Impact of cement waste on soil fertility and crop productivity: a serious concern for food security.

The rapid expansion of urbanization and construction activities has led to a significant increase in cement production worldwide, resulting in a surge in cement waste generation. This study aims to provide a comprehensive analysis of the repercussions of cement waste on soil fertility and crop productivity, emphasizing its critical implications for global food security. Through a multidisciplinary approach, encompassing field surveys, laboratory experiments, and statistical modeling, we assess the physicochemical alterations induced by cement waste in agricultural soils. Our findings reveal substantial declines in crucial soil parameters, including pH levels, organic matter content, and nutrient availability, which directly translate into diminished crop yields. Furthermore, the study identifies key mechanisms underlying these detrimental effects, including altered microbial communities and disrupted nutrient cycling processes. In addition, the findings underscore the severity of the issue, revealing substantial declines in soil fertility and crop yields in areas affected by cement waste contamination. Additionally, we discuss potential mitigation strategies and policy interventions aimed at mitigating the adverse effects of cement waste on agricultural systems. By quantifying the extent of soil degradation and crop yield reduction attributed to cement waste, this research underscores the urgency for sustainable waste management practices and highlights the need for policy interventions to safeguard agricultural productivity and ensure global food security in the face of escalating urbanization and construction activities.

Underground communication: Long non-coding RNA signaling in the plant rhizosphere.

Long non-coding RNAs (lncRNAs) have emerged as integral gene-expression regulators underlying plant growth, development, and adaptation. To adapt to the heterogeneous and dynamic rhizosphere, plants use interconnected regulatory mechanisms to optimally fine-tune gene-expression-governing interactions with soil biota, as well as nutrient acquisition and heavy metal tolerance. Recently, high-throughput sequencing has enabled the identification of plant lncRNAs responsive to rhizosphere biotic and abiotic cues. Here, we examine lncRNA biogenesis, classification, and mode of action, highlighting the functions of lncRNAs in mediating plant adaptation to diverse rhizosphere factors. We then discuss studies that reveal the significance and target genes of lncRNAs during developmental plasticity and stress responses at the rhizobium interface. A comprehensive understanding of specific lncRNAs, their regulatory targets, and the intricacies of their functional interaction networks will provide crucial insights into how these transcriptomic switches fine-tune responses to shifting rhizosphere signals. Looking ahead, we foresee that single-cell dissection of cell-type-specific lncRNA regulatory dynamics will enhance our understanding of the precise developmental modulation mechanisms that enable plant rhizosphere adaptation. Overcoming future challenges through multi-omics and genetic approaches will more fully reveal the integral roles of lncRNAs in governing plant adaptation to the belowground environment.

In Silico Identification and Characterization of Rare Cold Inducible 2 (RCI2) Gene Family in Cotton.

RCI2/PMP3s are involved in biotic and abiotic stresses and have an influence on the regulation of many genes. RCI2/PMP3 genes, which particularly encode small membrane proteins of the PMP3 family, are involved in abiotic stress responses in plants. In this work, in silico studies were used to investigate RCI2's potential function in stress tolerance and organogenesis. We conducted an extensive study of the RCI2 gene family and revealed 36 RCI2 genes from cotton species that were distributed over 36 chromosomes of the cotton genome. Functional and phylogenetic examination of the RCI2/PMP3 gene family has been studied in Arabidopsis, but in cotton, the RCI2/PMP3 genes have not yet been studied. Phylogenetic and sequencing studies revealed that cotton RCI2s are conserved, with most of them categorized into six distinct clades. A chromosome distribution and localization study indicated that cotton RCI2 genes were distributed unevenly on 36 chromosomes with segmental duplications, suggesting that the cotton RCI2 family is evolutionarily conserved. Many cis-elements related to stress responsiveness, development, and hormone responsiveness were detected in the promoter regions of the cotton RCI2. Moreover, the 36 cotton RCI2s revealed tissue-specific expression patterns in the development of cotton performed by transcriptome analysis. Gene structure analysis indicated that nearly all RCI2 genes have two exons and one intron. All of the cotton RCI2 genes were highly sensitive to drought, abscisic acid, salt, and cold treatments, demonstrating that they may be employed as genetic objects to produce stress-resistant plants.

Hypoglycaemia in a Patient Taking Tetracyclines.

Hypoglycaemia with tetracycline use is a very rare and unknown side effect of the antibiotic. The case highlights the importance of recognizing and managing this potential adverse effect. We present a case of an adolescent male with acne vulgaris who developed hypoglycaemic episodes after initiating tetracycline treatment and was referred by his General Practitioner to the Endocrinology clinic. The hypoglycaemia symptoms settled once tetracyclines were stopped. Acne vulgaris is a prevalent skin condition among adolescents, and antibiotics such as doxycycline and tetracycline are commonly used to treat severe cases of acne. While generally well-tolerated, rare side effects on glucose metabolism have been reported. Antibiotics are not well known to cause hypoglycaemic spells on their own. It is mostly when these antibiotics are started in patients taking other regular medications that the interaction between these medications causes hypoglycaemia.

Functional characterization of transcriptional activator gene SIARRI in tomato reveals its role in fruit growth and ripening.

Auxins regulate several characteristics of plant development and growth. Here, we characterized a new transcriptional activator SIARRI which binds specific DNA sequences and was revealed in Arabidopsis (ARR1). SIARRI acts as a two-component response regulator and its Arabidopsis homologous gene is AT3G16857. It belongs to the subfamily of type-B response regulators in the cytokinin signaling pathway. The study aimed to characterize the transgenic Micro-Tom plants by the overexpression of Solanum lycopersicum two-component response regulator ARR1. Overexpression of SIARRI results in a pleiotropic phenotype during fruit development and ripening. This study indicates that SIARRI is a primary regulator of leaf morphology and fruit development. Moreover, overexpressed plants showed variations in growth related to auxin as well as shorter hypocotyl elongation, enlarged leaf vascularization, and decreased apical dominance. The qRT-PCR investigation revealed that expression was downregulated at the breaker stage and high at Br+6 at various stages of fruit growth and ripening. In contrast to the fruit color, lycopene and ß-carotene concentrations in red-yellow overexpression line fruits were reduced significantly, and also slightly reduced in some red fruits. The quantity of ß-carotene in the transgenic fruits was lower than that of lycopene. This study showed that this gene might be a new transcriptional activator in fruit development and ripening. Furthermore, this study will provide new insights into tomato fruit ripening.

A Novel Markov Model-Based Traffic Density Estimation Technique for Intelligent Transportation System.

An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things-intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic.

Evaluation Of Normal Diameter Of Infra-Renal Aorta In A Pakistani Population Using Contrast-Enhanced Computed Tomography.

BACKGROUND: It is a common observation that the aortic size of Pakistani population is relatively less as compared to western population. Till now there is no study which has measured the dimensions of abdominal aorta in local population.The standard diameter of an artery across the body is critical for clinicians to recognize when an artery has become aneurysmal. This study aims to present the results of a local population's normal diameter of an infrarenal aorta and how it varies by age, gender, weight, height, body mass index (BMI) and body surface area (BSA). METHODS: This cross-sectional observational study was conducted in Vascular Surgery Department, at Combined Military Hospital (CMH), Peshawar, from July 2020 to November 2021.Participants in the study included all patients who underwent a contrast-enhanced computed tomography (CT) scan of the abdomen for any reason other than cardiovascular disease.The infrarenal abdominal aorta's mean internal diameter (anteroposterior and transverse diameter) was assessed. SPSS v 23 was used to analyze the data and present it as frequency and percentages. The Pearson correlation coefficient assessed the correlation between aortic diameters, weight, height, BMI, and BSA. RESULTS: Recruitment of a total of 250 patients was done in this study. Males were 194 (77.6%), while the rest were female patients. The patients' mean age was 39.6±12.8 years. The mean anteroposterior (AP) diameter of the infrarenal aorta was 16.13±2.32 mm. The mean transverse diameter (TD) was 15.96±2.34 mm. The infrarenal diameter of the aorta was smaller in women when compared to men, and the calibre of the aorta increased with the increasing age of the patients. There was a statistically significant positive relationship between their age and the average diameter of the infrarenal aorta (p<0.001) among both men and women. CONCLUSIONS: Clinicians and vascular surgeons will benefit from the findings in diagnosing and treating abdominal aortic aneurysms. Hence, thoughtful consideration should be made before formulating intervention protocols.

Impacts of adiposity parameters on peak expiratory flow rate in healthy young adults of Bahria University Medical and Dental College Karachi: Cross-sectional study.

OBJECTIVE: To explore the association of various adiposity parameters in young adults. METHODS: The cross-sectional study was conducted at Bahria University Medical and Dental College, Karachi, from January to February 2021, and comprised healthy medical students aged 19-21 years. Height, weight, body mass index, waist circumference, waist-hip ratio and percentage body fat were recorded. Peak expiratory flow rate was determined using Wright's meter, and its association with adiposity markers was determined using regression analysis. Data was analysed using SPSS 22. RESULTS: Of the 162 subjects, 96(59.3%) were females and 66(40.7%) were males. The overall mean age was 20.18±1.01 years. Peak expiratory flow rate was significant positively associated with height, body mass index, waist circumference, and percentage body fat (p<0.05). It had weak negative association with waist-hip ratio(p>0.05). CONCLUSIONS: Peak expiratory flow rate increased with height, body mass index, waist circumference, and percentage body fat in healthy subjects.

Recent advances in bioremediation of heavy metals and persistent organic pollutants: A review.

Heavy metals and persistent organic pollutants are causing detrimental effects on the environment. The seepage of heavy metals through untreated industrial waste destroys the crops and lands. Moreover, incineration and combustion of several products are responsible for primary and secondary emissions of pollutants. This review has gathered the remediation strategies, current bioremediation technologies, and their primary use in both in situ and ex situ methods, followed by a detailed explanation for bioremediation over other techniques. However, an amalgam of bioremediation techniques and nanotechnology could be a breakthrough in cleaning the environment by degrading heavy metals and persistant organic pollutants.

Development of Ductile and Durable High Strength Concrete (HSC) through Interactive Incorporation of Coir Waste and Silica Fume.

The issue of brittleness and low post-peak load energy associated with the plain HSC led to the development of fiber-reinforced concrete (FRC) by using discrete fiber filaments in the plain matrix. Due to the high environmental impact of industrial fibers and plasticizers, FRC development is ecologically challenged. Sustainability issues demand the application of eco-friendly development of FRC. This study is aimed at the evaluation of coir as a fiber-reinforcement material in HSC, with the incorporation of silica fume as a partial replacement of cement. For this purpose, a total of 12 concrete mixes were produced by using three different doses of coir (0%, 1%, 1.5%, and 2% by wt. of binder) with silica fume (0%, 5%, and 10% as volumetric replacements of cement). The examined parameters include compressive strength, shear strength, splitting tensile strength, ultrasonic pulse velocity, water absorption, and chloride ion permeability. The scanning electron microscopy (SEM) technique was adopted to observe the microstructure of the CF-reinforced concrete. The results revealed that due to the CF addition, the compressive strength of HSC reduces notably; however, the splitting tensile strength and shear strength experienced notable improvements. At the combined incorporation of 1.5% CF with 5% silica fume, the splitting tensile strength and shear strength of the concrete experienced improvements of 47% and 70%, respectively, compared to that of the control mix. The CF incorporation is detrimental to the imperviousness of concrete. The combined incorporation of CF and silica fume is recommended to minimize the negative effects of CF on the permeability resistance of concrete. The SEM results revealed that CF underwent a minor shrinkage with the age.

Comparison of three standard neoadjuvant chemotherapy regimens based on pathological tumor response in breast cancer patients.

We compared the efficacy of different neoadjuvant chemotherapy regimens and pathological factors related to higher pCR in localized breast cancer. This comparative retrospective study included 313 patients with breast carcinoma who received neoadjuvant therapy from January 2017 till July 31, 2019 at our institute. Patients were grouped in 3 different categories according to the treatment arms. In Arm A, patients received dose-dense AC [4 Cycles] followed by dose dense paclitaxel [4 Cycles]. In Arm B, 2 weekly dose dense AC [4 Cycles] followed-by paclitaxel every week [12 Cycles], while Arm C received 3 weekly AC [4 Cycles] and 3 weekly paclitaxel [4 Cycles]. pCR was seen in 135(43.1%) patients with the highest pCR in arm B i-e 33(55%), followed by 39(43.3%) in arm A, and 63(38.6%) in arm C. Triple-negative patients had the highest percentage of pCR 38 (65.5%). HER2 positive patients who received neoadjuvant Trastuzumab also had increased pCR rate of 21 (61.7%). ER/PR positive, HER2 negative patients had the lowest pCR 56 (33.5%). Dose dense AC [4 cycles] followed-by weekly Paclitaxel [12 cycles] is the most effective neoadjuvant therapy regimen for breast cancer patients, particularly if they were also triple negative and HER2 positive receiving Trastuzumab.

Micro and nanorobot-based drug delivery: an overview.

Progress in the drug delivery system in the last few decades has led to many advancements for efficient drug delivery. Both micro and nanorobots, are regarded as superior drug delivery systems to deliver drugs efficiently by altering other forms of energy into propulsion and movements. Furthermore, it can be advantageous as it is directed to targeted sites beneath physiological environments and conditions. They have been validated to possess the capability to encapsulate, transport, and supply therapeutic contents directly to the disease sites, thus enhancing the therapeutic efficiency and decreasing systemic side effects of the toxic drugs. This review discusses about the microand nanorobots for the diagnostics and management of diseases, types of micro, and nanorobots, role of robots in drug delivery, and its biomedical applications.

Investigation of Thermal Gel Formation of Methylcellulose in Glycols Using DSC and XRD.

Novel compositions of methylcellulose in ethylene, propylene and butylene glycol were investigated for their thermal gel formation. These compositions have previously been found useful for inkjet-printing-based additive manufacturing processes as support materials. Experimental techniques such as viscosity measurements between 20 °C-150 °C-20 °C, differential scanning calorimetry (DSC) and X-ray diffraction (XRD) were used and the results showed that the gel formation upon cooling is caused by polymer-polymer association. The results also show that, for methylcellulose, propylene glycol is a better solvent than ethylene glycol and butylene glycol. Since no chemical reaction is involved, these gels can be used as support materials for jetting-based additive manufacturing processes.

Different variants of pandemic and prevention strategies: A prioritizing framework in fuzzy environment.

In this trying time for the world battling different variants of the COVID'19 pandemic, different intervention strategies are being taken by government, to limit the spread of infection. Closing educational institutes, stay at home orders, campaigns for emphasis on vaccination, usage of medical mask and frequently sanitizing hands, etc. are the endeavors made by the authorities to decrease the number of cases in the country. In this regard, the contribution aims to help the decision-makers to identify a potential prevention strategy, based on public acceptance and intervention effectiveness. To achieve this objective, feasible judgments of professionals from three different sectors are brought together through meetings. Opinions, based on ten criteria, are recorded in linguistic form for prioritizing six alternatives. The linguistic terms are then evaluated and manipulated by entailing triangular fuzzy numbers and a group multi-criteria decision making (GMCDM) approach. After using the fuzzy analytical hierarchy process (F-AHP) for the complex decisions, the fuzzy VIsekriterijumsko KOmpromisno Rangiranje method (F-VIKOR) is utilized to attain the closest ideal stratagem. Consequently, through the ranking orders of defuzzified scores, intuitive preference of compromise solutions is suggested. The tactic gaining more priority with respect to the group utility to the majority and F-VIKOR index is complete lockdown for the short term. Furthermore, a comparison analysis is also added in the discussion to verify the attained prioritized outcomes. This comparative study is carried out through the technique for order of preference by similarity to ideal solution (TOPSIS), which evidently produces the same preference of alternatives. In addition, this strategy can be apparently discovered to be an effective strategy adopted by different countries in successfully decreasing the number of cases.

Histopathological Account of Obstetrical and Gynecological Specimens: Retrospective Study at a Tertiary Care Center of Peshawar.

Introduction Histopathologic specimen examination of surgically isolated organs and tissues yields valuable information regarding a disease process and plays a vital role in the future management of a patient. Our aim was to account for the common diagnosis yielded from histopathological specimens of the obstetrics and gynecology department and to determine if all the obstetric and gynecological specimens should be routinely sent for histopathology. Methods A retrospective, cross-sectional study was conducted at the histopathology unit of a tertiary care hospital in Peshawar. Data were acquired for all gynecological and obstetric specimens sent for histopathology for analysis to the histopathology unit during August 2018 and July 2019. Any sample that was not sent via surgical excision was excluded from the study. Results A total of 922 samples were sent for histopathological analysis in the tertiary care hospital. The mean age of patients who had their specimens sent for pathology was 40.78 ± 10.81 years. Most of the samples sent were of the uterus (458) and the age 31-50 years (270) had the highest proportion of histopathological specimens. Normal ovaries (64.4%) and fallopian tubes (78.8%) were the main diagnoses for these two specimens while a normal cervix (0.58%) was the least common diagnosis among samples sent for histopathology. Chronic cervicitis (92.4%) in cervix and secretory phase endometrium (30.1%) in the uterus were the other common diagnosis. All the other samples were infrequently sent. Conclusion Uterine specimens are the most common histopathological specimen sent followed by cervix and then fallopian tube. Fallopian tube and ovaries yielded the highest normal diagnosis. Cervix specimens must be biopsied. More data is needed for a certain consensus on the need for routine histopathology.

Qualitative and quantitative analysis of steatite using calibration-free laser-induced breakdown spectroscopy in conjunction with x-ray fluorescence spectroscopy and Fourier-transform infrared spectroscopy.

The qualitative and quantitative study of raw steatite was carried out using a pulsed nanosecond Nd:YAG laser set to fundamental harmonic (1064 nm) at atmospheric pressure. To cross-validate the data, x-ray diffraction (XRD), x-ray fluorescence (XRF) spectroscopy, and Fourier-transform infrared spectroscopy (FTIR) were used. The analysis of optical emission spectra in the wavelength range 200-720 nm showed the existence of silica (Si), magnesium (Mg), and calcium (Ca). The plasma temperature and electron number density were estimated using the Boltzmann plot and Stark-broadening line profile methods, with results at 4906 K and ${1.47}\times{{10}^{17}}\;{{\rm cm}^{- 3}}$, respectively. The quantitative study was carried out using the calibration-free laser-induced breakdown spectroscopy (CF-LIBS) process, assuming local thermodynamic equilibrium and an optically thin plasma, and the following results were obtained: Si = 63.37%, Mg = 35.95%, and Ca = 0.671%. The quantitative findings obtained using the CF-LIBS approach were consistent with those obtained using XRD, XRF, and FTIR, demonstrating the applied methods' potential to be effective and complementary for the qualitative and quantitative study of multiphase raw steatite.

Influence of semi-arid environment on radiation use efficiency and other growth attributes of lentil crop.

Solar radiation (SR) is essential for yield improvement in lentil, which is a crop of marginal environments. Herein, experiments were conducted over 2 years under a semi-arid environment to study the radiation interception (RI), efficiency, growth, and development of three lentil genotypes (Punjab Masoor-2009 (PM-2009), NIAB Masoor-2006 (NM-2006), and NIAB Masoor-2002 (NM-2002)) in relation to three nitrogen rates (13, 19, and 25 kg ha-1). Seasonal dynamics of intercepted photoactive radiation (IPAR) and cumulated photosynthetic photon flux density were highly associated with seasonal dynamics of leaf area index (LAI), with a high value of R2 (0.93 and 0.89) across all nitrogen rates and genotypes in both years. Nitrogen application promoted growth, and maximum LAI (3.97 and 3.57) and RI (324 and 301 MJ m-2) were attained for the first and second years of study, respectively. Biomass and yield were positively associated with IPAR. Variation in radiation absorption (RA) among genotypes was due to different patterns of LAI development. In both years, yield (23% and 25%) and radiation use efficiency (RUE) for grain yield (0.44 and 0.37 g MJ-1) were respectively higher for PM-2009 than for the other genotypes. Genotype PM-2009 had 15 days shorter crop cycle than others while 14% higher GDDs accumulated in the first year compared with the second due to the higher temperature. High nitrogen (25 kg ha-1) application resulted in higher dry matter (DM), and grain yield (GY), while RUE and PAR were not statistically different under 19 kg N ha-1 application across years. Genotypes PM-2009 and NM-2006 may perform reasonably well under arid to semi-arid regions at farmer field. These findings may assist researchers and crop modelers to optimize the lentil ideotype for efficient light utilization.

Robot-Assisted Pedestrian Regulation Based on Deep Reinforcement Learning.

Pedestrian regulation can prevent crowd accidents and improve crowd safety in densely populated areas. Recent studies use mobile robots to regulate pedestrian flows for desired collective motion through the effect of passive human-robot interaction (HRI). This paper formulates a robot motion planning problem for the optimization of two merging pedestrian flows moving through a bottleneck exit. To address the challenge of feature representation of complex human motion dynamics under the effect of HRI, we propose using a deep neural network to model the mapping from the image input of pedestrian environments to the output of robot motion decisions. The robot motion planner is trained end-to-end using a deep reinforcement learning algorithm, which avoids hand-crafted feature detection and extraction, thus improving the learning capability for complex dynamic problems. Our proposed approach is validated in simulated experiments, and its performance is evaluated. The results demonstrate that the robot is able to find optimal motion decisions that maximize the pedestrian outflow in different flow conditions, and the pedestrian-accumulated outflow increases significantly compared to cases without robot regulation and with random robot motion.