Miracle-dz/UniFAR-FTUs huggingface dataset:
Mediating effects of perceived impacts on student’s knowledge and attitudes toward climate change

of over 608,000. It is divided into three cities, Ozamiz, and Tangub, and 14 municipalities. The province's economy is primarily based on agriculture, aquaculture, and agro-industrial activities, with rice, corn, coconuts, bananas, and fruit crops being its main crops. Fish farming and marine resources also contribute significantly to the local economy. Misamis Occidental offers several tourist attractions, Mount Malindang National Park, Belveder Hoyohoy View Deck in Tangub City, and the Sinanduloy Cultural Troupe Festival. The province is accessible by land and air transportation, with Laguindingan Airport serving as the gateway. Road networks connect the province to other parts of Mindanao, with buses and vans providing public transportation services. The study involved the participation of 415 higher education students who were selected at random to ensure that the sample adequately represents the student population. Standardized questionnaires were adopted and slightly modified to provide the needed information relative to the problems. The items in the questionnaires were subjected to face validity from the pool of experts in
Isolation and identification of Trichoderma species from different Isolation and identification of Trichoderma species from different habitats and their use for bioconversion of solid waste habitats and their use for bioconversion of solid waste

: The native population of Trichoderma species collected from different habitats was quantified and characterised. The identified strains are T. harzianum (IMI-392432, 392433, 392434); T. pseudokoningii (IMI-392431) and T. virens (IMI-392430). Out of five strains, T. harzianum was the most common in all of the habitats. Colony forming units (cfu’s) of Trichoderma species varied significantly (P = 0.05) in different habitats and were positively correlated with the physico-chemical characteristics of the habitat. Trichoderma was found to have adapted to an acidic habitat. In testing for an efficient bioconversion agent, T. harzianum (IMI-392432) was found to be the most effective in kitchen waste decomposition. It provided the highest volume (31.80%) and weight (30.80%) losses in waste treated with spore suspension. Promising results were also noted using a combined treatment with different strains/species of Trichoderma , which resulted in 18% greater decomposition of waste than the control.
suggest-Short communication: The effect of delayed colostrum feeding on plasma concentrations of glucagon-like peptide 1 and 2 in newborn calves

Glucagon-like peptide (GLP)-1 is involved in glucose homeostasis via its role in stimulating insulin secretion, whereas GLP-2 increases mucosal growth of the small intestine. To our knowledge, the effect of delayed colostrum feeding on plasma GLP-1 and GLP-2 in neonatal calves has not been evaluated. To investigate the effect of delayed colostrum feeding on plasma concentrations of GLP-1 and GLP-2 in newborn calves, we randomly assigned 27 Holstein bull calves to 1 of 3 treatment groups: those fed colostrum within 1 h after birth (control), 6 h after birth (6H), and 12 h after birth (12H; n = 9 for each treatment). Blood samples were obtained before the colostrum feeding and every 3 h after each colostrum feeding for a 36-h period, and plasma concentrations of GLP-1, GLP-2, insulin, and glucose were measured. Plasma GLP-1 concentration at 12 h after colostrum feeding was lower in 12H than in control calves. In addition, plasma insulin concentration was lower in the 6H and 12H calves than in the controls. Plasma glucose and GLP-2 concentrations were, however, not affected by treatment. These results indicate that delayed colostrum feeding can decrease plasma GLP-1 and insulin concentrations without affecting glucose or GLP-2 concentration.
Identiﬁcation of Vessel Class with LSTM using Kinematic Features in Maritime Trafﬁc Control

—Prevent abuse and illegal activities in a given area of the sea is a very difﬁcult and expensive task. Artiﬁcial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS ﬂow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.
THE EVOLUTION OF LOGISTICS MANAGEMENT TOWARD THE DIGITAL TRANSITION

The digital transformation and automation become indispensable for organizations and countries due to the progress and rapid development of technology. Also, it impacts on the logistics sector. Thus, this study presents a theoretical perspective related to logistics evolution and digital transformation. On the basis of the literature review, this paper studies the logistics evolution over time and its innovations, followed by an analysis of digital transformation and its impact on logistics based on the main challenges remained to achieve digitalization. The results of the study show that logistics sector is highly impacted by the industry evolution and the introduction of information technology, which bring several challenges toward the digital transition. Also, it shows that the digitalization has many benefits for the logistics sector within technological, economic and environmental factors.
Combination of hyaluronic acid, carmellose, and osmoprotectants for the treatment of dry eye disease

Background: Dry Eye Disease (DED) is a multifactorial disease, with a high that can have a great impact on the quality of of patients. The first step of treatment includes the use of lacrimal substitutes composed of polymers, possible to associate osmoprotectant agents to the lacrimal substitutes. The aim of this article is to analyze the properties of the combination of hyaluronic acid (HA), carmellose, and osmoprotectors (Optava Fusion ® ; Allergan, Inc., Irvine, CA, USA) on DED. General considerations on the use of artificial tears are also proposed. Methods: A group of ophthalmologists, experts in the management of the ocular surface, analyzed different aspects related to DED; among them, the use of artificial tears in general and the properties of the combination of HA, carmellose, and osmoprotectors, in particular, were discussed. A review of the literature was carried out, which included different articles published in Spanish, English, and French until April 2017. Conclusions: DED is a common chronic pathology that usually requires sustained treatment. In addition, the combination of HA, carmellose, and osmoprotectors has proven to be effective in the treatment of symptoms and signs of dry eye by the synergistic action of all its components. This review provides key elements to help ophthalmologists who begin in the management of DED.
The Effects of pH on the Decay of Animal Bones

: It is a well-known fact in the forensic community that the process of soft tissue decomposition lasts much longer when the cadaver is submerged in an aqueous environment. Studies of this nature with skeletal remains are less frequently produced, and therefore there is not much supported knowledge about whether human bones would face similar effects. The human skeleton potentially undergoes physical changes over various environmental conditions, but their changes in liquid conditions are poorly understood. This experiment was a study on the macroscopic effects that pH may have on the degradation of animal bones. Various small animal bones were placed in common household solutions of differing pH for the purpose of recording any physical changes. The only notable changes observed over the course of the experiment were the drastic discoloration of solutions with higher acidity, as well as the production of sediment-like residue in the saltwater solution. Further investigation into this in the context of potential body disposal could prove useful for the future of forensic science.
Stratospheric constituent trends from ER-2 profile data

Trend analysis of the AASE ER-2 profile data reveals an average decrease in N2O on potential temperature isentropes which can be attributed to diabatic cooling of inner vortex air. This conclusion is independently supported by radiative transfer computations. Trends in ozone and water vapor over the same period are not consistent with the magnitude of the diabatic descent. After accounting for the diabatic motion (estimated from N2O) an additional 0.44±. 3%/day average anomalous O3 decrease above 440K (∼20 km) is needed to balance the continuity equation. This ozone decrease suggests additional photochemical destruction of ozone in the presence of the high amounts of ClO observed during the mission. A 0.4±0.3%/day average anomalous increase in H2O is also observed near 420K (∼18 km) which may be due to the evaporation of ice crystals falling from higher, colder stratospheric layers.
Modes of Network Governance: Structure, Management, and Effectiveness

This article examines the governance of organizational networks and the impact of governance on network effectiveness. Three basic models, or forms, of network governance are developed focusing on their distinct structural properties. Propositions are formulated examining conditions for the effectiveness of each form. The tensions inherent in each form are then discussed, followed by the role that management may play in addressing these tensions. Finally, the evolution of governance is explored. Networks have been widely recognized by both scholars and practitioners as an important form of multi-organizational governance. The advantages of network coordination in both public and private sectors are considerable, including enhanced learning, more efficient use of resources, increased capacity to plan for and address complex problems, greater competitiveness , and better services for clients and customers (see Alter and Hage 1993; Brass et al. 2004; Huxham and Vangen 2005). However, despite much progress made by researchers studying networks of organizations over the past 15 years and more, there is still a considerable discrepancy between the acclamation and attention networks receive and the knowledge we have about the overall functioning of networks. By network functioning , we refer to the process by which certain network conditions lead to various network-level outcomes. Understanding the functioning of networks is important since only then can we better understand why networks produce certain outcomes, irrespective of whether networks result from bottom-up processes or are the product of strategic decisions made by network participants or government officials. This article addresses these issues by focusing on the critical role of network gover-nance and its impact on network effectiveness. We recognize that the study of effectiveness has been problematic at both organizational (Goodman and Pennings 1977) and network (Provan and Milward 2001) levels, especially regarding the key question, ''effec-tiveness for whom? ''. Yet despite problems regarding conceptualization and measurement,
Phenology and vegetation change measurements from true colour digital photography in high Arctic tundra

Manual collection of accurate phenology data is time-consuming and expensive. In this study, we investigate whether repeat colour digital photography can be used (1) to identify phenological patterns, (2) to identify differences in vegetation due to experimental warming and site moisture conditions, and (3) as a proxy for biomass. Pixel values (RGB) were extracted from images taken of permanent plots in long-term warming experiments in three tundra communities at a high Arctic site during one growing season. The Greenness Excess Index (GEI) was calculated from image data at the plot scale (1 × 1 m) as well as for two species, Dryas integrifolia and Salix arctica. GEI values were then compared to corresponding field-based phenology observations. GEI and Normalized Difference Vegetation Index (NDVI) values from a paired set of true colour and infrared images were compared with biomass data. The GEI values followed seasonal phenology at the plot and species scale and correlated well with standardized observa.
Simple, Functional, Inexpensive Cell Extract for in vitro Prototyping of Proteins with Disulfide Bonds Author List

In vitro expression of proteins from E. coli extract is a useful method for prototyping and production of cytotoxic or unnatural products. However, proteins that have multiple disulfide bonds require custom extract that, to date, requires careful addition of exogenous isomerase enzymes or the use of expensive commercial kits. This cost and complexity currently limit access to some groups who wish to rapidly prototype proteins with disulfide bonds. Herein, we present a simple solution that does not require addition of supplemental enzymes. We use a commercially available SHuffle T7 Express lysY strain of E. coli that expresses both T7 RNAP and DsbC isomerase enzymes. We experimentally determine optimal growth conditions (IPTG induction and harvest times) to balance overall productivity and efficiency of disulfide bond formation using a luciferase (from Gaussia princeps ) that contains five disulfide bonds as our reporter protein. We also demonstrate the ability for rapid prototyping by screening the activity of four luciferase candidates against ten luciferin analogues. To display the broad applicability of the extract, three other enzymes containing ≥ 3 disulfide bonds (hevamine, endochitinase A, and periplasmic AppA) were also expressed from minimal genetic templates that had undergone rolling circle amplification and confirmed via activity assays.
Role of Artificial Intelligence in drug development

In the last decade, artificial intelligence (AI) has revolutionised the field of drug research. Staff abilities (55 percent), data structure (52 percent), and resources were all factors in AI deployment (49 percent). Nearly 60% of respondents said they expected to hire more people in the next two years to assist AI usage or adoption in drug development. AI in areas like as drug research and development, drug repurposing, boosting pharmaceutical productivity, and clinical trials, among others, minimises human effort and allows for the achievement of objectives in a short amount of time. On the one hand, AI techniques used in drug development bring the drug development process and the use of various models closer to medicinal chemists, while on the other hand, AI methods used in drug development bring the drug development process and the use of various models closer to mathematicians
In Vitro Efﬁcacy of Antibiotics Commonly Used To Treat Human Plague against Intracellular Yersinia pestis (cid:1)

Yersinia pestis initiates infection as a facultative intracellular parasite in host macrophages; however, little is known about the efﬁcacy of antibiotics commonly used to treat human plague against intracellular Y. pestis . Intracellular minimal bactericidal concentrations (MBCs) were determined using a high-throughput broth microdilution assay in which human THP-1 macrophage-like cells were infected with Y. pestis strain KIM6-2053.1 (cid:1) and exposed to 2-fold serial dilutions of antibiotics for 24 h in 96-well plates. The numbers of CFU, upon which minimal bactericidal concentrations were based, were determined by counting “microcolonies” in wells of 96-well plates following lysis of tissue culture cells to release surviving Y. pestis , replica dilution, and plating in soft tryptic soy broth agar. For THP-1 cells, streptomycin and ciproﬂoxacin had comparable efﬁcacies for intra-and extracellular Y. pestis , but the MBCs for chloramphenicol, gentamicin, doxycycline, and amoxicillin were two-, three-, four, and ﬁve 2-fold serial dilutions greater, respectively, for intracellular than for extracellular Y. pestis . During the initial stage of plague, intracellular Y. pestis
WGCNA-Based Identi�cation of Hub Genes and Key Pathways Involved in Obesity

The prevalence of obesity is increasing, yet its pathogenesis and therapeutic targets are still unclear, and the e�cacy of existing therapeutic modalities is limited. Therefore, it is crucial to elucidate the molecular mechanisms underlying the pathogenesis of obesity and to explore potential molecular targets for obesity drug therapy. The expression dataset (GSE73304) was downloaded from the Gene Expression Omnibus database (GEO), and the data were divided into C and P groups, which were normalized for differentially expressed genes analysis (DEGs), Gene Set Enrichment Analysis (GSEA) and weighted gene co-expression network analysis (WGCNA). The intersecting genes obtained by DEGs and WGCNA were analyzed by three machine learning methods (LASSO, RandomForest, SVM-REF), and the gene ROC curves, genetic differences between groups and correlations between genes were analyzed after obtaining the major genes. Based on WGCNA and machine learning, this study found that several genes were signi�cantly different between healthy and obese populations and closely associated with multiple molecular mechanisms, and these genes may serve as potential targets for drug therapy and diagnostic biomarkers, which need further studies to elucidate.
Exploring supply chain ﬁ nance along different supply chain stages: a case-based research in the agri-food industry

Purpose – Since 2008 ’ s ﬁ nancial crisis, attention toward supply chain ﬁ nance (SCF) has increased. However, most research investigates SCF considering single supply chain (SC) stages or buyer – supplier dyads and focuses on a single SCF solution. It is important to see how different solutions are adopted at different SC stages, by actors with different ﬁ nancing needs. This study aims to analyze SCF at different SC stages, to understand why different solutions are implemented at different SC stages and the contingency factors (regulation, SC stage, product category and size) in ﬂ uencing their adoption. Design/methodology/approach – The paper is based on multiple exploratory case studies in the Italian agri-food industry, considering ﬁ rms distributed at different SC stages and adopting multiple SCF solutions. The paper exploits a contingent approach (Sousa and Voss, 2008) to analyze how contingent factors in ﬂ uence SCF adoption at different SC stages. Findings – Findings explain how and why different SC stages (producer, cooperative, processor and retailer) implement different SCF solutions (reverse factoring, dynamic discounting, inventory ﬁ nance and Minibond), describing contingency variables ’ impact on their adoption. Originality/value – To the best of the authors ’ knowledge, the research is original in its description of SCF at different SC stages, considering different SC actors ’ drivers and barriers, and questioning the importance of a coordinated approach in SCF adoption along an entire SC. Moreover, the paper adopts a contingent approach, contributing to SCF research, seldomly based on theoretical lenses.
A comparison on characteristics of climate change in the north and south of Tianshan Mountain

Based on the temperature and precipitation date from 1951 to 2008 in typical weather stations in the north and south of Tianshan Mountain of Xinjiang,using regression analysis and trend analysis,we compared the trends and characteristics of climate changes in the north and south of Tianshan Mountain in recent 58 years.The results indicated the characteristics of climate changes in the north of Tianshan Mountain were warming-wetting,the average temperatures per year increased the precipitations also increased the characteristics of climate changes in the south of Tianshan Mountain were warming-wetting,but because of the special location,the characteristics of climate changes in the south of Tianshan Mountain were different,they showed different trends and characteristics.Overall,the climate of Xinjiang became warming-wetting,it was different from the eastern monsoon region's,which became warming-drying.
Swine inﬂuenza: clinical, serological, pathological, and virological cross-sectional studies in nine farms in Argentina

Background Inﬂuenza A viruses (IAV) are important pathogens responsible for economic losses in the swine industry and represent a threat to public health. In Argentina, clinical, pathological, and virological ﬁndings suggest that IAV infection is widespread among pig farms. In addition, several subtypes of IAV, such as pH1N1, H3N2, d 1H1N1, and d 2H1N2, have been reported. Objectives To evaluate the infection patterns of inﬂuenza virus in nine pig farms in Argentina. Methods Clinical, serological, pathological, and virological cross-sectional studies were conducted. Results Clinical and pathological results were characteristic of endemic inﬂuenza infection in eight of the nine farms studied. By rRT-PCR, six of the nine farms were positive to inﬂuenza. Five IAV were obtained. Genome analysis determined that four of the isolations were pH1N1 and that the remaining one was a reassortant human origin H3N2 virus containing pandemic internal genes. Serological results showed that all farms were positive to inﬂuenza A antibodies. Moreover, the hemagglutination inhibition test showed that infection with viruses containing HA ′ s from different subtypes (pH1, d 1H1, d 2H1, and H3) is present among the farms studied and that coinfections with two or more subtypes were present in 80.5% of positive pigs. Conclusions Because vaccines against IAV are not licensed in Argentina, these results reﬂect the situation of IAV infection in non-vaccinated herds. This study provides more information about the circulation and characteristics of IAV in a poorly surveyed region. This study provides more data that will be used to evaluate the tools necessary to control this disease.
Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models

The integration of an ensemble of deep learning models has been extensively explored to enhance defense against adversarial attacks. The diversity among sub-models increases the attack cost required to deceive the majority of the ensemble, thereby improving the adversarial robustness. While existing approaches mainly center on increasing diversity in feature representations or dispersion of first-order gradients with respect to input, the limited correlation between these diversity metrics and adversarial robustness constrains the performance of ensemble adversarial defense. In this work, we aim to enhance ensemble diversity by reducing attack transferability. We identify second-order gradients, which depict the loss curvature, as a key factor in adversarial robustness. Computing the Hessian matrix involved in second-order gradients is computationally expensive. To address this, we approximate the Hessian-vector product using differential approximation. Given that low curvature provides better robustness, our ensemble model was designed to consider the influence of curvature among different sub-models. We introduce a novel regularizer to train multiple more-diverse low-curvature network models. Extensive experiments across various datasets demonstrate that our ensemble model exhibits superior robustness against a range of attacks, underscoring the effectiveness of our approach.