Results from an expedited spinal nerve root block clinic at a UK tertiary neurosurgical centre.

STUDY DESIGN: Retrospective Observational Study. INTRODUCTION: Lumbar radicular pain has a prevalence of 3-5%. Level 1 evidence has demonstrated equivalence between surgical and injection treatment. We assess the outcomes from a transforaminal epidural steroid injection clinic in a tertiary neuroscience referral centre. METHODS: We performed an analysis of data from consecutive patients entered into a new internal referral database between August 2018 to May 2021. Radicular pain was classified as one of "first presentation" or "recurrence". Outcomes were obtained from follow up clinic letters and recorded in a binary manner of "positive result" or "negative result". Spinal pathology was documented from radiology reports and MRI images. RESULTS: We analysed 208 patients referred to the clinic. Excluding those who improved to a point of not requiring treatment, and those who underwent surgical intervention, 119 patients undergoing injection were included, of which 14 were lost to follow-up. 68 % of patients had a positive result from injection. Subgroup analysis demonstrated good outcomes for both hyperacute (<6 weeks) and chronic (>12 months). Contained disk pathologies had better outcomes than uncontained. There was no difference in outcomes across grades of compression, but previous same level surgery was associated with poorer response rates. CONCLUSIONS: There is a high rate of natural resolution of symptoms in patients with LSRP. In those where pain persists, TFESI is a valuable first line treatment modality. This study suggests the efficacy of TFESI is potentially independent of grade of stenosis and chronicity of symptoms. Contained disc pathologies respond better than uncontained.

Zinc Aluminum Oxide Encapsulation Layers for Perovskite Solar Cells Deposited Using Spatial Atomic Layer Deposition.

An atmospheric-pressure spatial atomic layer deposition system is used to rapidly deposit 60 nm zinc-aluminum oxide (Zn-AlOx ) thin-film-encapsulation layers directly on perovskite solar cells at 130 °C without damaging the temperature-sensitive perovskite and organic materials. Varying the Zn/Al ratio has a significant impact on the structural properties of the films and their moisture barrier performance. The Zn-AlOx films have higher refractive indexes, lower concentrations of OH─ groups, and lower water-vapor transmission rates (WVTR) than AlOx films without zinc. However, as the Zn/Al ratio increases beyond 0.21, excess Zn atoms segregate, leading to an increase in the number of available hydroxyl groups on the surface of the deposited film and a slight increase in the WVTR. The stability of the p-i-n formamidinium methylammonium lead iodide solar cells under standard ISOS-D-3 testing conditions (65 °C and 85% relative humidity) is significantly enhanced by the thin encapsulation layers. The layers with a Zn/Al ratio of 0.21 result in a seven-fold increase the time required for the cells to degrade to 80% of their original efficiency.

CenTime: Event-conditional modelling of censoring in survival analysis.

Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on baseline observations. This is particularly useful in healthcare to prognostically predict clinically important events based on patient data. However, existing approaches often have limitations; some focus only on ranking patients by survivability, neglecting to estimate the actual event time, while others treat the problem as a classification task, ignoring the inherent time-ordered structure of the events. Additionally, the effective utilisation of censored samples-data points where the event time is unknown- is essential for enhancing the model's predictive accuracy. In this paper, we introduce CenTime, a novel approach to survival analysis that directly estimates the time to event. Our method features an innovative event-conditional censoring mechanism that performs robustly even when uncensored data is scarce. We demonstrate that our approach forms a consistent estimator for the event model parameters, even in the absence of uncensored data. Furthermore, CenTime is easily integrated with deep learning models with no restrictions on batch size or the number of uncensored samples. We compare our approach to standard survival analysis methods, including the Cox proportional-hazard model and DeepHit. Our results indicate that CenTime offers state-of-the-art performance in predicting time-to-death while maintaining comparable ranking performance. Our implementation is publicly available at https://github.com/ahmedhshahin/CenTime.

Hybrid global search with enhanced INC MPPT under partial shading condition.

The photovoltaic system is quickly emerging as a highly favored option among renewable energy sources. However, it faces several significant challenges, including variable solar irradiance, temperature, and partial shading. Unfortunately, conventional Maximum Power Point Trackers (MPPTs) cannot accurately track partial shading. Artificial intelligence and optimization techniques have been proposed as alternatives, but they require extensive training and can take a long time to achieve maximum power point (MPP) under partial shading circumstances. In this paper, a dynamic and fast-moving method of MPP tracking is proposed for use under both uniform solar irradiance and partial shade. This method combines an enhanced incremental conductance (INC) algorithm with a global search algorithm that looks at how well solar cells work when partly shaded. Simulation investigations are performed to validate the method's applicability and ensure that it reaches the most accurate value of MPP with a short-tracking time of less than 0.2 s and a steady-state error of less than 0.3% of the PV power. The results confirm the efficacy of the suggested tracking method under uniform solar irradiance and partial shade.

Improving efficiency of parallel inverters operation in island mode microgrids.

DC/AC inverters play a vital role in microgrids, efficiently converting renewable energy into usable AC power. Parallel operation of inverters presented numerous challenges, including maximizing system efficiency, minimizing circulating current, and maximizing system accuracy. This proposal introduces an analytical optimization technique designed to enhance the efficiency of paralleled inverters in microgrid systems while minimizing circulating current. The system parameter estimation is performed with a rapid recursive least squares (RLS) estimator. An optimized proportional-integral-derivative (PID) controller achieves high accuracy and streamlining system construction. The performance of the proposed optimizer is compared to common optimization methods, such as particle swarm optimization (PSO), neural networks, interior search, and interior point optimizers, focusing on system efficiency and eliminating circulating currents. Simulation investigations validated the method's applicability and demonstrated the proposed optimizer's superiority in efficiency, stability, and limiting circulating currents. It also achieved zero execution time, significantly outperforming alternatives like the neural network optimizer, which took 0.693 s. In various scenarios, the proposed optimizer improved system efficiency by 3% compared to the equally shared current system.

Manufacturing of quantum-tunneling MIM nanodiodes via rapid atmospheric CVD in terahertz band.

Quantum-tunneling metal-insulator-metal (MIM) diodes have emerged as a significant area of study in the field of materials science and electronics. Our previous work demonstrated the successful fabrication of these diodes using atmospheric pressure chemical vapor deposition (AP-CVD), a scalable method that surpasses traditional vacuum-based methods and allows for the fabrication of high-quality Al2O3 films with few pinholes. Here, we show that despite their extremely small size 0.002 µm2, the MIM nanodiodes demonstrate low resistance at zero bias. Moreover, we have observed a significant enhancement in resistance by six orders of magnitude compared to our prior work, Additionally, we have achieved a high responsivity of 9 AW-1, along with a theoretical terahertz cut-off frequency of 0.36 THz. Our approach provides an efficient alternative to cleanroom fabrication, opening up new opportunities for manufacturing terahertz-Band devices. The results of our study highlight the practicality and potential of our method in advancing nanoelectronics. This lays the foundation for the development of advanced quantum devices that operate at terahertz frequencies, with potential applications in telecommunications, medical imaging, and security systems.

Effect of different oxygen precursors on alumina deposited using a spatial atomic layer deposition system for thin-film encapsulation of perovskite solar cells.

An atmospheric-pressure spatial atomic layer deposition system operated in atmospheric-pressure spatial chemical vapor deposition conditions is employed to deposit alumina (AlOx) thin films using trimethylaluminum and different oxidants, including water (H2O), hydrogen peroxide (H2O2), and ozone (O3). The impact of the oxygen precursor on the structural properties of the films and their moisture-barrier performance is investigated. The O3-AlOxfilms, followed by H2O2-AlOx, exhibit higher refractive indexes, lower concentrations of OH- groups, and lower water-vapor-transmission rates compared to the films deposited using water (H2O-AlOx). The AlOxfilms are then rapidly deposited as thin-film-encapsulation layers on perovskite solar cells at 130 °C without damaging the temperature-sensitive perovskite and organic materials. The stability of thep-i-nformamidinium methylammonium lead iodide solar cells under standard ISOS-D-3 testing conditions (65 °C and 85% relative humidity) is significantly enhanced by the encapsulation layers. Specifically, the O3-AlOxand H2O2-AlOxlayers result in a six-fold increase in the time required for the cells to degrade to 80% of their original efficiency compared to un-encapsulated cells.

The Impact of Palliative Chemotherapy on the Survival of Patients With Metastatic Colorectal Cancer in Jordan.

Background In Jordan, managing metastatic colorectal cancer (mCRC) is particularly complex, considering limited resources, access to advanced therapies, and unique patient demographics. Palliative chemotherapy, an approach aimed at relieving symptoms and improving the quality of life in patients with advanced cancer, including mCRC, has gained attention as a treatment strategy. While palliative chemotherapy may not aim for complete cancer eradication, it can extend survival, manage disease-related symptoms, and enhance the patient's overall well-being. However, deciding to pursue palliative chemotherapy for mCRC patients involves individual patient characteristics, performance status, disease aggressiveness, potential treatment-related adverse effects, and available healthcare resources. Given the need for region-specific insights into treatment outcomes, the proposed study seeks to investigate the impact of palliative chemotherapy on overall survival (OS), specifically within Jordan's healthcare landscape. Our study aims to showcase palliative chemotherapy's effectiveness on OS in first-line settings. Materials and methods This study is a retrospective analysis conducted at the Military Cancer Center (MCAC) in Jordan. It includes 73 patients diagnosed with mCRC between January 1, 2018, and January 1, 2020. Data were obtained from electronic medical records, and patients were monitored until June 10, 2023. Various patient characteristics were analyzed, including age, sex, primary tumor site, metastatic site, and treatment options for mCRC. The study evaluated the effectiveness of palliative chemotherapy in improving survival rates compared to BSC. Result We conducted a study with 73 participants, whose mean age was 60.37 ±13.5 years and a median of 63. Of these patients, 51 (69.9%) were male, and 22 (30.1%) were female. The primary site of the tumor was located on the left side in 32 patients (43.9%), on the right side in 26 patients (35.6%), and rectal cancer in 15 patients (20.5%). The most common site of the tumor was the sigmoid (17 patients, 23.3%). The liver was the most common site of metastasis (52 patients, 71.2%). Of the patients, 47 (64.4%) received palliative chemotherapy, while 26 (35.6%) were kept on best supportive care (BSC). Of those who received chemotherapy, FOLFIRI was administered to 32 patients (43.8%) and FOLFOX to 15 patients (20.5%). Based on the Kaplan-Meier curve, palliative chemotherapy patients had a significantly longer OS than those who only received BSC. Patients with palliative chemotherapy had a median OS of 12.4 months, while those who only had BSC survived for 5.3 months. The HR was 0.36 with a 95% confidence interval of 0.2-0.62, and the P-value was less than 0.001. Conclusion This study shows that palliative chemotherapy offers a notable advantage and a significant survival benefit compared to BSC.

A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study.

In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respiratory causes were identified whereby the CNN model was used to capture imaging features in the CT scans and the RNN model was used to investigate time series and thus global information. To account for heterogeneity in patients' follow-up times, two different variants of LSTM models were evaluated, each incorporating different strategies to address irregularities in follow-up time. The models were trained on subjects who underwent cardiovascular and respiratory deaths and a control cohort matched to participant age, gender, and smoking history. The combined model can achieve an AUC of 0.76 which outperforms humans at cardiovascular mortality prediction. The corresponding F1 and Matthews Correlation Coefficient are 0.63 and 0.42 respectively. The generalisability of the model is further validated on an 'external' cohort. The same models were applied to survival analysis with the Cox Proportional Hazard model. It was demonstrated that incorporating the follow-up history can lead to improvement in survival prediction. The Cox neural network can achieve an IPCW C-index of 0.75 on the internal dataset and 0.69 on an external dataset. Delineating subjects at increased risk of cardiorespiratory mortality can alert clinicians to request further more detailed functional or imaging studies to improve the assessment of cardiorespiratory disease burden. Such strategies may uncover unsuspected and under-recognised pathologies thereby potentially reducing patient morbidity.

Tamarindus indica Extract as a Promising Antimicrobial and Antivirulence Therapy.

The worldwide crises from multi-drug-resistant (MDR) bacterial infections are pushing us to search for new alternative therapies. The renewed interest in medicinal plants has gained the attention of our research group. Tamarindus indica L. (T. indica) is one of the traditional medicines used for a wide range of diseases. Therefore, we evaluated the antimicrobial activities of ethanolic extract of T. indica. The inhibitions zones, minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and fractional inhibitor concentration indices (FICI) against Gram+ve and -ve pathogens were detected. The bioactive compounds from T. indica extract were identified by mass spectroscopy, thin-layer chromatography, and bio-autographic assay. We performed scanning electron microscopy (SEM) and molecular docking studies to confirm possible mechanisms of actions and antivirulence activities, respectively. We found more promising antimicrobial activities against MDR pathogens with MIC and MBC values for Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa), i.e., (0.78, 3.12 mg/mL) and (1.56, 3.12 mg/mL), respectively. The antimicrobial activities of this extract were attributed to its capability to impair cell membrane permeability, inducing bacterial cell lysis, which was confirmed by the morphological changes observed under SEM. The synergistic interactions between this extract and commonly used antibiotics were confirmed (FICI values < 0.5). The bioactive compounds of this extract were bis (2-ethylhexyl)phthalate, phenol, 2,4-bis(1,1-dimethylethyl), 1,2-benzenedicarboxylic acid, and bis(8-methylnonyl) ester. Additionally, this extract showed antivirulence activities, especially against the S. aureus protease and P. aeruginosa elastase. In conclusion, we hope that pharmaceutical companies can utilize our findings to produce a new formulation of T. indica ethanolic extract with other antibiotics.

WS2 and WS2-ZnO Chemiresistive Gas Sensors: The Role of Analyte Charge Asymmetry and Molecular Size.

We investigate the interaction of various analytes (toluene, acetone, ethanol, and water) possessing different structures, bonding, and molecular sizes with a laser-exfoliated WS2 sensing material in a chemiresistive sensor. The sensor showed a clear response to all analytes, which was significantly enhanced by modifying the WS2 surface. This was achieved by creating WS2-ZnO heterojunctions via the deposition of ZnO nanoparticles on the WS2 surface with a high-throughput, atmospheric-pressure spatial atomic layer deposition system. Water and ethanol produced a much higher response compared to acetone and toluene for both the WS2 and WS2-ZnO sensing mediums. We resolved that the charge-asymmetry points in analyte molecules play a key role in determining the sensor response. High charge-asymmetry points correspond to highly polar bonds (HPBs) in a neutral molecule that have a high probability of interaction with the sensing medium. Our results indicate that the polarity of the HPBs primarily dictates the interaction between the analyte and sensing medium and consequently controls the response of the sensor. Moreover, the size of the analyte molecule was found to affect the sensing response; if two molecules have the same HPBs and are exposed to the same sensing medium, the smaller molecule is likely to produce a higher and faster response. Our study provides a comprehensive picture of analyte-sensor interactions that can help in advancing semiconductor gas sensors, including those based on two-dimensional materials.

Integrating in vivo and in silico approaches to investigate the potential of Zingiber roseum rhizome extract against pyrexia, inflammation and pain.

Zingiber roseum is a perennial herb in the Zingiberaceae family. The plant is native to Bangladesh, and rhizomes are frequently used in traditional medicine to cure gastric ulcers, asthma, wounds, and rheumatic disorders. Therefore, the present study aimed to analyse the antipyretic, anti-inflammatory, and analgesic properties of Z. roseum rhizome to confirm its efficacy in traditional applications. After 24 h of treatment, ZrrME (400 mg/kg) showed a considerable drop in rectal temperature (3.42°F) compared to standard paracetamol (5.26°F). At both doses (200 and 400 mg/kg), ZrrME showed a substantial dose-dependent decrease in paw oedema. However, after 2, 3 and 4 h of testing, the extract (200 mg/kg) had a lower anti-inflammatory response than standard indomethacin, whereas the higher dose (400 mg/kg) of rhizome extract had a more robust response compared to standard. ZrrME also showed substantial analgesic activity against all in vivo analgesic test models. The in vivo findings were further evaluated by in silico study of our previously identified compounds of ZrrME with the cyclooxygenase-2 enzyme (3LN1). The substantial binding energy (ranges from-6.2 to-7.7 Kcal/mol) of the polyphenols (excluding catechin hydrate) to the COX-2 enzyme affirm the in vivo test results of the present studies. In addition, the compounds were found effective as antipyretic, anti-inflammatory, and analgesic agents, according to the biological activity prediction software. Both in vivo and in silico results demonstrated promising antipyretic, anti-inflammatory, and pain-relieving effects of Z. roseum rhizome extract, which corroborate the claim of its traditional uses.

Impact of KRAS Mutation on Survival Outcome of Patients With Metastatic Colorectal Cancer in Jordan.

Background Colorectal cancer (CRC) is the most prevalent cancer in males, with an incidence rate (IR) of 13.1%, and the second most prevalent cancer in females, with an IR of 8.4%, coming after breast cancer in Jordan. The present study was motivated by conflicting clinical data regarding the prognostic impact of Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in patients with metastatic colorectal cancer (mCRC). Our study aimed to investigate if KRAS mutation conferred a negative prognostic value in Jordanian patients with mCRC. Materials and methods The current study is a retrospective study that collected data from a cohort of 135 mCRC patients diagnosed between 1 January 2017 and 1 January 2022 at our Oncology Department at the Jordanian Military Cancer Center (MCAC) using our patients' electronic medical records. The last follow-up date was 1 September 2022. From the cohort, we obtained data regarding age, sex, date of diagnosis, metastatic spread, KRAS status, either mutated KRAS or wild-type KRAS, and location of the primary tumor. All patients underwent tumor tissue biopsies to determine KRAS mutational status based on quantitative polymerase chain reaction and reverse hybridization from an accredited diagnostic laboratory at Jordan University Hospital. Statistical analysis was carried out to address the associations between KRAS mutation and the patients-tumor characteristics and their prognosis on survival. Results KRAS mutation was found in 40.3% of the participants in the study, and 56.7% had the wild type. There was a predilection of KRAS mutation, with 67% on the right side versus 33% on the left side (p = 0.018). Kaplan-Meier survival analysis showed worse survival outcomes in KRAS mutant patients (p = 0.002). The median overall survival in the KRAS mutant patients was 17 months (95% confidence interval (CI): 13.762-19.273) compared to 21 months (95% CI: 20.507-27.648) in patients with wild-type KRAS. Additionally, the Cox regression model identified that KRAS mutation carries a poorer prognosis on survival outcome hazard ratio (HR: 2.045, 95% CI: 1.291-3.237, p = 0.002). The test also showed statistical significance in the metastatic site (lung only). But this time, it was associated with a better survival outcome (HR: 0.383, 95% CI: 0.186-0.788, p = 0.009). Conclusion The present study shows that the presence of KRAS mutation has been found to negatively impact the prognosis and survival outcome of Jordanian patients with mCRC.

Benzoates as photosensitization catalysts and auxiliaries in efficient, practical, light-powered direct C(sp3)-H fluorinations.

Of the methods for direct fluorination of unactivated C(sp3)-H bonds, photosensitization of SelectFluor is a promising approach. Although many substrates can be activated with photosensitizing catalysts, issues remain that hamper fluorination of complex molecules. Alcohol- or amine-containing functional groups are not tolerated, fluorination regioselectivity follows factors endogenous to the substrate and cannot be influenced by the catalyst, and reactions are highly air-sensitive. We report that benzoyl groups serve as highly efficient photosensitizers which, in combination with SelectFluor, enable visible light-powered direct fluorination of unactivated C(sp3)-H bonds. Compared to previous photosensitizer architectures, the benzoyls have versatility to function both (i) as a photosensitizing catalyst for simple substrate fluorinations and (ii) as photosensitizing auxiliaries for complex molecule fluorinations that are easily installed and removed without compromising yield. Our auxiliary approach (i) substantially decreases the reaction's induction period, (ii) enables C(sp3)-H fluorination of many substrates that fail under catalytic conditions, (iii) increases kinetic reproducibility, and (iv) promotes reactions to higher yields, in shorter times, on multigram scales, and even under air. Observations and mechanistic studies suggest an intimate 'assembly' of auxiliary and SelectFluor prior/after photoexcitation. The auxiliary allows other EnT photochemistry under air. Examples show how auxiliary placement proximally directs regioselectivity, where previous methods are substrate-directed.

Polyphenols Profile and Enzyme Inhibitory Properties of Blumea lacera (Burm. f.) DC.: A Potential Candidate against Obesity, Aging, and Skin Disorder.

Blumea lacera (Burm. f.) DC. is attracting scientific interest due to the diverse biological activities of its various parts and its use in folk medicine. The present study was undertaken to investigate the tissue-specific differential expression pattern of its total bioactive compounds. The study was further extended to whole plant phenolics profiling, in vitro enzyme inhibition activities, followed by in silico enzyme inhibition analysis to assess its potential as herbal medicine. The amount of total phenolics in different tissues was followed in decreasing order as old leaf, flower bud, root, young leaf, flower, old stem, and young stem, while that for the flavonoids was old leaf, root, young leaf, flower bud, flower, young stem, and old stem. This study identified rosmarinic acid, quercetin, and kaempferol in this plant for the first time. The solvent extracts demonstrated strong inhibition of lipase and tyrosinase activity, along with varying degrees of inhibition of acetylcholinesterase and butyrylcholinesterase activity. Among the detected compounds, ten displayed strong in silico binding affinities with the tested enzymes. The findings provide a new insight into further investigation of the medicinal potential of this species against obesity, neurological disorders, and aberrant skin color.

An organophotocatalytic late-stage N-CH3 oxidation of trialkylamines to N-formamides with O2 in continuous flow.

We report an organophotocatalytic, N-CH3-selective oxidation of trialkylamines in continuous flow. Based on the 9,10-dicyanoanthracene (DCA) core, a new catalyst (DCAS) was designed with solubilizing groups for flow processing. This allowed O2 to be harnessed as a sustainable oxidant for late-stage photocatalytic N-CH3 oxidations of complex natural products and active pharmaceutical ingredients bearing functional groups not tolerated by previous methods. The organophotocatalytic gas-liquid flow process affords cleaner reactions than in batch mode, in short residence times of 13.5 min and productivities of up to 0.65 g per day. Spectroscopic and computational mechanistic studies showed that catalyst derivatization not only enhanced solubility of the new catalyst compared to poorly-soluble DCA, but profoundly diverted the photocatalytic mechanism from singlet electron transfer (SET) reductive quenching with amines toward energy transfer (EnT) with O2.

Alcohol-based Hand Sanitizers amid COVID-19: Chemical Formulation, Analysis, Safety.

Alcohol-based hand sanitizers (ABHSs) containing ethanol (EtOH) or isopropyl alcohol (IPA) to inactivate microorganisms help prevent the spread of respiratory diseases. These products have become very popular during the COVID-19 pandemic. Apart from vaccines or other preventative antiseptic measures, the majority of consumers have relied on different types of ABHSs to disinfect their hands. As a result, there has been a global rush in the demand for these ABHSs and other antiseptic hygiene products. This has resulted in the formation of many new commercial sanitizer producers. There are around fifty companies of varying sizes that have been marketing their ABHSs in Bangladesh, most of which have only been manufacturing their products for the first time since the COVID-19 pandemic. To monitor the quality and components of these products, the Bangladesh Council of Scientific and Industrial Research (BCSIR) analyzed approximately 200 different hand sanitizer samples using GC-FID method. All samples were alcohol-based except for 3 which were alcohol-free aqueous hand sanitizers. Of the supplied formulated ABHSs, 80 samples were found to contain only IPA and 54 contained only EtOH. However, 28 samples were found to be contaminated with methanol (MeOH), 7 samples contained only MeOH and 18 samples contained both EtOH and IPA. This is the first study to explore the analysis of alcohol content in formulated ABHSs and their marketing status in Bangladesh, but the findings could be of use in other jurisdictions as similar issues have been raised in many parts of the world.

SVA-SSD: saliency visual attention single shot detector for building detection in low contrast high-resolution satellite images.

Building detection in high-resolution satellite images has received great attention, as it is important to increase the accuracy of urban planning. The building boundary detection in the desert environment is a real challenge due to the nature of low contrast images in the desert environment. The traditional computer vision algorithms for building boundary detection lack scalability, robustness, and accuracy. On the other hand, deep learning detection algorithms have not been applied to such low contrast satellite images. So, there is a real need to employ deep learning algorithms for building detection tasks in low contrast high-resolution images. In this paper, we propose a novel building detection method based on a single-shot multi-box (SSD) detector. We develop the state-of-the-art SSD detection algorithm based on three approaches. First, we propose data-augmentation techniques to overcome the low contrast images' appearance. Second, we develop the SSD backbone using a novel saliency visual attention mechanism. Moreover, we investigate several pre-trained networks performance and several fusion functions to increase the performance of the SSD backbone. The third approach is based on optimizing the anchor-boxes sizes which are used in the detection stage to increase the performance of the SSD head. During our experiments, we have prepared a new dataset for buildings inside Riyadh City, Saudi Arabia that consists of 3878 buildings. We have compared our proposed approach vs other approaches in the literature. The proposed system has achieved the highest average precision, recall, F1-score, and IOU performance. Our proposed method has achieved a fast average prediction time with the lowest variance for our testing set. Our experimental results are very promising and can be generalized to other object detection tasks in low contrast images.

Photocatalyst-Free, Visible-Light-Mediated C(sp3)-H Arylation of Amides via a Solvent-Caged EDA Complex.

A photocatalyst-free and mild visible light photochemical procedure for C(sp3)-H arylation of amides is described. The reaction proceeds via an electron donor-acceptor (EDA) complex between an electron-rich arene substrate and electron-poor persulfate oxidant. C(sp3)-H arylation of the amide occurs selectively with the most electron-rich arene of the substrate. Mechanistic studies corroborate the reaction taking place in a solvent cage holding components in a close proximity.