Fermatean hesitant fuzzy rough aggregation operators and their applications in multiple criteria group decision-making.

The precise selection of suppliers to fulfill production requirements is a fundamental component of all manufacturing and process industries. Due to the increasing consumption levels, green supplier selection (GSS) has been one of the most important issues for environmental preservation and sustainable growth. The present work aims to develop a technique based on Fermatean hesitant fuzzy rough set (FHFRS), a robust fusion of Fermatean fuzzy set, hesitant fuzzy set, and rough set for GSS in the process industry. On the basis of the operational rules of FHFRS, a list of innovative Fermatean hesitant fuzzy rough weighted averaging operators has been established. Further, several intriguing features of the proposed operators are highlighted. To cope with the ambiguity and incompleteness of real-world decision-making (DM) challenges, a DM algorithm has been developed. To illustrate the applicability of the methodology, a numerical example for the chemical processing industry is presented to determine the optimum supplier. The empirical findings suggest that the model has a significant application of scalability for GSS in the process industry. Finally, the improved FHFR-VIKOR and TOPSIS approaches are employed to validate the proposed technique. The results demonstrate that the suggested DM approach is practicable, accessible, and beneficial for addressing uncertainty in DM problems.

Novel Information Measures for Fermatean Fuzzy Sets and Their Applications to Pattern Recognition and Medical Diagnosis.

Fermatean fuzzy sets (FFSs) have piqued the interest of researchers in a wide range of domains. The striking framework of the FFS is keen to provide the larger preference domain for the modeling of ambiguous information deploying the degrees of membership and nonmembership. Furthermore, FFSs prevail over the theories of intuitionistic fuzzy sets and Pythagorean fuzzy sets owing to their broader space, adjustable parameter, flexible structure, and influential design. The information measures, being a significant part of the literature, are crucial and beneficial tools that are widely applied in decision-making, data mining, medical diagnosis, and pattern recognition. This paper aims to expand the literature on FFSs by proposing many innovative Fermatean fuzzy sets-based information measures, namely, distance measure, similarity measure, entropy measure, and inclusion measure. We investigate the relationship between distance, similarity, entropy, and inclusion measures for FFSs. Another achievement of this research is to establish a systematic transformation of information measures (distance measure, similarity measure, entropy measure, and inclusion measure) for the FFSs. To accomplish this aim, new formulae for information measures of FFSs have been presented. To demonstrate the validity of the measures, we employ them in pattern recognition, building materials, and medical diagnosis. Additionally, a comparison between traditional and novel similarity measures is described in terms of counter-intuitive cases. The findings demonstrate that the innovative information measures do not include any absurd cases.

Molecular Characterization and Epidemiology of Antibiotic Resistance Genes of ß-Lactamase Producing Bacterial Pathogens Causing Septicemia from Tertiary Care Hospitals.

Septicemia is a systematic inflammatory response and can be a consequence of abdominal, urinary tract and lung infections. Keeping in view the importance of Gram-negative bacteria as one of the leading causes of septicemia, the current study was designed with the aim to determine the antibiotic susceptibility pattern, the molecular basis for antibiotic resistance and the mutations in selected genes of bacterial isolates. In this study, clinical samples (n = 3389) were collected from potentially infected male (n = 1898) and female (n = 1491) patients. A total of 443 (13.07%) patients were found to be positive for bacterial growth, of whom 181 (40.8%) were Gram-positive and 262 (59.1%) were Gram-negative. The infected patients included 238 males, who made up 12.5% of the total number tested, and 205 females, who made up 13.7%. The identification of bacterial isolates revealed that 184 patients (41.5%) were infected with Escherichia coli and 78 (17.6%) with Pseudomonas aeruginosa. The clinical isolates were identified using Gram staining biochemical tests and were confirmed using polymerase chain reaction (PCR), with specific primers for E. coli (USP) and P. aeruginosa (oprL). Most of the isolates were resistant to aztreonam (ATM), cefotaxime (CTX), ampicillin (AMP) and trimethoprim/sulfamethoxazole (SXT), and were sensitive to tigecycline (TGC), meropenem (MEM) and imipenem (IPM), as revealed by high minimum inhibitory concentration (MIC) values. Among the antibiotic-resistant bacteria, 126 (28.4%) samples were positive for ESBL, 105 (23.7%) for AmpC ß-lactamases and 45 (10.1%) for MBL. The sequencing and mutational analysis of antibiotic resistance genes revealed mutations in TEM, SHV and AAC genes. We conclude that antibiotic resistance is increasing; this requires the attention of health authorities and clinicians for proper management of the disease burden.

High prevalence of Panton-Valentine Leucocidin (PVL) toxin carrying MRSA and multidrug resistant gram negative bacteria in late onset neonatal sepsis indicate nosocomial spread in a Pakistani tertiary care hospital.

BACKGROUND: Neonatal sepsis has high incidence with significant mortality and morbidity rates in Pakistan. We investigated common etiological patterns of neonatal sepsis at a tertiary care setup. METHODS: 90 pus and blood, gram negative and gram positive bacterial isolates were analyzed for virulence and antibiotic resistance gene profiling using PCR and disc diffusion methods. RESULTS: Staphylococcus aureus showed strong association with neonatal sepsis (43 %) followed by Citrobacter freundii (21 %), Pseudomonas aeruginosa (13 %), Escherichia coli (15 %) and Salmonella enterica (8 %). Molecular typing of E. coli isolates depicted high prevalence of the virulent F and B2 phylogroups, with 4 hypervirulent phylogroup G isolates. 76.9 % S. aureus isolates showed presence of Luk-PV, encoding for Panton-valentine leucocidin (PVL) toxin with majority also carrying MecA gene and classified as methicillin resistant S. aureus (MRSA). ecpA, papC, fimH and traT virulence genes were detected in E. coli and Salmonella isolates. 47 % Citrobacter freundii isolates carried the shiga like toxin SltII B. Antimicrobial resistance profiling depicted common resistance to cephalosporins, beta lactams and fluoroquinolones. CONCLUSION: Presence of PVL carrying MRSA and multidrug resistant gram negative bacteria, all isolated from late onset sepsis neonates indicate a predominant nosocomial transmission pattern which may complicate management of the disease in NICU setups.

Evaluation of sodium citrate anticoagulant for the Resolution of edta-dependent pseudo Thrombocytopenia.

BACKGROUND: EDTA-dependent pseudo thrombocytopenia (EDTA-PTCP) refers to a falsely low platelet count occurring in the presence of ethylene diamine tetra-acetic acid (EDTA) anticoagulant during blood sample collection, which results in the formation of platelet clumps in vitro. This phenomenon has significant clinical implications, including unnecessary administration of platelets. Our study aims to evaluate the efficacy of sodium citrate anticoagulant for the resolution of EDTAPTCP. METHODS: This retrospective study was conducted in the haematology laboratory of Shifa International Hospital (SIH), Pakistan. Patients with pseudo thrombocytopenia (i.e. platelet count less than 150,000/ul with platelet clumps seen on peripheral smear) were included in this study if they had blood samples drawn in both EDTA and sodium citrate tubes less than 48 hours apart. Data was analyzed using IBM® SPSS Software Version 22. RESULTS: A total of 151 study participants were included in this study. The mean age was 48.95±20.69 years and the majority were female (52.3%). Wilcoxon signed-rank test showed that there was a statistically significant difference in platelet count measured in both tubes (Z = -3.223, p=0.001). Overall, blood samples processed in sodium citrate tubes showed lower platelet count than EDTA samples. Sodium citrate anticoagulant was able to correct EDTA-PTCP in 47 (31.1%) of the cases. CONCLUSIONS: Sodium citrate anticoagulant was only able to resolve one-third of our EDTA-PTCP cases. Our findings do not support the use of sodium citrate as a suitable alternative for correction of EDTA-PTCP.

Soft ordered double quantitative approximations based three-way decisions and their applications.

The classical theory of rough set was established by Pawlak, which mainly focusses on the approximation of sets characterized by a single equivalence relation over the universe. However, most of the current single granulation structure models cannot meet the user demand or the target of solving problems. Multigranulation rough sets approach can better deal with the problems, where data might be spread over various locations. In this article, we present the idea of soft preference and soft dominance relation for the development of soft dominance rough set in an incomplete information system. Subsequently, several important structural properties and results of the proposed model are carefully analyzed. After employing soft dominance based rough set approach to it for any times, we can only get six different sets at most in an incomplete information system. That is to say, every rough set in a universe can be approximated by only six sets, where the lower and upper approximations of each set in the six sets are still lying among these six sets. The relationships among these six sets are established. Based on soft dominance relation, we introduce logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximations in an incomplete information. Meanwhile, to measure the uncertainty of soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximation and some of their interesting properties are examined. Thereafter, a novel multi attribute with multi decision making problem approach based on logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough sets approach are developed to solve the selection of medicine to treat the coronavirus disease (COVID-19). The basic principle and the detailed steps of the decision making model (algorithms) are presented in detail. To demonstrate the applicability and potentiality of the proposed model, we present a practical example of a medical diagnosis is given to validate the practicality of the technique.

A wind power plant site selection algorithm based on q-rung orthopair hesitant fuzzy rough Einstein aggregation information.

Wind power is often recognized as one of the best clean energy solutions due to its widespread availability, low environmental impact, and great cost-effectiveness. The successful design of optimal wind power sites to create power is one of the most vital concerns in the exploitation of wind farms. Wind energy site selection is determined by the rules and standards of environmentally sustainable development, leading to a low, renewable energy source that is cost effective and contributes to global advancement. The major contribution of this research is a comprehensive analysis of information for the multi-attribute decision-making (MADM) approach and evaluation of ideal site selection for wind power plants employing q-rung orthopair hesitant fuzzy rough Einstein aggregation operators. A MADM technique is then developed using q-rung orthopair hesitant fuzzy rough aggregation operators. For further validation of the potential of the suggested method, a real case study on wind power plant site has been given. A comparison analysis based on the unique extended TOPSIS approach is presented to illustrate the offered method's capability. The results show that this method has a larger space for presenting information, is more flexible in its use, and produces more consistent evaluation results. This research is a comprehensive collection of information that should be considered when choosing the optimum site for wind projects.

Decision support model for the patient admission scheduling problem based on picture fuzzy aggregation information and TOPSIS methodology.

Health care systems around the world do not have sufficient medical services to immediately offer elective (e.g., scheduled or non-emergency) services to all patients. The goal of patient admission scheduling (PAS) as a complicated decision making issue is to allocate a group of patients to a limited number of resources such as rooms, time slots, and beds based on a set of preset restrictions such as illness severity, waiting time, and disease categories. This is a crucial issue with multi-criteria group decision making (MCGDM). In order to address this issue, we first conduct an assessment of the admission process and gather four (4) aspects that influence patient admission and design a set of criteria. Even while many of these indicators may be accurately captured by the picture fuzzy set, we use an advanced MCGDM approach that incorporates generalized aggregation to analyze patients' hospitalization. Finally, numerical real-world applications of PAS are offered to illustrate the validity of the suggested technique. The advantages of the proposed approaches are also examined by comparing them to various existing decision methods. The proposed technique has been proved to assist hospitals in managing patient admissions in a flexible manner.

q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming.

The main purpose of this manuscript is to present a novel idea on the q-rung orthopair fuzzy rough set (q-ROFRS) by the hybridized notion of q-ROFRSs and rough sets (RSs) and discuss its basic operations. Furthermore, by utilizing the developed concept, a list of q-ROFR Einstein weighted averaging and geometric aggregation operators are presented which are based on algebraic and Einstein norms. Similarly, some interesting characteristics of these operators are initiated. Moreover, the concept of the entropy and distance measures is presented to utilize the decision makers' unknown weights as well as attributes' weight information. The EDAS (evaluation based on distance from average solution) methodology plays a crucial role in decision-making challenges, especially when the problems of multicriteria group decision-making (MCGDM) include more competing criteria. The core of this study is to develop a decision-making algorithm based on the entropy measure, aggregation information, and EDAS methodology to handle the uncertainty in real-word decision-making problems (DMPs) under q-rung orthopair fuzzy rough information. To show the superiority and applicability of the developed technique, a numerical case study of a real-life DMP in agriculture farming is considered. Findings indicate that the suggested decision-making model is much more efficient and reliable to tackle uncertain information based on q-ROFR information.

Molecular epidemiology of antibiotic-resistant genes and potent inhibitors against TEM, CTX-M-14, CTX-M-15, and SHV-1 proteins of Escherichia coli in district Peshawar, Pakistan.

The Extended Spectrum Beta-Lactamases (ESBLs) producing bacteria is an issue of concern for clinicians resulting in minimize the treatment options. To overcome resistance mechanisms, novel inhibitors with good Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties must inhibit the ESBLs resistant genes. The current study aimed to identify the antibiotic resistance genes of ESBLs producing E. coli and a single inhibitor was designed to inhibit all the resistant proteins. The results showed that 42.9% ESBL producers had CTX-M (69.9%), TEM (63.4%), SHV (34.5%) and CTX-M-14 (17.5%) genes. The ESBLs producing isolates were resistant to cephalosporins, quinolones, and sulfonamide with Minimum Inhibitory Concentration (MICs) ranging from 64 to >256 µg/ml. To design multi inhibitory ligands, RECAP synthesis was used for the de-novo discovery of 1000 inhibitors database. Protein crystal structures were retrieved from Protein Data Base (PDB). Lipinski's rules of five were applied to the novel inhibitors database to improve the ADMET properties. The novel inhibitors database was selected for docking simulations. Placement of the ligand was used by the London dG algorithm implemented in Molecular Operating Environment (MOE), while GBVI/WSA dG algorithm was used for final refinement. Based on docking score, visual inspection of ligands interaction with key residues, binding affinity, and binding energy of ligands with proteins, ten compounds were selected for ESBLs proteins with best ADMET properties, binding energy, and binding affinity the reported ones. These hits compounds have unique scaffolds and are predicted to be a starting point for developing potent inhibitors against antibiotic-resistant proteins.

Phenotypic and molecular characterization of virulence factors of extra-intestinal pathogenic Escherichia coli isolated from patients of Peshawar, Pakistan.

Extra-Intestinal Escherichia coli (ExPEC) are important cause of Urinary Tract Infections (UTIs) and systemic infections. The purpose of this study was to investigate numerous ExPEC bacterial isolates for phenotypic virulence characteristics including hemolytic activity and resistance pattern and to observe their association with genetic traits via Polymerase Chain Reaction (PCR). A total of 367 ExPEC isolates were collected from patients admitted in Khyber Teaching Hospital (KTH) Peshawar, Pakistan. Standard techniques were used for identification of isolates, determination of hemolytic potential and antimicrobial susceptibility testing. PCR was used for screening of virulence genes using specific primers. A total of 367 ExPEC isolates were characterized, among which 62.7, 24.3, 7.1 and 6% were isolated from urine, pus, sputum and wound specimens, respectively. Majority of the isolates (82.8%) were hemolysin positive. Multi drug resistance pattern was shown by 41% of the isolates and harbored at least one virulence gene (71.7%), of which sat was the most prevalent (64.3%). The highest resistance was found to cefotaxime (99.2%), ampicillin (97.5%) and aztreonem (89.6%). 15 different virulence genes combinations were observed in the current study. A total of 16 virotypes (15 of positive virulence genes and one of no virulence gene) were observed in the current study. The current investigation showed a high prevalence of sat and hlyA genes among ExPEC isolate, suggesting a role of these genes in the pathogenesis of ExPEC.

A comprehensive study of upward fuzzy preference relation based fuzzy rough set models: Properties and applications in treatment of coronavirus disease.

In this paper, we first introduce a new type of rough sets called α-upward fuzzified preference rodownward fuzzy preferenceugh sets using upward fuzy preference relation. Thereafter on the basis of α-upward fuzzified preference rough sets, we propose approximate precision, rough degree, approximate quality and their mutual relationships. Furthermore, we presented the idea of new types of fuzzy upward ß-coverings, fuzzy upward ß-neighborhoods and fuzzy upward complement ß-neighborhoods and some relavent properties are discussed. Hereby, we formulate a new type of upward lower and upward upper approximations by applying an upward ß-neighborhoods. After employing the upward ß-neighborhoods based upward rough set approach to it any times, we can only get the six different sets at most. That is to say, every rough set in a universe can be approximated by only six sets, where the lower and upper approximations of each set in the six sets are still lying among these six sets. The relationships among these six sets are established. Subsequently, we presented the idea to combine the fuzzy implicator and t-norm to introduce multigranulation (ℐ,T)-fuzzy upward rough set applying fuzzy upward ß-covering and some relative properties are discussed. Finally we presented a new technique for the selection of medicine for treatment of coronavirus disease (COVID-19) using multigranulation (ℐ,T)-fuzzy upward rough sets.

Long term outcome of chronic myeloid leukemia patients treated with imatinib: Report from a developing country.

The outcome of chronic myeloid leukemia has been greatly improved by the use of Imatinib (IM), a selective BCR/ABL kinase inhibitor. The aim of present study was to report long term follow-up & outcome of IM-treated CML patients along with their clinicopathological features, risk group stratification, adverse events and to compare it with CML patients reported from western countries. The mean follow-up of 123 CML patients was 5.5 years in present study, who were treated with frontline IM 400mg daily in a tertiary care hospital in Pakistan. Risk stratification scores, response to treatment (ELN guidelines) and survival outcomes estimated by Kaplan-Meier analysis. Mean age: 35 years (9-67 years) and M: F: 1.5:1, mean follow up time: 5.5 years (1-15 years). Overall survival (OS): at 5.5, 8, 10 and 12 years were 93%, 88%, 81% and 73%, respectively. Progressions free survival (PFS) was 95%, 83%, 83% and 78% at 5.5, 8, 10 and 12 years, respectively. OS estimate by Sokal score was significant (P-value: 0.0019). Additional chromosomal aberrations: 1.6%. Eighteen (14.6%) patients progressed to AP/BC. Adverse events were moderate and tolerable. We present findings from a long term follow up of CML patients treated with IM in a developing country. CML mean age at onset was considerably lower than the western populations. Furthermore, 5.5 years OS are comparable to western CML population. IM in our patients as frontline choice proved to be very effective. IM was found to be well tolerated, safe with manageable moderate side effects.

Effect of protein and oil volume concentrations on emulsifying properties of acorn protein isolate.

This study aims to extract acorn protein isolate (API) from locally abundant waste acorn fruit and investigate its emulsification behavior by mixing different protein (0.1-2% w/v) and oil volume concentrations (5-45% v/v). Significant decrease in emulsifying activity index (EAI) and an increase in emulsifying stability index (ESI) were observed with an increase in API concentrations (P < 0.05). Droplet sizes of emulsions and viscosity were observed to decrease significantly (P < 0.05) with increase in API concentration while the increase was observed in interfacial protein concentration (Г). In contrast, increase in oil volume concentration results in increase of droplet sizes, packing fractions and viscosity, while decrease in Г values was observed. The results reveal that main fractions of API (66.2-14.4 kDa) were migrated to oil-water interface for emulsion stabilization. These results demonstrate the potential application of API in food formulation and development.

Environmentally benign extraction of cellulose from dunchi fiber for nanocellulose fabrication.

In the current study, cellulose was extracted from the plant dunchi fiber by using an ecofriendly method followed by preparation of nanocellulose. The procedure involved an alkali treatment and chlorine-free bleaching for removal of lignin and hemicelluloses from material. Fourier transform infrared (FTIR) spectroscopy provided the evidence about removal of hemicellulose and lignin. The morphological changes in the surface of lignocellulosic fibers were studied through scanning electron microscopy (SEM). X-ray Diffraction (XRD) analysis measured the degree of crystallinity of extracted cellulosic material. By using Segal method, the degree of crystallinity was found 66.7%. Crystal thickness was determined by Scherrer equation and its value was found to be 40.07 Å. The values were closed to the values observed for commercial microcrystalline cellulose (MCC). The TGA curve showed the thermal degradation pattern of the cellulosic material and it was closed to the thermal behavior of pure cellulose. Finally, nanocellulose was produced by acid hydrolysis from the obtained cellulosic material. Transmission electron microscopy (TEM) showed the existence of nanocellulose with an average aspect ratio of 10.45 ± 3.44. In the future, dunchi fiber has a potential to be used as a renewable source to produce cellulose and subsequently its nanocellulose for a wide range of applications in composite materials.

Cutaneous toxicities of new targeted cancer therapies: must know for diagnosis, management, and patient-proxy empowerment.

The world of oncology treatment is rapidly changing, and with the investigation into and utilization of molecular signaling pathways for cancer treatment, many new targeted small-molecule oral agents have been introduced as therapies, with more new drugs appearing every year. These agents, while generally considered less toxic overall than traditional chemotherapy, are not without adverse effects. The authors undertook an extensive literature search to determine the incidence, severity, and management strategies for small-molecule oral targeted agents approved by the FDA between 2013 and 2018. Dermatologic adverse effects are among the most frequently seen with many of these targeted therapies, and may include rashes, palmar-plantar dysesthesia, alopecia, secondary skin malignancies, and hair and nail changes. Rarely, more severe cutaneous toxicities are seen, such as Stevens-Johnson Syndrome and toxic epidermal necrolysis. In many cases, there is no specific management strategy suggested in the literature for these toxicities, but frequent monitoring of the skin, prophylactic management of palmar-plantar dysesthesia, use of corticosteroids and/or antihistamines, and intervention with dose interruption are suggested depending on circumstance and severity. Patient education and timely intervention is warranted in order to ensure that patient treatment is optimized.

Designing of potent inhibitors for metallo-beta-lactamases producing Escherichia coli in molecular specification hereto.

The rapid spread of Metallo-ß-Lactamases producing Gram-negative bacteria in Pakistan is alarming and novel inhibitors with multi inhibition potential are required. In the current study, an effort was made to identify the resistance genes of MBLs producing E. coli and single inhibitor was designed having the potential to block all resistant proteins. Results showed that out of 573 clinical isolates, 14.1% MBLs producers have NDM-1 (27.2%) and VIM (13.6%) gene. The isolates were resistant to MEM, AMP, AMC, FEP, CTX, LEV and ATM, while effective antibiotics were TGC, CO, FOS and AK with MICs ranging from 4 to >32µg/ml. RECAP synthesis was used for de-novo discovery of 1000 inhibitors and protein crystal structures were retrieved from PDB. Active sites were identified in each protein and to improve ADMET properties, Lipinski's rules of five was applied. Placement of the ligand was done by London dG algorithm implemented in MOE. For final refinement, GBVI/WSA dG algorithm was used. Based on docking score, visual inspection of ligands interaction with key residues, binding affinity and binding energy of ligands with proteins, 10 compounds were selected for MBLs proteins which presented best ADMET properties, binding energy and affinity than the reported ones.

Effects of Maillard reaction on physicochemical and functional properties of walnut protein isolate.

In this study, the Maillard reaction (MR) of glucose was applied to improve the physicochemical and functional properties of walnut protein isolate (WNPI). The MR products (MRPs) were prepared with glucose at 0 h (MRP0), 1 h (MRP1), 2 h (MRP2) and 3 h (MRP3) heating at 95 °C. The Infra-Red spectrum showed reduction of amide and S-H functionalities in MRPs with complete intermixing of glucose in MRP3. Scanning electron microscopy indicated changes in the morphology of MRP3 which also exhibited promising antioxidant effect. Significant decrease (P < 0.05) in hydrophobicity values (Ho) and increase (P < 0.05) in emulsifying activity/emulsifying stability indexes values were observed for MRPs. Uniform droplet distribution was observed in microscopy of emulsions while an increase in the interfacial protein concentration ( Г) was obtained for MRPs. These results suggest that MR is useful in improving the utilization of this protein in food product development.

Endocrine disrupting chemicals and impact on male reproductive health.

Endocrine disrupting chemicals (EDCs) have been known to adversely affect the endocrine system leading to compromised functions of hormones. The presence of these compounds in everyday products such as canned food, water bottles, plastics, cosmetics, fertilizers, kid's toys and many others goods is a greater concern for general population. The persistent and long-term use of EDCs has deleterious effects on human reproductive health by interfering with the synthesis and mechanism of action of sex hormones. Any change during the synthesis or action of the sex hormones may result in abnormal reproductive functions which includes developmental anomalies in the reproductive tract and decline in semen quality. The present paper provides an overview of the EDCs and their possible impact on male reproductive health with major focus on semen quality which leads to male infertility.