Miracle-dz/UniFAR-FTUs huggingface dataset:
TRAP transporters: an ancient family of extracytoplasmic solute-receptor-dependent secondary active transporters.

Tripartite ATP-independent periplasmic transporters (TRAP-T) represent a novel type of secondary active transporter that functions in conjunction with an extracytoplasmic solute-binding receptor. The best characterized TRAP-T family member is from Rhodobacter capsulatus and is specific for C4-dicarboxylates [Forward, J. A. , Behrendt, M. C. , Wyborn, N. R. , Cross, R. & Kelly, D. J. (1997). J Bacteriol 179, 5482-5493]. It consists of three essential proteins, DctP, a periplasmic C4-dicarboxylate-binding receptor, and two integral membrane proteins, DctM and DctQ, which probably span the membrane 12 and 4 times, respectively. Homologues of DctM, DctP and DctQ were identified in all major bacterial subdivisions as well as in archaea. An orphan DctP homologue in the Gram-positive bacterium Bacillus subtilis may serve as a receptor for a two-component transcriptional regulatory system rather than as a constituent of a TRAP-T system. Phylogenetic data suggest that all present day TRAP-T systems probably evolved from a single ancestral transporter with minimal shuffling of constituents between systems. Homologous TRAP-T constituents exhibit decreasing degrees of sequence identity in the order DctM > DctP > DctQ. DctM appears to belong to a large superfamily of transporters, the ion transporter (IT) superfamily, one member of which can function by either protonmotive force- or ATP-dependent energization. It is proposed that IT superfamily members exhibit the unusual capacity to function in conjunction with auxiliary proteins that modify the transport process by providing (i) high-affinity solute reception, (ii) altered energy coupling and (iii) additional yet to be defined functions.
A WAY WITH WORDS: A Unique Approach to Literacy and Career Development

This article describes a unique collaboration between the Career Center at the University of Missouri–Columbia, Columbia Public Schools and the community. A WAY WITH WORDS is an “America Reads” community literacy program that has enriched the educational experience of graduate, undergraduate and K–5 students since 1996. Teams of undergraduate volunteers led by graduate students in Counseling Psychology and Educational Leadership (ELPA) tutor local children in an effort to increase literacy. The teams interact and communicate with children, parents, teachers and principals as they serve during school and in after-school programs that they co create with school administrators and community members. Tremendous opportunities exist for learning about socio-economically and increasing ethnically diverse communities. During a biweekly seminar, team leaders lead career exploration activities that focus on mentoring, multicultural issues and team building. The program seeks to cultivate civic responsibility as an aspect of career development through communication, relatedness and reflection.
Contact languages based on languages from Africa, Asia, Australia, and the Americas

Introduction AFRICAN-BASED LANGUAGES 1. Kikongo-Kituba 2. Sango 3. Lingala 4. Fanakalo 5. Mixed Ma'a/Mbugu 6. Kinubi 7. Juba Arabic ASIAN-BASED LANGUAGES 8. Chinese Pidgin Russian 9. Sri Lankan Malay 10. Singapore Bazaar Malay 11. Ambon Malay 12. Yimas-Arafundi Pidgin 13. Pidgin Hindustani 14. Pidgin Hawaiian AUSTRALIAN-BASED LANGUAGE 15. Gurindji Kriol LANGUAGES BASED ON LANGUAGES OF THE AMERICAS 16. Media Lengua 17. Chinuk Wawa 18. Michif 19. Eskimo Pidgin Language Index
Periodontally Accelerated Osteogenic Orthodontics (PAOO): Perio-Ortho Interrelationship

Surgical intervention to involve the alveolar housing and influence the tooth movement has been described in various forms since 19 century. Periodontally Accelerated Osteogenic Orthodontics (PAOO) is an interdisciplinary clinical procedure that combines selective alveolar corticotomy, particulate bone grafting, and the application of orthodontic forces. This procedure facilitates faster orthodontic tooth movement and is theoretically based on the bone healing pattern known as the Regional Acceleratory Phenomenon (RAP). PAOO results in an increase in alveolar bone width, shorter treatment time, increased post treatment stability and decreased alveolar bone dehiscence. This article describes a case where PAOO technique was utilized for accelerated orthodontic closure of extraction space between maxillary right canine and second premolar in a young female with Class I malocclusion with bimaxillary protrusion.
Enhancing Fleet Operations with a Vehicle Route Management Solution

A vehicle route management solution is a software tool that helps fleet managers optimize their fleet operations by planning and monitoring the routes that their vehicles take. This solution uses local search meta-heuristics and real-time data to determine the most efficient routes, which can help reduce fuel consumption, increase vehicle utilization, and improve customer satisfaction. The benefits of using a vehicle route management solution are numerous. For instance, it can help fleet managers reduce operational costs by reducing the amount of fuel consumed by their vehicles. This is achieved by optimizing the routes that the vehicles take, thereby minimizing the distance travelled, and reducing fuel consumption. Additionally, a vehicle route management solution can help increase vehicle utilization by ensuring that vehicles are used efficiently. This helps customers plan their day more effectively, and reduces the frustration caused by unexpected delays. In conclusion, a vehicle route management solution is a valuable tool for fleet managers who want to optimize their fleet operations. By using algorithms and real-time data to determine the most efficient routes, this solution can help reduce operational costs, increase vehicle utilization, and improve customer satisfaction. The application is designed to be scalable and customizable, which means that it can be adapted to meet the specific needs of different transportation companies and local authorities. It can be used to optimize routes for both urban and rural areas, as well as for different types of vehicles and passenger loads. Overall, the vehicle route optimization web application is a powerful tool that can help transportation companies and local authorities operate more efficiently and provide better service to their customers.
Industry 5.0: Enhancing Human-Robot Collaboration through Collaborative Robots – A Review

Modern production systems are currently changing, moving from mass production to mass customization logic, as described in Industry 5.0. The aim of Industry 5.0 is to outperform conventional manufacturing techniques by creating interconnected systems that include everything from machinery, robots, and workers to goods and consumers. This is accomplished by fully integrating the physical and virtual worlds. It focuses on building intelligent hybrid workspaces where robots share labour-intensive duties to increase productivity and safety in a range of industrial sectors. Cobots, or collaborative robots, are introduced in this. Cobots are becoming more prevalent in modern industrial systems because they combine the adaptability and competence of manual labour with the efficiency of automated systems. To maintain consistent human safety and effective collaborative productivity, communication between a human operator and the robot in these collaborative contexts must be precise and seamless. In more specific words, the framework can be used to operate an industrial robot securely and remotely in real-time while still protecting the safety of the technician. The objective of this article is to offer a clear overview of Industry 5.0's major ideas and prospective applications. It focuses on the supporting technologies of Industry 5.0 such as the Internet of Things (IoT), 6G systems, Blockchain Technology (BT), Digital Twin (DT), Artificial Intelligence (AI), Cyber-physical systems, and Extended Reality (XR) technologies, for seamless connectivity and data exchange. Furthermore, it also elaborates on the application of Cobots in various industrial fields.
Novel Microbial Signatures in the Faecal Microbiome Associated with Severe Alcoholic Hepatitis: Bacteroides Finegoldii and Veillonella Dispar

Alcoholic hepatitis is associated with dysbiosis, resulting in compositional changes in the gut microbiome, endotoxin transfer to the portal vein, and activation of inflammatory signalling pathways in the liver. However, the microbiome signature of severe alcoholic hepatitis (AH) patients of Indian origin is unknown. To investigate the microbiome diversity of Indian AH patients in comparison to non-alcoholic healthy controls (HC). 16S rRNA amplicon-based metagenomics analysis of faecal samples at the time of AH diagnosis (n=12) was compared with HC (n=6), and correlation with survival status, co-occurrence networking, Linear Discriminant Analysis Effect Size (LEfSe), and the relationship between diet – microbiome were performed. 16S rDNA data showed a significant abundance of the Enterobacteriaceae family belonging to the phylum Proteobacteria and a depletion of the phylum Firmicutes in AH. A species-level classification identified Klebsiella pneumonia, Klebsiella variicola, and Parabacteroides distasonis as having the highest predictive performance value with reference to mortality at 60 days. Apart from this, a unique finding was the abundance of Bacteroides finegoldii and Veillonella dispar in AH patients. Moreover, the co-occurrence networking analysis revealed a higher level of connectivity and complexity within the microbial community of AH patients compared to HC. Thus, indicating the significant positive association (Spearman r > 0.7, p < 0.01) among members of the Firmicutes, Bacteroidetes, and Proteobacteria phyla in AH. Wilcoxon-Rank Sum test (p < 0.01) identified Firmicutes phyla occurrence associated with high carbohydrate intake and Actinobacteria phyla with low protein intake. The findings provide the baseline occurrence profile of the gut microbiome signature of liver damage and the diet-microbiome relationship in patients with severe AH. The study demonstrated an abundance of Proteobacteria phyla, indicating their role in inflammatory conditions, and further identified Bacteroides finegoldii and Veillonella dispar in severe AH patients. Additionally, Klebsiella pneumonia, Klebsiella variicola, and Parabacteroides distasonis were identified as mortality-predictive risk biomarkers.
Data Warehousing and Data Mining: A Course in MBA and MSIS Program from Uses Perspective

Over the past years data warehousing and data mining tools have evolved from research into a unique and popular business application class for decision support and business intelligence. The paper presents and discusses the main components and contents of a course in data warehousing and data mining offered in the graduate business curriculum of an American university in the Midwest. Further, it also discusses how the course was delivered. The course has been designed from lessons learned in research and practice in the field. Key to the development and success of the course is an on-going collaboration between a large company in the retailing branch and the university. Collaboration with the business world has proven invaluable in building bridges between the academic institution and the real world. However, teaching a course in a dynamic field like this will always remain a challenge.
Performance Optimization of a Residential Microgrid Balancing Economic and Energy Issues

Microgrids are currently seen as the future of power generation and distribution systems. This paper illustrates the optimization of the operation stage of the main components of a microgrid supplying the final demands for electricity, heating and cooling of a residential district. The optimization was performed with reference to four seasonal standard days and optimizing the operating costs or the primary energy use. The electricity production from a photovoltaic system and a combined heat and power (CHP) satisfies the local electricity demand. The heating demand is fulfilled with a gas-fired boiler, a CHP, a solar thermal collector and a reversible heat pump that is employed also for the cooling demand together with an absorbtion chiller. Moreover, a storage system for each demand is also included. The optimization model is formulated through a mixed-integer linear programming approach and implemented in MATLAB. The results show a reduction of costs ranging between about two and four times and a reduction of primary energy use between about two and five times with respect to the traditional scenario (electricity and gas from the grid).
Mapping Social Connections: A Graph Mining and Ensemble learning Approach to Link Prediction

This research presents an innovative approach for predicting linkages in social network graphs using graph mining techniques. Link prediction is a key issue in network research and has a wide range of real-world uses, such as customised suggestions and targeted marketing. The most likely new interactions between social media users in the near future can be predicted using a social network’s graph. Our suggested approach makes use of the power of graph mining techniques to search for information on the system architecture and node attributes. This paper provides a variety of feature engineering methodologies that are used to convert this data into useful input. These traits are then fed into the machine learning model that is used to forecast links. We test the effectiveness of our method using real social network datasets. This study can further optimize our understanding of social network dynamics and aid in decision-making in a variety of contexts.
Overview of Memristive Cryptography

Memristors are emerging nano-devices with potential for excellent performance and rich electrical dynamic behavior. After their numerous successful applications in neu-romorphic and in-memory computing, the scientific community has turned to their potential for cryptographic implementations. This overview aims at summarizing the current state of affairs in this domain and outlining possible directions for future research. As in other fields where researchers from different disciplines come together, tensions and misunderstandings with respect to objectives and terminology are unavoidable, including the precise meaning of the very term “memristive cryptography”. We aim at establishing a better understanding of the objectives followed by various strands of research. An important issue is to synchronize recently reported results with the established requirements and performance indicators from the classical cryptography domain. As a specific example, we consider random number generation for security applications, which is one main line of memristive cryptography research. We outline today's requirements on RNGs that are enforced by RNG standards and therefore are a prerequisite for the practical relevance of any such developments in the medium-to-long term.
Dual Band Dual Circularly Polarized Patch Antenna for Sub-6 and Wi-Fi Applications

This paper presents dual band dual circularly polarized (CP) patch antenna for Sub-6GHz and Wi-Fi applications. The antenna is printed on a duroid substrate (εr= 2.2, thickness of 0.8 mm). It consists of modified feedline, regular octagon patch and modified ground system. By utilizing truncated ground, two bands of S11, 2.16-2.92GHz and 3.42-4.1 GHz is achieved along with two bands of circular polarization 2.4-2.58GHz and 3.7-4.0GHz is achieved. LHCP is achieved in the lower band and RHCP is achieved in Upperband. CP mechanism is explained in this article by using surface current distribution. The proposed antenna is designed using dimension 40×39×0.8mm3. Peak Gain of the proposed antenna is 2.4dB and radiation efficiency of 95% is observed. The suggested antenna is simple in design and promising option for various wireless application.
Performance Testing of The CNC Laser Engraver Machine on Plywood Media

This work aims to test and analyze the performance of the CNC Laser Engraver Machine on plywood media by using the grbl settings. The engraving process was conducted by using three filling methods in the grbl setting, i.e., reversed diagonal filling, horizontal filling and no filling. In the reversed diagonal filling method is tested a gears image input, in the horizontal filling method is tested a rumah gadang image input and in the no-filling method is tested a piston image input. The machine performance was assessed by comparing the CAD-based images input with the engraved images output that are carved on plywood media by a laser speed setting of 1000 mm/min, a laser power scale of 60% and a distance of laser from the media of 5 cm. From this assessment it can be concluded that the CNC Laser Engraver Machine is capable to create the shape and size of the images output that is the same as the shape and size of the images input. Here, the images size is obtained by a vernier caliper that has an accuracy of 0.05 mm.
Phenotypic and Genotypic Analysis of Bacterial Pathogens Recovered from Patients Diagnosed with Fever of Unknown Origin in Egypt

Fever of unknown origin (FUO) is a medical term describing fever that lasts for at least three weeks without a diagnosis being reached after extensive diagnostic evaluation. Therefore, this study aimed to identify the common pathogens causing FUO in patients admitted to Abbasia Fever Hospital in Egypt from January 2020 to December 2022, their antimicrobial susceptibility profiles, and associated resistance genes. The study also aimed to investigate the burden of multidrug-resistant (MDR) pathogens and the priority pathogens nominated by the World Health Organization (WHO) for posing the greatest threat to human health due to antibiotic resistance. During the study period, about 726 patients were diagnosed with FUO. After extensive investigations, the cause of the FUO was found to be infectious diseases in 479/726 patients (66.0%). Of them, 257 patients had positive bacterial cultures, including 202 Gram-negative isolates that comprised Klebsiella pneumoniae (85/202; 42.1%), Escherichia coli (71/202; 35.1%), Acinetobacter baumannii (26/202; 12.9%), and Pseudomonas aeruginosa (14/202; 6.9%) and 55 Gram-positive isolates, including Staphylococcus aureus (23/55; 41.8%), Streptococcus pneumoniae (7/55; 12.7%), and Enterococcus spp. (25/55; 45.5%). The MDR phenotype was shown by 68.3% and 65.5% of the Gram-negative and Gram-positive isolates, respectively. Carbapenem resistance (CR) was shown by 43.1% of the Gram-negative isolates. Of the 23 S. aureus isolates obtained from research participants, 15 (65.2%) were methicillin-resistant S. aureus (MRSA). A high-level aminoglycoside resistance (HLAR) phenotype was found in 52.0% of the Enterococcus sp. isolates. The PCR screening of resistance genes in the MDR isolates showed that blaOXA−48 was the most prevalent (84%) among the carbapenemase-coding genes, followed by blaVIM (9%) and then blaIMP (12%). The ESBL-coding genes blaTEM, blaCTX-M, aac(6′)-Ib, and blaSHV, were prevalent in 100%, 93.2%, 85,% and 53.4% of the MDR isolates, respectively. This study updates the range of bacteria that cause FUO and emphasizes the burden of multidrug resistance and priority infections in the region. The obtained data is of relevant medical importance for the implementation of evidence-based antimicrobial stewardship programs and tailoring existing empirical treatment guidelines.
Precipitation explains GRACE water storage variability over large endorheic basins in the 21st century

Introduction: Seasonal—interannual variations in surface water storage revealed by the Gravity Recovery and Climate Experiment (GRACE) satellites have received less attention than storage trends in the literature. We focus on six large endorheic basins and develop variability attribution diagnostics against independent precipitation and evapotranspiration (hereafter P and E) datasets.Methods: We generate a flux-inferred storage (FIS), representing the integral of the component flux anomalies into and out of a region, enabling a comparison between the P and E contributions to GRACE water storage anomalies on seasonal to interannual timescales. Additionally, a monthly budget closure approach is applied, giving self-consistent coupled water and energy exchanges from 2002 to 2020.Results: On seasonal timescales, P and E data show insufficient cancellation, implying over-large seasonal variations in surface storage. In most basins, P drives the seasonal storage cycle with E dampening storage amplitudes, although in the Caspian Basin, seasonal storage is driven by E, with P remaining seasonally constant when integrated over the whole drainage basin. Budget closure mostly adjusts E, which has larger uncertainties, in fitting the GRACE data. On year-to-year and multi-year timescales, there is a strong correlation between P-driven storage and the observed GRACE variability, which ranges between 0.55 and 0.88 across all basins, and this is maintained after budget closure. However, storage changes driven by P alone from GPCP are too large compared to GRACE, with E data from FLUXCOM generally having only very weakly compensating interannual variations. After budget closure, interannual E variability is substantially increased. Closed energy budgets often show interannual amplitudes, partly driven by radiation and partly by water budget variation through shared latent heat losses, although these have not been independently verified.Discussion: Although water flux trends cannot be detected with significance due to the large interannual variability, the strong agreement between multi-annual GRACE storage and precipitation variations, especially over the Caspian basin, lends no support to the suggestion that E changes driven by climate change are responsible for water storage trends seen by GRACE.
LSTM Approach for Efficient Stock Market Prediction

Stock market investing has always been difficult for shareholders and prevents the use of standard models to make more accurate predictions of future values. Although many researchers and academicians have proposed methods to make stock price prediction more efficient. But after going through those proposals, we found a number of loopholes that can be tackled using a different approach. In this research work, machine learning and a study of finance have been combined to construct a model employing long-short term memory (LSTM) that forecasts the value of the SENSEX in the future. Finally, we have evaluated the performance of our proposed method. So this research work can be used by other researchers in the same domain. Our research will encourage practitioners to better identify the exciting sector for future views while also assisting beginners in comprehending the ML paradigm.
Securing development in an unstable world

"The Annual World Bank Conference on Development Economics" (ABCDE) brings together the world's finest development thinkers to present their perspectives and ideas. In recent years, a parallel, second conference has been held in Europe with the same goal of expanding the flow of ideas between thinkers, practitioners, and policymakers in the field of international development. This title presents selected papers from the seventh annual ABCDE - Europe meetings, held in May 2005 in Amsterdam, the Netherlands.