BACKGROUND: Unmanned aerial vehicles (UAVs), more commonly known as drones, have rapidly become more diverse in capabilities and utilization through technology advancements and affordability. While drones have had significant positive impact on healthcare and consumer delivery particularly in remote and austere environments, Violent Non-State Actors (VNSAs) have increasingly used drones as weapons in planning and executing terrorist attacks resulting in significant morbidity and mortality. We aim to analyze drone-related attacks globally against civilians and critical infrastructure for more effective hospital and prehospital care preparedness.
METHODS: We retrospectively reviewed the Global Terrorism Database (GTD) from 1970 to 2020 to analyze the worldwide prevalence of drone-related attacks against civilians and critical infrastructure. Cases were excluded if they had insufficient information regarding a drone involvement, and if attacks were conducted by the government entities. The trends in the number of attacks per month, as well as the number of fatalities and injuries, were examined using time series and trend analysis.
RESULTS: The database search yielded 253 drone-related incidents, 173 of which met inclusion criteria. These incidents resulted in 92 fatalities and 215 injuries with civilian targets most commonly attacked by drones (76 events, 43.9%), followed by military (46 events, 26.5-%). The Middle East region was most affected (168 events, 97% of attacks) and the Islamic state of Iraq was the most common perpetrator (106 events, 61.2%). Almost all attacks were by explosive devices attached to drones (172 events, 99.4%). Time series with linear trend analyses suggested an upward trends of drone attacks by VNSAs, resulting in a greater number of injuries and fatalities, that became more frequent over the years.
CONCLUSIONS: Overtime, there were upward trends of drone attacks, with higher lethality and morbidity. There were more injuries compared to fatalities. Most common region affected was the Middle East, and most common type of weapon employed by drone technology was explosive weapon. Investment in medical personnel training, security, and research is crucial for an effective mass-casualty incident response after the drone attacks.

To assess the effects of warm-up music and low dose (3 mg·kg-1) of caffeine (CAF) on female taekwondo athlete\'s activity profile and psychophysiological responses during simulated combat. In a double-blinded, randomized, crossover study, 16 female athletes participated in simulated combats under one control and 5 experimental conditions [i.e., CAF alone (CAF), placebo alone (PL), CAF with music (CAF + M), PL with music (PL + M), and no supplement with music (M)]. After warming-up, athletes rated their felt arousal (FAS). Mean (HRmean) and peak (HRpeak) heart rate values were determined for each combat. After fighting, athletes rated their perceived exertion (RPE), feeling scale (FS), FAS, and physical enjoyment (PACES). Time-motion and technical-tactical variables were analyzed. CAF + M induced shorter skip and pause time, while attack time increased compared to other conditions (p < 0.05). Moreover, CAF + M increased single attacks, combined attacks, counter-attacks (p < 0.001), and defensive actions (p < 0.05) than other conditions. HRmean and HRpeak were lower under CAF + M than other conditions (p < 0.05). Additionally, higher FAS post-combat, FS, and PACES were observed under CAF + M, while RPE was lower (except CAF condition) compared to the other conditions (p < 0.05.Using CAF with warm-up music may increase combat cadence and improve the psychological state in female athletes more effectively than either strategy alone.

Generalized Person Re-Identification (GReID) aims to develop a model capable of robust generalization across unseen target domains, even with training on a limited set of observed domains. Recently, methods based on the Attack-Defense mechanism are emerging as a prevailing technology to this issue, which treats domain transformation as a type of attack and enhances the model\'s generalization performance on the target domain by equipping it with a defense module. However, a significant limitation of most existing approaches is their inability to effectively model complex domain transformations, largely due to the separation of attack and defense components. To overcome this limitation, we introduce an innovative Interactive Attack-Defense (IAD) mechanism for GReID. The core of IAD is the interactive learning of two models: an attack model and a defense model. The attack model dynamically generates directional attack information responsive to the current state of the defense model, while the defense model is designed to derive generalizable representations by utilizing a variety of attack samples. The training approach involves a dual process: for the attack model, the aim is to increase the challenge for the defense model in countering the attack; conversely, for the defense model, the focus is on minimizing the effects instigated by the attack model. This interactive framework allows for mutual learning between attack and defense, creating a synergistic learning environment. Our diverse experiments across datasets confirm IAD\'s effectiveness, consistently surpassing current state-of-the-art methods, and using MSMT17 as the target domain in different protocols resulted in a notable 13.4% improvement in GReID task average Rank-1 accuracy. Code is available at: https://github.com/lhf12278/IAD.

OBJECTIVE: Familial Mediterranean fever (FMF) is the most common inherited autoinflammatory disease in the world. There are known triggers to initiate an FMF attack, yet potential effects of intrauterine devices (IUD) in women of reproductive age have not been evaluated before.
METHODS: Consecutive female patients with FMF who ever used IUD over the age of 18 were enrolled. Female patients with FMF were sub grouped according to the type of IUD they use. FMF attack frequency, severity, duration, presence of dysmenorrhea, severity of dysmenorrhea, having attacks during menstruation before and after IUD use were questioned. Demographic and clinical data were collected from hospital database.
RESULTS: When all patients with IUD use were evaluated, it was found that the frequency of attacks increased after IUD insertion at 3rd and 12th months (median [min-max] attack frequency at 3rd month, 1 (0-3) vs 1 (0-6), p = 0.002, median [min-max] attack frequency at 12th month, 2 (0-12) vs 3.5 (0-18), p = 0.028). Attack severity measured by VAS pain was also significantly increased. Attack duration and menstrual pain was similar before and after IUD use. Attack frequency at 3rd and 12th months, attack severity and menstrual pain was all increased significantly in Cu-IUD users, whereas none of these parameters deteriorated in LNG-IUD group.
CONCLUSIONS: IUD use, especially Cu-IUD, may increase the frequency and severity of attacks in female patients with FMF. Clinicians may benefit from considering LGN-IUD if IUDs are preferred as contraception in women of childbearing age with FMF.

An electrocardiogram, used to not only assess the rate and rhythm of the heart but also to evaluate for injury to the heart, is performed by attaching 12 leads to the patient\'s body. A myocardial infarction can be mimicked by the misplacement of the leads. A 58-year-old man with long-distance running-associated bradycardia developed postoperative atrial fibrillation with a rapid ventricular response. He converted to normal sinus rhythm after a single oral dose of 30 milligrams of diltiazem; however, the automated reading of the electrocardiogram performed in the hospital showed new changes suggestive of a postero-lateral myocardial infarction, including Q waves in leads I and aVL, as well as early precordial R wave progression with R waves and positive T waves in V2 and V3, and a dominant R wave (R wave to S wave ratio greater than one) in V2. A cardiac work-up was entirely normal: serial troponin levels, thyroid stimulating hormone, echocardiogram, computerized tomography of the chest, and Doppler studies of the extremities. Lead misplacement during the electrocardiogram was suspected during the subsequent evaluation by an astute cardiologist; the findings were diagnostic for a left arm to right arm limb lead reversal. All the changes in myocardial infarction were absent when the electrocardiogram was repeated in the office. Misplacement of leads during an electrocardiogram is not a rare event; therefore, the clinician needs to consider the possibility of improper placement of the leads when evaluating an electrocardiogram. Indeed, emotional distress, additional diagnostic procedures, and potentially harmful procedures may be experienced by the patient from incorrect diagnoses based on electrode misplacement during an electrocardiogram; in addition, there are often increased costs to the patient and the healthcare system. Therefore, in the setting of an incorrect diagnosis attributed to lead misplacement during the performance of an electrocardiogram, the acronym MISFIT (which uses the first letters of the words \"myocardial infarction simulated from improper telemetry\") has been introduced. In conclusion, it is important to emphasize that a MISFIT is characterized by an electrocardiogram \'mis\'diagnosis of a myocardial infarction that does not \'fit\' with the clinical scenario.

Sensor data has been used in social security and welfare infrastructures such as insurance and medical care to provide personalized products and services; there is a risk that attackers can alter sensor data to obtain unfair benefits. We consider that one of the attack methods to modify sensor data is to attack the wearer\'s body to modify biometric information. In this study, we propose a noninvasive attack method to modify the sensor value of a photoplethysmogram. The proposed method can disappear pulse wave peaks by pressurizing the upper arm with air pressure to control blood volume. Seven subjects experiencing a rest environment and five subjects experiencing an after-exercise environment wore five different models of smartwatches, and three pressure patterns were performed. It was confirmed in both situations that the displayed heart rate decreased from the true heart rate.

OBJECTIVE: To evaluate the effect of vitamin D supplementation on the frequency and duration of attacks in patients of PFAPA syndrome with low vitamin D levels.
METHODS: This retrospective study comprised PFAPA patients with vitamin D deficiency/insufficiency between 2018 and 2023. The frequency and duration of PFAPA attacks before and after vitamin D supplementation were noted.
RESULTS: Seventy-one patients were included. Of the 71 patients, 24 (33.8%) had vitamin D insufficiency, and 47 (66.2%) had vitamin D deficiency. In patients with vitamin D insufficiency, mean attack frequency and mean attack duration before vitamin D supplementation were 4.3 ± 1.9/year and 2.2 ± 1.6 days, respectively, while mean attack frequency and mean attack duration after vitamin D supplementation were 3.5 ± 2.7/year per year and 1.3 ± 0.9 days respectively (p = 0.2, p = 0.2, respectively). In patients with vitamin D deficiency, mean attack frequency and mean attack duration before vitamin D supplementation were 7.4 ± 2.1/year and 2.2 ± 1.6 days, respectively, while mean attack frequency and mean attack duration after vitamin D supplementation were 3.3 ± 2.4/year and 1.3 ± 0.9 days respectively (p < 0.01, p = 0.04, respectively). When the vitamin D level and the frequency of attacks were compared, the cut-off value of vitamin D was found to be 29.7 nmol/L.
CONCLUSIONS: In PFAPA patients with low vitamin D levels, the frequency and duration of PFAPA attacks were reduced with vitamin D supplementation. Especially at vitamin D level cut-off > 29.7 nmol/L, the frequency of attacks reduced significantly.

Concerns about violence against nurses and other medical personnel have increased during the COVID-19 pandemic. However, as of yet, limited systematic knowledge of such violence is available. Addressing this gap, we analyse the geographical distribution of, motivations behind, and contexts of collective attacks against health workers in the context of the COVID-19 pandemic. To do so, we systematically recorded and coded attack events worldwide from 1 March 2020 to 31 December 2021. We identify high-risk countries, attack characteristics, and the socio-economic contexts in which attacks tend to occur. Our results show that opposition against public health measures (28.5%), fears of infection (22.3%), and supposed lack of care (20.6%) were the most common reasons for attacks. Most attacks occurred in facilities (often related to a supposed lack of care) or while health workers were on duty in a public place (often due to opposition to public health measures). However, 17.9% of all attacks took place in off-duty settings. Democratic countries with high vaccination rates and strong health systems were relatively safe for nurses and doctors. Distrust in the skills of health workers and the science underlying health interventions is a major driver of collective attack risks and should be addressed before it turns violent. This study was not registered.

IoT devices have grown in popularity in recent years. Statistics show that the number of online IoT devices exceeded 35 billion in 2022. This rapid growth in adoption made these devices an obvious target for malicious actors. Attacks such as botnets and malware injection usually start with a phase of reconnaissance to gather information about the target IoT device before exploitation. In this paper, we introduce a machine-learning-based detection system for reconnaissance attacks based on an explainable ensemble model. Our proposed system aims to detect scanning and reconnaissance activity of IoT devices and counter these attacks at an early stage of the attack campaign. The proposed system is designed to be efficient and lightweight to operate in severely resource-constrained environments. When tested, the implementation of the proposed system delivered an accuracy of 99%. Furthermore, the proposed system showed low false positive and false negative rates at 0.6% and 0.05%, respectively, while maintaining high efficiency and low resource consumption.

To understand the impact and burden of disease experienced by patients with hereditary angioedema (HAE).
To determine whether the use of short message service (SMS) to communicate with patients with HAE facilitates the collection of attack rate, medication use, and quality of life measurements.
Patients aged 12 years and older with doctor-confirmed HAE C1-inhibitor deficiency types I and II were invited to participate. We devised a novel method for monitoring attacks by using questions weekly via SMS to gain a more accurate picture of the burden of HAE in Australian patients in real time.
A total of 2,648 weekly SMS messages were sent to 47 participants; 1,892 responses were received (71%). Participants reported 463 attacks across all treatment groups. Sixty percent of attacks were treated. Icatibant and C1-inhibitor concentrate were administered IV for 210 and 67 attacks, respectively. Of the 463 recorded attacks, 23 necessitated presentation to the hospital (5%), predominantly for facial and/or throat swelling. Several participants reported attacks (n = 186), which they chose not to treat. Most of those attacks were rated mildly severe. Twenty-one participants reported lost days owing to HAE attacks (44.7%). Fifty-eight attacks (17%) resulted in time away from work or school, equating to a total of 85.5 days lost.
This study was a first of its kind, real-world, prospective, observational study of Australian patients living with HAE. Despite the availability of effective on-demand therapies, HAE remains burdensome. Wider access to safe and effective prophylactic therapies is needed for patients living with HAE.