; 60%. (4) Conclusions: We conclude that there are not many differences in physical condition between the three competitive levels of futsal, despite the unequal sporting demands between them. However, the elite group has greater power and muscle strength, and both groups showed a high probability of lower limb muscle injury at this stage of the sporting season, alerting sports training professionals to the importance of individualized analysis of physical condition and performance capacity.

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson’s R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Large language models have recently made significant progress in natural language processing, and there is observation that these models exhibit reasoning abilities when they are sufficiently large. This has sparked considerable research interest since reasoning is a hallmark of human intelligence that is widely considered missed in artificial intelligence systems. Due to large size of these models, evaluation of LLMs’ reasoning ability is largely empirical. Creating datasets to evaluate the reasoning ability of LLMs is therefore an important area of LLM research. A key open question is whether LLMs reason or simply recite memorized texts they have encountered during their training phase. This work conducts simple experiments using Cheryl’s Birthday Puzzle and Cheryl’s Age Puzzle and their variants created in this work to investigate whether LLMs recite or reason and discovers that LLMs tend to recite memorized answers for well-known questions, which appear more frequently on the internet, even though such answers may not be sensible for the modified versions of the questions. When presented with less well-known questions, it is observed that LLMs answer with correct reasoning more frequently. A possible inference is that LLMs tend to reason on less well-known questions but recite memorized answers on popular questions. As a result, to accurately evaluate the reasoning ability of LLMs, it is essential to create new datasets to ensure that LLMs are elicited to truly use their reasoning ability to generate responses to the presented questions. In view of the finding, this work proposes a new dataset comprising of unseen questions requiring semantic and deductive logical reasoning skills to elicit reasoning ability from LLMs. The proposed evaluation framework is based on the intuition that some questions or puzzles can only be answered through the mastery of reasoning needed for situational awareness, and the dataset consists of 84 logical reasoning questions on room assignment subject to constraints. The proposed evaluation framework has several desirable properties, including resilience to training data contamination, ease of response verification, extensibility, usefulness and automated test case generation. This work then applies the proposed dataset to evaluate the reasoning ability of state-of-the-art LLMs, including GPT-3, GPT-4, Llama-3.1, Gemini-1.5 and Claude-3.5, and compare their performance with the performance of human intelligence on the dataset.

Neosporosis is an infection caused by the protozoan parasite Neospora caninum and has substantial veterinary hazards. Neosporosis cannot be controlled via vaccination or a chemotherapeutic agent. Thus, accurate diagnosis followed by isolation and culling of infected animals is regarded as the most efficient way of control. In vivo diagnosis often relies on serologic testing of the animals, and milk represents a non-invasive and easy to collect sample matrix. However, ELISAs specifically designed for the antibody detection in milk are sometimes not easily available and it is tempting to use ELISA kits designed for use in serum also for milk samples. Herein, we evaluated a widely used commercial ELISA (ID Screen® Neospora caninum competition Multispecies ELISA (ID. Vet, Grabels, France)), developed for detection of N. caninum antibodies in serum samples, for its performance with milk samples instead. Milk samples from dairy ruminants (cows, buffaloes, sheep, goats; n = 149) were tested in parallel with the serum ELISA and a commercial milk ELISA as a standard test (Neospora caninum Milk Competitive ELISA, ID. Vet, Grabels, France). The detected prevalence rates were 42 (28.2%), 26 (17.4%), and 26 (17.4%) using milk ELISA, serum ELISA, and both ELISAs, respectively. Sensitivity, specificity, positive predictive value, and negative predictive value for the serum ELISA used with milk samples were 61.9%, 100%, 100%, 87%, respectively: Agreement and Kappa value between the two ELISAs were 89.3%, and 0.70, respectively. High values of Pearson correlation coefficient (0.991) and area under ROC curve (0.789) demonstrated a high diagnostic performance of serum ELISA also in milk samples. Also, Bland-Altman plot and Histogram describing the frequency of distribution of ELISA optical densities confirmed the high agreement of both serum and milk ELISAs. The current results revealed a high specificity but moderate sensitivity of the serum ELISA used for milk samples compared with the milk ELISA. However, the excellent positive predictive value of the serum ELISA makes it an alternative option in case of unavailability of milk ELISA. With this study, we provided additional evidence that a widely used serum ELISA test kit may also be used for detection of N. caninum antibodies in milk samples.

Faba bean is an important legume crop wordwide, grown both for food and feed. As for many legume crops, postemergence weed control is difficult. The aim of this work was to assess potential of intercropping on weed management by assessing the effect of mixing faba bean with different crops (wheat, barley, and pea) on weeds in the South of Spain. Four field trials were conducted over four consecutive seasons, and results found that addition alternate intercropping of faba bean and barley achieved high levels of weed control, both for coverage and biomass (92.7% and 76.6%, respectively). Intercropping with wheat did not reduce weed coverage but did decrease weed biomass by 46.1% as compared to faba bean monocrop. Intercropping with pea did not provide significant reductions for weed coverage neither for weed biomass. The diversity of the weed community was not altered by the different crop combinations tested. Additional experiments under controlled conditions were carried out to determine a possible role of barley allelopathy in weed suppression. A strong allelopathic effect entailing a reduction in the number of plants and biomass was detected for four weeds: Sinapis arvensis, Polypogon monspeliensis, Matricaria camomilla, and Medicago trucatula. It can be concluded that intercropping faba bean with barley is an excellent strategy for weed control in the Southern Spain.

Over the last five decades, weed management systems have relied primarily on synthetic herbicides. Due to the concerns over the potential impact of chemicals on human health and the environment, efforts are being made to reduce the heavy reliance on synthetic herbicides. To reduce the use of synthetic herbicides, the use of natural products such as essential oils, plant extracts, allelochemicals, agricultural by-products, and some microbes are gaining attention because of their short environmental half-life and low toxicity. They are a good alternative to synthetic herbicides, especially in organic agriculture, since they focus on environmental protection, and ecological stability. Most of the commercially available natural herbicides are non-selective and require careful application in order to preserve the cash crops. Although many studies in this direction have been undertaken, the use of these natural products is still not common because of their cost the difficulties in their synthesis due to their complex structure, cost effectiveness, poor performance, and rapid degradation. When used singly, these natural herbicides do not perform as well as the chemical herbicides. An integrated approach may provide better results. Using a combination of natural herbicides may be more effective than using just one.

Small and medium-sized enterprises (SMEs) face unique challenges that can be effectively addressed through the adoption of data mining and business intelligence (BI) tools. This systematic literature review scrutinizes the deployment and efficacy of BI and data mining technologies across SME sectors, assessing their impact on operational efficiency, strategic decision-making, and market competitiveness. Therefore, drawing from a methodologically rigorous analysis of 93 scholarly articles published between 2014 and 2024, the review elucidates the evolving landscape of BI tools and techniques that have shaped SME practices. It reveals that advanced analytics such as predictive modeling and machine learning are increasingly being adopted, though significant gaps remain, particularly shaped by economic factors. The utilization of BI and data mining enhances decision-making processes and enables SMEs to adapt effectively to market dynamics. Despite these advancements, SMEs encounter barriers such as technological complexity, high implementation costs, and substantial skills gaps, impeding effective utilization. Our review, grounded in the analysis of business intelligence tools used indicates that dashboards (31.18%) and clustering techniques (10.75%) are predominantly utilized, highlighting their strategic importance in operational settings. However, a considerable number of studies (66.67%) do not specify the BI tools or data mining techniques employed, pointing to a need for more detailed methodological transparency in future research. The predominant focus on the ICT and manufacturing sectors underscores the industrial context sector specific applicability of these technologies, with ICT accounting for 45.16% and manufacturing 22.58% of the studies. We advocate for targeted educational programs, development of user-friendly and cost-effective BI solutions, and strategic partnerships to facilitate knowledge transfer and technological empowerment in SMEs. Empirical research validating the impacts of BI and data mining on SME performance is crucial, providing a directional pathway for future academic inquiries and policy formulation.

The development of fetal organs can be impacted by systemic changes in the mother's circulation, and the placenta is essential for pregnancy homeostasis and feeding. In clinical obstetrics, oxytocin (OXT) is used to induce labor. To further explore the placental homeostasis of OXT, we compared OXT levels in neonatal cord blood among newborns whose mothers either received OXT prenatally or underwent natural labor. Our previous study revealed that the oxytocin receptor (OXTR), a vital component of the neural retina that forms the blood-retina barrier, is expressed in the retinal pigment epithelium (RPE). We hypothesized that. the formation of the neural retina and vessels within it may be impacted by perinatal OXT injection, which suggests that it may be used as a therapeutic intervention for developing eye illnesses such as retinopathy of prematurity (ROP). We first studied the amounts of OXT in neonatal cord blood. To investigate this subcellular activity, we administered OXT to mature RPE cells. With the aid of network analysis, our results suggest that perinatal administration of OXT may affect the growth of the neural retina and its corresponding retinal vessels, making it a potential therapeutic intervention for developmental eye diseases such as retinopathy of prematurity (ROP).

Sperm marking represents a valuable monitoring tool for genetic pest control strategies such as the Sterile Insect Technique, but also provides a key tool for reproductive biology studies. Sperm-marked lines can be generated by introducing transgenes that mediate the expression of fluorescent proteins during spermatogenesis. Homozygous lines established by transgenesis approaches are going through a genetic bottleneck that can lead to reduced fitness. Transgenic SIT approaches have mostly focused on Dipteran and Lepidopteran pests so far. With this study, we provide sperm-marked lines for the Coleopteran pest model organism, the red flour beetle Tribolium castaneum, based on the β2-tubulin promoter/enhancer driving red (DsRed) or green (EGFP) fluorescence. The obtained lines are reasonably competitive and were thus used for studies on reproductive biology confriming the phenomenon of ‘last male sperm precedence’ and that the spermathecae are deployed for long term sperm storage enabling the use of sperm from first matings even after secondary matings for a long period of time. The homozygosity and competiveness of the lines will enable future studies to analyze the controlled process of sperm movement into the long time storage organ as part of a post-mating cryptic female choice mechanism of this extremely promiscuous species.

The glycosaminoglycan, heparan sulphate (HS), orchestrates many developmental processes. Yet its biological role has not yet fully been elucidated. Small molecule chemical inhibitors can be used to perturb HS function and these compounds pro-vide cheap alternatives to genetic manipulation methods. However, existing chemical inhibition methods for HS also interfere with chondroitin sulphate (CS), complicating data interpretation of HS function. Herein, a simple method for the selective inhibition of HS biosynthesis is described. Using endogenous metabolic sugar pathways, Ac4GalNAz produces UDP-GlcNAz, which can target HS synthesis. Cell treatment with Ac4GalNAz resulted in defective chain elongation of the polymer and decreased HS expression. Conversely, no adverse effect on CS production was observed. The inhibition was transient and dose-dependent, affording rescue of HS expression after removal of the unnatural azido sugar. The utility of inhibition is demonstrated in cell culture and in whole or-ganisms, demonstrating that this small molecule can be used as a tool for HS inhibition in biological systems.

Abstract: Abstract: The objective of this article is to analyze the dimensions of creativity concerning students with high abilities. Firstly a review of the most relevant scientific contributions on creativity is carried out. Next the dimensions of creativity in secondary school students who have been previously identified as high- ability students are analyzed. Those abilities associated to di-vergent thinking were assessed by means of the Torrance Test of Creative Thinking [19]. The flu-ency, flexibility and originality dimensions were assessed with the Scientific-Creative Thinking Test (TPCC, [7]). The results obtained evidence that high-ability students achieve greater scores in both the figurative creativity and scientific-creativity dimensions. A significant relationship between creativity and high ability can therefore be established. This study is of an exploratory nature and the results obtained contribute to develop future studies in application of its findings in the teaching-learning process..

Canola (Brassica napus L) is a profitable grain crop for Australian growers. However, weeds remain a major constraint for its production. Chemical herbicides are used for weed control, but this tactic also leads to the evolution of herbicide resistance in different weed species. Suppression of weeds by crop competition and allelopathic mechanisms has been receiving significant attention. Here, the weed suppressive ability, and associated functional traits and stability of four selected canola genotypes (PAK85388-502, AV-OPAL, AV-GARNET and BAROSSA) were examined at different locations of NSW, Australia. Results showed that there were significant effects of canola genotypes and of genotypes by crop density interaction on weed growth. Among the tested genotypes, PAK85388-502 and AV-OPAL were the most weed suppressive and, at plant density of 10 plants/m2, they reduced weed biomass of wild radish, shepherd’s purse and annual ryegrass by more than 80%. No significant differences were found in the primary root lengths among canola varieties; however, plants of the allelopathic genotype PAK8538-502 exhibited a 35% increase in lateral root number relative to plants of non-allelopathic genotype BAROSSA. The analysis of variance revealed a significant influence of genotypes with PAK85388-502 and AV-OPAL performed the best across all the research sites. Results showed that canola genotypes PAK85388-502 and AV-OPAL were more weed suppressive than AV-GARNET and BAROSSA and may release specific bioactive compounds in their surroundings to suppress neighbouring weeds. This study provides valuable information that could be utilised in breeding programs to select weed suppressive varieties of canola in Australia. Thus, lateral root number could be a potential target trait for weed suppressive varieties. Additionally, other root architecture traits may contribute to the underground allelopathic interaction to provide a competitive advantage to the crop.

China’s leading development of a complete battery value chain for Electric Vehicles (EV) is restructuring the global automotive sector. The competitive advantage of China's EV battery industry lies on its firms’ core competency and political economic geography. Based on first-hand empirical material and data obtained from years of fieldwork in an EV battery cluster in South China, this paper identifies what the Chinese EV battery industry’s core competency is and details how it is built up from below. The current core competency of Chinese battery firms is their mass manufacturing capability to supply lithium-ion batteries vehicle manufacturers (OEMs) with stable and consistent quality as well as competitive prices. This competency is acquired by firms through technological learning at workshop level while taking use of their experiences accumulated in mass production of batteries for consumer electronics sectors. Furthermore, the rapid learning and accumulation of knowledge on battery manufacturing at large scale is also facilitated by the industrial cluster environment where firms are embedded. Supported and promoted by local government policies, Chinese EV battery clusters are composed of firms from different segments of a complete battery value chain. The findings illuminate the likely strategic strengths, weaknesses, and futures of the Chinese EV battery industry in global competition.

The Eucalyptus genus is the most planted forest crop in the world, with Brazil being one of the countries with the greatest productive potential. However, the occurrence of weeds can cause losses in productivity. Chemical control is widely used, but the efficiency of herbicides depends on factors such as the presence of straw in the soil and the occurrence of rainfall. Due to the scarcity of results regarding the interaction between herbicide, straw, and water depth in the forest sector, the objective of this study is to evaluate the efficiency of S-metolachlor + glyphosate in the control of grasses in different densities of eucalyptus straw and with simulated rain after the application of the product. The experiment was conducted in DBC, factorial 3×3×2, with four replications. The first factor represented 0, 50 and 100% of the commercial dose of S-metolachlor + glyphosate, the second 0, 5, and 10 ton ha-2 of straw, and the third 25 and 50mm of water depth applied in soil with a mix of grasses previously sowed. The rainfall simulation was performed 24 hours after herbicide application on each straw volume. The fresh mass of the aerial part of the grasses was collected 43 days after sowing and dried in an oven to determine the dry mass. Visual analyzes of the percentage of control were performed with scales ranging from 0 to 100, where 0 represents no control and 100 efficient control. The fresh and dry mass and the grasses' dry mass/water ratio decreased with increasing herbicide dosage and straw density. The dosage of 2.12 + 1.59 kg i.a. ha-1 of S-metolachlor + glyphosate resulted in greater control of grasses, and the treatments without straw and with the application of the herbicide had the highest percentages of control. Applying different water depths (25 mm or 50 mm) did not influence the control. Despite the control of grasses, the efficiency of the herbicide mixture was affected by the presence of vegetation cover.

Understanding the interaction between pharmaceuticals and serum proteins is crucial for optimizing therapeutic strategies, especially in patients with coexisting chronic diseases. The primary goal of this study was to assess the potential changes in binding affinity and competition between glipizide (GLP, a second-generation sulfonylurea hypoglycemic drug) and losartan (LOS, a medication commonly prescribed for hypertension, particularly for patients with concurrent diabetes) with non-glycated (HSA) and glycated (gHSAGLC, gHSAFRC) human serum albumin using multiple spectroscopic techniques (fluorescence, UV-visible absorption, and circular dichroism spectroscopy). The results indicate that FRC is a more effective glycation agent for HSA than GLC, significantly altering the albumin structure and affecting the microenvironment around critical amino acid residues, Trp-214 and Tyr. These modifications reduce the binding affinity of LOS and GLP to gHSAGLC and gHSAFRC, compared to HSA, resulting in less stable drug-protein complexes. The study reveals that LOS and GLP interact nonspecifically with the hydrophobic regions of the albumin surface in both binary (ligand-albumin) and ternary systems (ligand-albumin-ligandconst) and specifically saturate the binding sites within the protein molecule. Furthermore, the presence of an additional drug (GLP in the LOS-albumin complex or LOS in the GLP-albumin complex) complicates the interactions, likely leading to competitive binding or displacement of the initially bound drug in both non-glycated and glycated albumins. Analysis of the CD spectra suggests mutual interactions between GLP and LOS, underscoring the importance of closely monitoring patients co-administered these drugs to ensure optimal therapeutic efficacy and safety. Początek formularzaDół formularza

Background: After the increasingly common anterior cruciate ligament reconstruction (ACLR) procedure in competitive athletes, rehabilitation is crucial for facilitating a timely return to sports (RTS) and preventing re-injury. This pilot study investigates the biomechanical and psychological outcomes of postoperative rehabilitation in competitive athletes, comparing supervised rehabilita-tion (SVR) and home-based rehabilitation (HBR). Methods: After ACLR, 60 (out of 74 screened) athletes were recruited and equally divided into 2 groups using non-probability convenience sam-pling: 30 HBR and 30 SVR (each group comprising 15 males and 15 females). Rehabilitation out-comes in respective groups were evaluated at 8 months using measures (Tegner-Activity-Scale [TAS], International Knee Documentation Committee subjective knee form [IKDC-SKF], ACL Return to Sport after Injury [ACL-RSI]) and objective parameters (isometric muscle strength, hamstring/quadriceps asymmetry). RTS was evaluated at 9 months; with ACL re-injury rates rec-orded approximately 6 months post-RTS. Results: Both groups exhibited decreased TAS scores (HBR: 8 to 6, SVR: 8 to 7), with the SVR group demonstrating superior post-operative IKDC-SKF scores (81.82 vs. 68.43) and lower ACL-RSI scores (49.46 vs. 55.25). Isometric and isokinetic mus-cle strength, along with asymmetry values, favored the SVR group 8 months post-ACLR (p

Technological advances in tea production are critical to meet global demands for tea consumption. To illuminate differences in the scientific and commercial relevance of research programs between major tea-related research organizations around the world, we conducted a bibliometric analysis comparing the scientific outputs, including peer-reviewed publications and patents, of six major research organizations published between January 01, 2008 and July 11, 2020. For this competitive ranking analysis, we examined a number of papers, research topics, academic influence, capacity for development, capacity for collaboration, and capacity for technological innovation. Among the six research organizations, Anhui Agricultural University (in China) had the most publications, while the Chinese Academy of Agricultural Sciences, Tea Research Institute showed a higher capacity for development. The Council for Scientific and Industrial Research (in India) and the University of Shizuoka (Japan) both showed high academic influence, while the University of Shizuoka, Tea Research Association Tocklai and National Agriculture and Food Research Organization (Japan) showed a high capacity for collaboration. The Chinese Academy of Agricultural Sciences, Tea Research Institute applied for the most patents, while the Council for Scientific and Industrial Research applied for the most international patents.

Background: Medicinal plants are of great importance to health of individual and communities. About 80% of the population in Uganda relies on traditional medicine because western-trained medical personnel are limited especially in villages. Most Ugandans use Hymenoxys odorato for medicinal purposes e.g. to treat colds, fever, coughs, anti-helminthes, locally used as tea, anti-allergy and also as an anti-venom to relieve snake bites. Method: A group of 25 male wistar rats of 150 g–210 g were kept for 14 days while being fed and treated with the extract. At 14^th day, anesthesia was given and blood samples collected by cardiac puncture for hematological and biochemical investigations. Serum was analyzed for Alkaline Phosphatase, Aspartate Transaminase and Alanine Transaminase while whole blood was used for complete blood count. The liver and kidney were removed and placed in 10% formalin to prepare for histology staining using haematoxylin and eosin technique. Results: The extract elevated hepatic biomarker enzymes i.e. ALP, ALT and AST. The increase was found to be significantly different (P > 0.05) at 400 and 500 mg/kg doses as compared to the control group. Histological sections of the liver showed distortion of liver cytoarchitecture, steatosis, necrosis of hepatocytes and congestion of the sinusoids at high doses 300, 400 and 500 mg/kg body weight. In the sections of the kidney, there was mild distortion of the integrity of the kidney with glomerular hypercellularity at high doses (400 and 500 mg/kg per body weight). Conclusion: Hymenoxys odorato aqueous extract has toxic effects on the liver and kidney of wistar rats. The effects were observed to be in a dose dependent manner.

This paper detects bidding behaviors in the auction with the random cutoff, where a winning bid needs to be above and the closest to the random cutoff. In this auction, each bidder is eager to predict the random cutoff in order to use the predicted random cutoff as bid. Furthermore, one of deep learning models, the transformer model is employed as one empirical method to anticipate the random cutoff. The result shows that the predicted random cutoff turns out to be a winner with probability of about 20 percent. This paper contributes to economic literature in terms of investigating the connection between a deep learning model and an auction based on the economic theory.

In this paper, a class of coupled competitive neural networks, which subject to disturbance and discontinuous activation functions, is concerned. To realize the fixed-time quasi-bipartite synchronization, an aperiodic intermittent controller is initially designed. Subsequently, by combining the fixed-time stability theory and nonsmooth analysis, several criteria are established to ensure the bipartite synchronization in fixed time. Moreover, synchronization error bounds and settling time estimates are provided. Finally, numerical simulations are presented to verify the main results.

Background: Pulmonary emboli (PE) is a life threatening condition that is discovered in many patients only "post mortem". Adequate and timely detection of PE is crucial, because of the high mortality and morbidity and the sudden unexpected hemodynamic collapse that may occur in patients with PE. Objectives: To assess the ability to predict clinical outcome of patients with acute PE, using a non-gated computed tomography pulmonary angiography (CTPA), based on the dimensions of the right ventricle. Methods: A retrospective study that analyzed CTPA images of patients admitted with acute PE during the years 2012-2017 in Baruch Padeh Medical Center. The cohort study included 300 patients with documented acute PE, among them 255 were hospitalized in medical (non-intensive care unit) wards, and 45 were patients were hospitalized in an intensive care unit (ICU). Results: Among the 45 patients admitted to the ICU, 8% died. Larger RV diameters predicted mortality (OR=10.14, 95% CI [1.09-93.86]) as well as lower systolic and diastolic blood pressure measurements (p=0.001 and 0.01). Among the 255 patients that were admitted in the Internal Medicine Ward 7% died. Older age (p=0.028), sepsis and cancer (both p<0.001), high WBCs count (p<0.001), and renal failure (p<0.001) predicted death. Overall, of all 300 patients that were admitted, lower blood pressure (systolic and diastolic) (p<0.001, 0.008), older age (p<0.007), sepsis (p<0.001), cancer (p=0.006), higher WBCs count (p<0.001), and impaired renal function (p<0.001) predicted death among patients admitted with confirmed acute PE. Conclusions: Clinical parameters and hematological parameters could predict the outcome of patients admitted with acute PE. RV diameter, measured by the non-ECG gated CTPA had an additive predictive value for patients who were hemodynamically unstable on admission and were hospitalized in the ICU.

What does the way autistics bypass, learn, and eventually master language tell us about human linguistic ability? Here, we argue that non-social acquisition of language, in addition to representing a strong argument for nativist models of human language, may be encompassed within the human-specific orientation and mastery of complex embedded structures, of which language represents one realization. Non-social language learning could thus represent the extension of available linguistic, and non-linguistic material processed by human genetic constraints, allowing language acquisition. This deviation from typical developmental language acquisition may ultimately allow access to language, sometimes in its most elaborate forms, and also explains the possibility of the absence of its development when applied to primarily non-linguistic structured material. However, such enlargement of material-specificity does not cast doubts about its human nature. Regardless of the adaptive success or failure of non-social language learning, it is up to science, legal policies, and ethical principles to strive to maintain autism as a human potentiality to further foster our vision of a plural society.

New advances of nano-enabled weed management: using poly(epsilon-caprolactone)-based nanoherbicides. A review

Palmer amaranth (Amaranthus palmeri) is a problematic common weed species, especially in cotton (Gossypium hirsutum). With the wide use of chemical herbicide and herbicide-tolerant transgenic cotton lines, Palmer amaranth populations have developed tolerance to commonly used herbicides. It is imperative to develop alternative weed control methods to slow the evolution of herbicide-resistant weed populations and provide new sources for weed management. Eleven chromosome substitution (CS) cotton lines CS-B26lo, CS-T17, CS-B16-15, CS-B17-11, CS-B12, CS-T05sh, CS-T26lo, CS-T11sh, CS-M11sh, CS-B22sh, and CS-B22lo were screened for weed-suppressing abilities in this study. The cotton lines were tested using the established stair-step structure methodology, which provided scope to study the effect of individual CS lines on the growth and development of Palmer amaranth weed without any interference of other external factors in the greenhouse. Height (cm) and chlorophyll concentration (cci) were measured for each plant in the system. The data were analyzed as a randomized complete block design using LSD mean comparisons of the genotypes at the P≤ .05 level. The 14th day after establishment resulted in the most significant variation in Palmer amaranth height reduction among the CS lines. Results indicated that CS-B22sh had the highest effect in reducing Palmer amaranth height and chlorophyll concentration with the most heightened susceptibility for Palmer amaranth. The cluster analysis revealed that Enlist® cotton, CS-CS-B22sh, and CS-T26lo were clustered in one group suggesting similar genetic potential with reference to Palmer amaranth growth and development. CS-B22sh showed novel genetic potential to control the growth and development of Palmer amaranth, a major weed in cotton fields. In the future, it will be interesting to investigate if CS-B22sh exudates from its root contain allelochemicals able to impede the growth and development of Palmer amaranth.

Galectins play a role in lung cancer oncogenic pathways including apoptosis, t-cell immune responses, and tumor metastasis. Biomarkers that diagnose, prognose, and assist with treatment remain important, and galectins represent biomarkers that have the potential to impact lung cancer management through these pathways. Using enzyme-linked immunosorbent assay (ELISA) we examined galectin-1, -3, and -9 levels from lung cancer patient serum. Through comprehensive chart review: patient demographics, staging information, tumor biology, treatment data, and outcomes including overall survival (OS) and metastasis were retrospectively collected. Galectin levels were then compared to these numerous factors. Galectin-1, -3, and -9 levels did not correlate with cancer stage, however galectin-3 levels were lower in small cell lung cancer (SCLC) and squamous cell lung cancer than in adenocarcinoma. There was no correlation between galectin levels and previous treatment or future metastasis. Patients that had an abnormal galectin-1 level had decreased OS. Furthermore, patients with curative surgically resectable NSCLC with abnormal galectin-1 levels had decreased OS, but there was no difference in those with SCLC or that were non-resectable treated palliatively. These findings provide insight into galectin levels in various lung cancer histology and highlight the potential for galectin-1 to assist in prognosis of surgically resectable NSCLC.

Predatory mites are a type of biological control agent used in many countries against various vegetable pests, particularly spider mites. Despite the significant presence of predatory mites in the Tibetan plateau, there is limited research on their fitness and prey capacity in the area. Herein, four predatory mite species, including one species Neoseiulus californicus and three species from genus Amblyseius (Amblyseius swirskii, Amblyseius barkeri, and Amblyseius cucumeris) were investigated. Specifically, their fitness and prey capacity on two-spotted mites (Tetranychus urticae) at highland conditions were evaluated. Compared to the other three predatory species, A. swirskii had the highest fecundity (Mean ± SEM=11.60 ± 0.34) and the highest pre-adult survival rate (Mean ± SEM = 83.33 ± 3.33%). Since their juvenile Survival Rate (SR) was extremely low (Mean ± SEM =13.33% ± 5.77%), most A. barkeri nymphs died before emergence. Compared to the other three predatory mites, A. swirskii had the highest predation capacity on T. urticae adult mites at 15 d post-release (Mean ± SEM =14.28 ± 2.24). Collectively, these findings imply notable advantages in employing A. swirskii for controlling two-spotted mites in the Tibetan Plateau. Furthermore, based on the results, A. swirskii was the most effective, and A. barkeri was the least effective in controlling two-spotted mites in the Tibetan Plateau. These findings could inform the development of a feasible biological control method based on suitable predatory mite species to manage T. urticae in the Tibetan Plateau, and would be helpful in delaying the rise or emergence of chemical pesticide resistance in two-spotted mites.

In China, there is an increasing need for greater genetic diversity in maize (Zea mays L.) germplasm and hybrids appropriate for mechanical harvesting. In order to test and distinguish American maize inbred lines with exceptional combining ability, four Chinese maize inbred lines (Chang7-2, Zheng 58, four-144 and four-287) were used to judge the combining ability and heterosis of 16 USA inbred lines by a NCII genetic mating method. The results showed that among the American inbred lines, 6M502A, LH208, NL001, LH212Ht, PHW51, FBLA and LH181 expressed good GCA for yield characteristics; while RS710, PHP76, FBLA, and PHJ89 showed excellent GCA for machine harvesting characteristics. Five hybrids (NL001 × Chang7-2, LH212Ht × Chang7-2, FBLA × four-144, LH181 × four-287, PHK93 × four-287) had better SCA values for yield characteristics, at 1.69, 1.07, 1.48, 1.84 and 1.05, respectively; while NL001 × Chang 7-2, 6M502A × Chang7-2, LH212Ht × Chang7-2, LH181 × four-287, PHW51 × Chang7-2 had better TCA values for yield characteristics, at 3.03, 2.80, 2.41, 2.19 and 1.91, respectively; NL001 × Chang7-2, 6M502A × Chang7-2, LH212Ht × Chang7-2, LH181 × four-287, PHW51 × Chang7-2 showed excellent Control Heterosis values, with 21.48%, 19.64%, 15.93%, 14.05% and 11.60% increases, respectively, compared to the check and potential for future utilization in Inner Mongolian corn production.

Previous research on video game player aggression has focused on violent content, while recent studies have examined competitive factors. Few research has examined the solely impacts of competitive factors in video games without violent content on aggression, and it is still unknown what neurological processes of these effects. The present study is the first to examine the the electrophysiological characteristics of short-term competitive video game exposure and aggression. Thirty-five participants played a video game in either competitive or solo mode for 15 minutes, followed by an ERP experiment based on the Oddball paradigm and the hot sauce paradigm to measure aggressive behavior. Results showed that playing competitive game mode was associated with faster judgment to aggressive words, larger P300 amplitudes, and selection of more chili powder. The P300 amplitude partially mediated the relationship between competitive game exposure and aggressive behavior. These findings support the general aggression model.

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

New technologies such as "connected" and "autonomous" vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate, in real-time, traffic signal systems has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not "connected" vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate in real-time traffic signal systems in terms of cooperative-competitive paradigm between "connected" vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that "invisible vehicles" for the system (which are not "connected") in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

This study examines the impact of weeds on sweet corn, where weeds compete with the main agricultural crops for essential elements such as nutrients, water, sunlight, and space for growth. In general. the use of herbicides is meant to suppress weed growth. Organic matter is important for plant growth and affects herbicide persistence. The study was aimed to explore the interdependence between ametryn herbicide and organic matter content and its impacts on weed growth, herbicide persistence, and sweet corn yield. The experiment was initiated in 2022 at the Experimental Station of the Faculty of Agriculture, Padjadjaran University, Indonesia, using a Split Plot Design in a Randomized Complete Block Design (RCBD) with three replicates. The experiments consisted of three levels of organic matter, i.e. low, medium, and high and 6 levels of ametryn herbicide at 0.0 (control), 0.5, 1.0, 1.5, 2.0, 2.5 kg a.i./ha. The results indicated that the apparent interdependence between ametryn herbicide doses of 1.5, 2.0 and 2.5 kg a.i./ha and the three levels of the organic matter content totally suppressed the weed growth. However, the effects of interdependence between ametryn herbicide and organic matter content on the herbicide persistence and on the sweet corn yield were not obvious. The ametryn herbicide gave excellent effects on sweet corn yield. Bioassay analysis showed that the lowest persistence of ametryn herbicide was in line with the highest content of the organic matter.

Dicarbonyls are electrophiles able to generate the so-called advanced glycation end-products (AGEs). Human exposure occurs via ingestion (e.g., food), inhalation (e.g., electronic cigarettes) and dysregulation of endogenous metabolic pathways (e.g., glycolysis). Biological systems can prevent AGEs formation via enzymatic and nonenzymatic reactions. However, the continuous exposure to dicarbonyls may cause the depletion of endogenous substrates and the beginning of AGEs accumulation (i.e., carbonylation). Since this process has been associated with multiple disorders, several studies advocated the use of dicarbonyl binders as food preservatives or as drugs aimed at mitigating carbonylation damages. As reported for other toxicants (e.g., HNE, acrolein), the screening of selective and potent binders can be performed by measuring the residual amount of a selected dicarbonyl substrate, upon its incubation with candidate binders. Unfortunately, naturally occurring dicarbonyls are poorly responsive to many detectors (e.g., UV or MS). For this reason, most of the screening methods that have been reported to date relies on indirect quantification upon derivatization. However, this strategy can potentially lead to inaccurate results since the tested compounds can affect the derivatization yield. Therefore, we herein reported the use of benzylglyoxal (BGO) as a convenient, UV responsive, dicarboyl surrogate. By using BGO as a substrate, we setup an easy and cheap chromatographic assay for the direct measurement of the binding activity towards dicarbonyls, without derivatization. The method was qualified by assessing the binding ability of some known dicarbonyl binders, obtaining results consistent with literature.

Tests of selection based on population differentiation were performed on two highly polygenic traits important for success and quality of life: body height and educational attainment (EA). Polygenic scores (PGS) of EA and height, computed across three public genomic databases revealed differences between populations (1000 Genomes, HGDP, gnomAD) that matched the average IQ and height of ethnic groups (r ~0.9). A moderately strong correlation between latitude and EA PGS (r= 0.67) implies the effect of climate (seasonality or winter temperature) on selection for cognitive ability. The effect of latitude was reduced (β= 0.28) but remained significant after adding the sub-continental group variable to the regression model.The global Fst index revealed population differentiation at height and EA loci, significantly deviating from random SNPs. Substantial Linkage Equilibrium (LD) Decay between YRI and CEU was found (r= 0.6) but there was no correlation between LD decay and population differences in polygenic scores for EA (r= 0.015, p= 0.45), and slight inflation of height PGS difference due to LD decay (r= -0.04, p= 0.0315). Selecting the SNPs most robust to LD decay (r>0.8) resulted in larger PGS gaps for EA, but smaller for height. Finally, it is shown that PGS differences are more sensitive to the significance of GWAS loci than Fst, reflecting the major limitations of Fst as an index of selection.

We investigated preschool-aged children’s understanding of early fractional tasks and how that performance correlates with fine motor skills and use of gestures while counting. Participants were 33 preschoolers aged 4 to 5 in two Southeastern public elementary schools. Children were tested individually in an interview-like setting. Mathematics tasks were presented in a paper and pencil format and the Grooved Pegboard test assessed fine motor skills. Finally, utilization of gestures was evaluated by taking a behavioral rating of the child’s hand morphology, accuracy of gestures, and synchrony of gestures and spoken word while performing a counting task. Results indicate performance on fractional reasoning tasks significantly predicts both fine motor ability and accuracy of gestures.

In every agricultural setting, weed seeds can be found in every cubic centimeter of soil. Weed seeds, as a valuable trait underlying the fate of weed populations, exhibit differing levels of seed dormancy, ensuring their survival under uncertain conditions. Seed dormancy is considered as an innate mechanism that constrains germination under suitable conditions that would otherwise stimulate germination of non-dormant seeds. This work provides new insight into changes in germination patterns along the dormant to nondormancy continuum in seeds with physiological dormancy. Notable findings are: (1) germination synchrony can act as a new parameter that quantitatively describes dormancy patterns and subsequently weed population dynamics, (2) germination synchrony is dynamic, suggesting that the more dormancy decreases, the more synchrony is obtainable, (3) after-ripening and stratification can function as a synchronizing agent that regulates germination behavior. Brassica napus showed the most synchronous germination with the value of 3.14, while lower level of germination asynchrony was for Sinapis arvensis, with the asynchrony value of 2.25. After-ripening and stratification can act as a synchronizing factor through decreasing asynchrony level and increasing synchrony. Weed establish a firm relationship between dormancy cycling and germination synchrony patterns, ensuring their survival and reproductive strategies. By germinating in synchrony, which is accompanied by cycling mechanisms, weeds have more opportunities to persist. The synchrony model used in the present study predicts germination behavior and synchrony along the dormant to nondormancy continuum in weed seeds with physiological dormancy, suggesting a useful method for quantification of germination strategies and weed population dynamics.

Oil agents produced from degreasing treatment of synthetic fibers are typical pollutants in printing and dyeing wastewater, which may cause large-scale environmental pollution without proper treatment. How to purify oily dye wastewater with low cost is a key problem at present. In this study, the biochar microspheres with oil removal ability were prepared deriving from waste bamboo chips using hydrothermal method. The structure of biochar microsphere was regulated by the activation and modification processes. The biochar microspheres were characterized and their adsorption behaviors for oily dye wastewater were explored. The results showed that the adsorption efficiency of biochar microspheres for oily dye wastewater (DTY) was improved significantly after the secondary pyrolysis and lauric acid grafting reaction. The maximum COD removal quantity of biochar microspheres for DTY was 889 mg/g with removal rate of 86.06% in 30 min. Besides, the kinetics showed that the chemisorption was the main adsorption manner. The application of biochar microspheres can decrease the costs of oily wastewater treatment and avoid environmental pollution.

Kluyveromyces marxianus is an attractive thermotolerant yeast species for ethanol production because of its ability to utilize various carbon sources as a fermentation substrate. The use of thermotolerant microbes enables performance of high-temperature ethanol fermentation, which has several advantages including reduction of cooling costs and minimization of contamination risk. To improve K. marxianus for ethanol fermentation under stress conditions, two strains, DMKU 3-1042 and DMKU 3-118, were adapted for heat resistance and toxic substances in pulp wastewater from a paper mill, respectively, resulting in the generation of KMR1042 and KMR118, respectively. Both adapted mutants exhibited clumpy clusters of cells as pseudohyphae and altered colony morphology, and their sedimentation speeds were much faster than those of the corresponding parent strains. The two mutants showed stronger tolerance to various stresses and higher performance for ethanol production than those of the corresponding parent strains at high temperatures or in the presence of toxic substances. Genome sequencing analysis revealed that both mutants had disruption of the same gene, SWI5, despite adaptation under different stress conditions, suggesting that the formation of pseudohyphae is a common strategy of K. marxianus for coping with stresses.

Complex problem-solving (CPS) tasks have become an increasingly popular tool for understand-ing and assessing cognitive ability. These tasks have been repeatedly shown to be predictors of academic and workplace success above and beyond traditional measures of general intelligence and fluid intelligence. To date, there has been little exploration of the underlying mechanisms that drive this additional predictive utility. In this study, we examined the role of a variety of non-cognitive personality and investment traits that could drive performance on CPS tasks. Adult participants (n = 152) were recruited via M-Turk and completed a battery of personality and in-vestment trait measures, a measure of general mental ability, and a 61-trial microworlds-style CPS task. Generalised linear mixed-effects models revealed a wide variety of personality and in-vestment traits influenced task performance above and beyond general mental ability. Specifical-ly, two clusters of traits emerged as important determinants of performance: one cluster that in-fluenced the capacity to deal with the introduction of system randomness (Conscientiousness and Extraversion) and one cluster that influenced the capacity to deal with the introduction of system delays (NFC, Learning Goal Orientation, and Intellect). These findings suggest that CPS tasks do capture more than just general mental ability and may be good predictors of academic and workplace success because they tap into both cognitive ability and the motivation and willingness to engage in cognitive exploration and mental effort.

Objectives: This study aimed to determine the relationship between objective chewing ability and nutritional status of Japanese community-dwelling elders. Design: Cross sectional study. Participants: In total, 509 community-dwelling elders living in the Tokyo metropolitan area participated in a comprehensive survey occurring in October 2013. Measurements: Basic characteristics referred to sex, age, and body mass index. Undernutrition was examined through serum albumin levels. Chewing ability was examined through a color-changeable xylitol gum. By evaluating color changes in the chewing gum. Nutritional intake was examined through the semi-quantitative Food Frequency Questionnaire. Results: In the poor chewing ability group, all nutrient intake levels were significantly low, except for carbohydrates and all food groups intake levels were significantly low, except for cereals, confectionery, sugars, seasonings, and spices. Additionally, after adjusting for covariates, chewing ability showed a significant association with undernutrition. Conclusion: We concluded that chewing ability was closely associated with nutrient and different food groups intake as well as undernutrition among Japanese community-dwelling elders. Thus, in order to ensure a comprehensive nutritional management, nutritionists and dentists should collaborate when treating the same patients.

Although the number of unwed mothers have mental health problems and intellectual disability, little research have focused on their mental and cognitive status. Since there has been public stigma of unwed mother in South Korea, they tend to conceal their status and less likely to seek psychiatric and psychological help. In this context, this study aims to assess current status of their mental health and intellectual characteristics. A total 48 unwed mothers from two shelter homes in South Korea were agreed to participate in the study. To compare mental health and intellectual abilities of unwed mothers with the general women population, reference data from national studies was used. Unwed mothers were more likely to have mood disorder, post traumatic stress disorder(PTSD), alcohol and nicotine use disorder, attention-deficit hyperactivity disorder (ADHD) than the general women population. Among 48 participants, 20 (41.7%) were lower than 70 Intelligence Quotient (IQ) and the mean of IQ (78.31) was significantly lower than normalized IQ mean of general women population. In logistic regression analysis, psychiatric disorders were associated intellectual disability. This study confirmed that unwed mothers dwelling in Korean shelter homes have more experience of mental disorders and lower intellectual ability than general women population.

The study is based on the notion that big data predictive analytics is important for developing strategic alliances performance of companies. this study investigates the relationship between big data predictive analytics, big data culture, and competitive strategies 'techniques were adopted, such as descriptive statistics, correlation,regression, etc. using SPSS and SmartPLS statistical software. Hypotheses were tested with bootstrapped analysis using SEM (through SmartPLS). The study developed a structural equation model by using the SEM analysis. The results of the SEM analysis suggested the hypothesized model of the study was valid. The results supported all the hypotheses of the study.Through empirical analysis, demonstrated the conclusion is that the big data predictive analytics has a positive and significant relationship with strategic alliance performance

This review covers the last 25 years literature on analogs of suberoylanilide hydroxamic acid (SAHA, known also as Vorinostat) acting as HDAC inhibitor. In particular, the topic has been focused on the synthesis and biological activity of compounds where the phenyl group (the surface recognition moiety, CAP) of SAHA has been replaced by an azaheterocycle through a direct bond with amide nitrogen atom, and the methylene chain in the linker region is of variable length. Most of the compounds reported displayed good to excellent inhibitory activity against HDACs and in many cases showed anti-proliferative activity against human cancer cell lines.

To improve water injection effect, microemulsions (MEs) were used to wet coal seam compared with water and sodium dodecyl sulfate solution (SDS). Wetting effects were characterized by contact angle, X-ray diffraction, Fourier infrared spectroscopy. The results showed that the microemulsion has better spreadability on coal surface and has stronger wettability for coals of different ranks and different particle sizes than traditional wetting agents. The W/O type microemulsion is more affinity to coal than the O/W type and the bicontinuous type.Oxygen and hydrogen contents contributed to wetting. Different wetting agents have the greatest impact on the oxygen-containing functional group absorption zone of coal, but have little impact on the change of clay mineral composition.As the content of quartz increased, the content of montmorillonite was decreased, and the hydrophilicity of coal was increased. This research proposes new ideas for solving coal dust problems and reducing coal mine disasters.

The increasing importance of batteries in the 21st century and the challenges posed by the anticipated growth in end-of-life batteries, particularly in Europe, are addressed. Projections indicate a significant increase in battery waste, with a specific focus on the recycling of black mass (BM)—a complex and hazardous byproduct of the battery recycling process. The research employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to systematically analyze the hazardousness of BM derived from various types of batteries. The findings reveal the inherently hazardous nature of BM, classifying it under multiple hazardous properties (HPs) according to European regulations. The urgent need for a definitive legislative classification of the hazardousness of BM is emphasized, and the potential of innovative technologies and strategies to improve recycling performance while mitigating risks is highlighted. The research significantly contributes to understanding the complexities of BM recycling, providing a foundation for future advancements in this area and emphasizing the need for further exploration and economic feasibility analysis of recycling technologies.

Based on recent popular money priming research results, which conclude that money makes self-sufficient (e.g. less interest in other people), we assumed that people are less interested in finding out whether others are lying or telling the truth. In a laboratory experiment, 163 students (85 women, 78 men, M_Age = 23.08, ranging from 18 to 36 years) were primed by actively handling money (versus paper sheets). Afterwards, they classified 24 video statements as true or deceptive (senders describing their most/least favorite movie), rated their classification confidence for each decision and then answered control questions. Results revealed no influence of priming condition on judgmental bias, classification accuracy, and classification confidence. Also the level of self-reported motivation to find out who lied or told the truth did not differ between conditions. Higher motivation was correlated to higher classification confidence. Additionally, and in line with Reinhard (2010) and Reinhard et al. (2011), higher classification accuracy correlated to a higher use of verbal content cues for classification decisions. Thus, while we were able to replicate these findings, our results contradict the assumption of a money prime influence on lie detection ability. Concluding, our results make self-sufficiency in this context questionable and offer next steps for research.

: Protease-producing yeasts were isolated from potato wastes and screened for protease production on skim milk agar plates The best producer of protease isolate was identified as Clavispora lusitaniae. The strain showed better enzyme production using tomato pomace and bread waste mix as a solid fermentation substrate. The optimized conditions improved enzyme activity and showed a maximal production of 33450±503 IU/g compared with the initial activity of 11205,78 ±360 without medium optimization. A threefold increase in protease activity after medium optimization proved the reliability of using the PBD and CCD design. A 19.76-fold purified enzyme and a yield of 32.94% were obtained after purification. The protease showed maximum activity at pH 4 and 60 °C and was resistant to Tween 20, Tween 40, SDS, and β-mercaptoethanol, Ca2+, and Mg2+ stimulated it. The protease activity was strongly inhibited in the presence of urea, and EDTA. The results revealed Clavispora lusitaniae protease's ability to degrade wheat seeds and flour gluten by 98.7% and 97% respectively under pH 4 for 24 hours at 40 °C. According to this study, this enzyme could be a potential candidate for the food industry, particularly for treating wheat seed and flour to reduce the immunogenicity of gluten.